diff --git a/tsml_eval/publications/clustering/__init__.py b/tsml_eval/publications/clustering/__init__.py new file mode 100644 index 00000000..44d57b6f --- /dev/null +++ b/tsml_eval/publications/clustering/__init__.py @@ -0,0 +1 @@ +"""Files for clustering publications.""" diff --git a/tsml_eval/publications/clustering/kasba/README.md b/tsml_eval/publications/clustering/kasba/README.md new file mode 100644 index 00000000..31a510cd --- /dev/null +++ b/tsml_eval/publications/clustering/kasba/README.md @@ -0,0 +1,109 @@ +# πŸ“˜ KASBA: k-means Accelerated Stochastic Subgradient Barycentre Averaging +**Official Repository for the KASBA Time Series Clustering Paper** + +This repository accompanies the paper: + +> **Rock the KASBA: Blazingly Fast and Accurate Time Series Clustering** +> +> https://arxiv.org/abs/2411.17838 + +KASBA is a $k$-means clustering algorithm that uses the Move-Split-Merge (MSM) elastic distance at all stages of clustering, applies a randomised stochastic subgradient descent to find barycentre centroids, links each stage of clustering to accelerate convergence and exploits the metric property of MSM distance to avoid a large proportion of distance calculations. It is a versatile and scalable clusterer designed for real-world TSCL applications. It allows practitioners to balance runtime and clustering performance when similarity is best measured by an elastic distance. + +KASBA delivers state-of-the-art clustering performance while achieving 1–3 orders of magnitude speedups over existing elastic distance–based k-means algorithms. + +This repository contains the exact model configurations, experiment scripts, and visualisation tools used to produce the results in the paper. + +--- + +## πŸ“ Repository Structure + + kasba/ + β”œβ”€β”€ README.md # This file + β”œβ”€β”€ __init__.py + β”œβ”€β”€ _utils.py # Internal utilities used across the project + β”œβ”€β”€ _model_configuration.py # Definitions of all models and configurations used in experiments + β”œβ”€β”€ _experiment_script.py # Script used to run experiments on datasets + β”œβ”€β”€ kasba.ipynb # Notebook demonstrating how to run KASBA + β”œβ”€β”€ result_visualisation.ipynb # Notebook for generating CD diagrams, MCM plots, etc. + └── results/ # Raw CSV result files used in the paper + └── combined # Subfolder for combined results + └── k-shape-compare # Subfolders results in section 5.4 + └── section-5.1 # Subfolders results in section 5.1 + └── train-test # Subfolders for train and test results + └── section-5.1 # Subfolders results in section 5.1 + └── section-5.2 # Subfolders results in section 5.2 + └── section-5.3 # Subfolders results in section 5.3 + + +## πŸš€ Getting Started + +### Install dependencies + +Create and activate a virtual environment from tsml-eval: + + python3 -m venv venv + source venv/bin/activate + pip install -e . + +If you are reading this message you will have to install a specific branch +of aeon while we wait for a new release. Run the following command to install: + + pip uninstall aeon + pip install git+https://github.com/aeon-toolkit/aeon@kasba-results#egg=aeon + +Note: The project uses aeon, numpy, matplotlib, and other standard scientific Python packages. + +--- + +## πŸ§ͺ Running KASBA + +Minimal example from the kasba.ipynb notebook: + + from kasba import KASBA + from aeon.datasets import load_dataset + + X, y = load_dataset("GunPoint") + + model = KASBA( + n_clusters=2, + distance="msm", + distance_params={ + "c": 1.0 + }, + ) + + labels = model.fit_predict(X) + +The notebook demonstrates: + +- How to use KASBA with different elastic distances +- How to cluster multivariate or unequal-length time series +- How to run multiple initialisations +- How to inspect convergence behaviour + +--- + +## πŸ“Š Reproducing Figures (CD & MCM) + +Use the result_visualisation.ipynb notebook to generate: + +- Critical Difference diagrams +- Model Comparison Matrices +- Ranking curves and statistical tests + +--- + +## πŸ“œ Citation + +If you use KASBA in academic work, please cite the paper: + + C. Holder, A. Bagnall, Rock the kasba: Blazingly fast and accurate time + series clustering, arXiv preprint arXiv:2411.17838 (2024) + +(A full BibTeX entry will be added once the paper is published.) + +--- + +## 🀝 Contact + +For questions or queries please open an issue on tsml-eval. diff --git a/tsml_eval/publications/clustering/kasba/__init__.py b/tsml_eval/publications/clustering/kasba/__init__.py new file mode 100644 index 00000000..eea108c3 --- /dev/null +++ b/tsml_eval/publications/clustering/kasba/__init__.py @@ -0,0 +1 @@ +"""Files for Rock the KASBA.""" diff --git a/tsml_eval/publications/clustering/kasba/_experiment_script.py b/tsml_eval/publications/clustering/kasba/_experiment_script.py new file mode 100644 index 00000000..f2cc4850 --- /dev/null +++ b/tsml_eval/publications/clustering/kasba/_experiment_script.py @@ -0,0 +1,149 @@ +import sys + +import numpy as np + +from tsml_eval.experiments import ( + run_clustering_experiment as tsml_clustering_experiment, +) +from tsml_eval.publications.clustering.kasba._model_configuration import ( + EXPERIMENT_MODELS, +) +from tsml_eval.publications.clustering.kasba._utils import ( + _parse_command_line_bool, + check_experiment_results_exist, + load_dataset_from_file, +) + + +def run_threaded_clustering_experiment( + dataset: str, + clusterer_name: str, + dataset_path: str, + results_path: str, + combine_test_train: bool, + resample_id: int, +): + """Run clustering experiment. + + Parameters + ---------- + dataset : str + Dataset name. + distance : str + Distance string (assumed correct and final), e.g.: + "msm", "dtw", "soft_msm", "soft_dtw", + "soft_divergence_msm", "soft_divergence_dtw". + clusterer_str : str + Free-form label used only for naming/logging (not logic). + dataset_path : str + Path to the dataset. + results_path : str + Path to the results. + averaging_method : str + One of: "soft", "kasba", "petitjean_ba", "subgradient_ba". + combine_test_train : bool, default=False + Boolean indicating if data should be combined for test and train. + resample_id : int, default=0 + Integer indicating the resample id. + n_jobs : int default=-1 + Integer indicating the number of jobs to run in parallel. + """ + if clusterer_name not in EXPERIMENT_MODELS: + raise ValueError(f"Unknown clusterer_name '{clusterer_name}'") + + # Skip if results already exist + if check_experiment_results_exist( + model_name=clusterer_name, + dataset=dataset, + combine_test_train=combine_test_train, + path_to_results=results_path, + resample_id=resample_id, + ): + return ( + f"[SKIP] {clusterer_name} (resample {resample_id}): " + f"results already exist." + ) + + X_train, y_train, X_test, y_test = load_dataset_from_file( + dataset, + dataset_path, + normalize=True, + combine_test_train=combine_test_train, + resample_id=0, + ) + n_clusters = np.unique(y_train).size + + factory = EXPERIMENT_MODELS[clusterer_name] + clusterer = factory( + n_clusters=n_clusters, + random_state=resample_id, + n_jobs=1, + ) + + tsml_clustering_experiment( + X_train=X_train, + y_train=y_train, + clusterer=clusterer, + results_path=results_path, + X_test=X_test, + y_test=y_test, + n_clusters=n_clusters, + clusterer_name=clusterer_name, + dataset_name=dataset, + resample_id=resample_id, + data_transforms=None, + build_test_file=not combine_test_train, + build_train_file=True, + benchmark_time=True, + ) + print(f"[DONE] {clusterer_name} (resample {resample_id})") + + +# Boolean to toggle if running locally or via command line. +RUN_LOCALLY = True + +if __name__ == "__main__": + """NOTE: To run with command line arguments, set RUN_LOCALLY to False.""" + if RUN_LOCALLY: + print("RUNNING WITH TEST CONFIG") + + dataset = "GunPoint" + clusterer_name = "KASBA" + combine_test_train = True + + dataset_path = ( + "/Users/chrisholder/Documents/Research/datasets/UCR/Univariate_ts" + ) + results_path = "/Users/chrisholder/projects/kasba-experiments/full_results" + run_threaded_clustering_experiment( + dataset=dataset, + clusterer_name=clusterer_name, + dataset_path=dataset_path, + results_path=results_path, + combine_test_train=combine_test_train, + resample_id=0, + ) + + else: + if len(sys.argv) != 6: + print( + "Usage: python _clustering_experiment_all.py " + " " + "" + ) + sys.exit(1) + + dataset = str(sys.argv[1]) + clusterer_name = str(sys.argv[2]) + dataset_path = str(sys.argv[3]) + results_path = str(sys.argv[4]) + combine_test_train = _parse_command_line_bool(sys.argv[5]) + + run_threaded_clustering_experiment( + dataset=dataset, + clusterer_name=clusterer_name, + dataset_path=dataset_path, + results_path=results_path, + combine_test_train=combine_test_train, + resample_id=1, + ) diff --git a/tsml_eval/publications/clustering/kasba/_model_configuration.py b/tsml_eval/publications/clustering/kasba/_model_configuration.py new file mode 100644 index 00000000..d2bd4941 --- /dev/null +++ b/tsml_eval/publications/clustering/kasba/_model_configuration.py @@ -0,0 +1,261 @@ +from aeon.clustering import ( + KASBA, + BaseClusterer, + KSpectralCentroid, + TimeSeriesKMeans, + TimeSeriesKMedoids, + TimeSeriesKShape, +) + + +def kasba_clusterer(n_clusters: int, random_state: int, n_jobs: int) -> BaseClusterer: + return KASBA( + n_clusters=n_clusters, + distance="msm", + ba_subset_size=0.5, + initial_step_size=0.05, + max_iter=300, + tol=1e-6, + distance_params={"c": 1.0}, + decay_rate=0.1, + verbose=False, + random_state=random_state, + ) + + +def kasba_clusterer_vldb( + n_clusters: int, random_state: int, n_jobs: int +) -> BaseClusterer: + return KASBA( + n_clusters=n_clusters, + distance="msm", + ba_subset_size=0.5, + initial_step_size=0.05, + max_iter=100, + tol=1e-6, + distance_params={"c": 1.0}, + decay_rate=0.1, + verbose=False, + random_state=random_state, + ) + + +def kasba_twe_clusterer( + n_clusters: int, random_state: int, n_jobs: int +) -> BaseClusterer: + return KASBA( + n_clusters=n_clusters, + distance="twe", + ba_subset_size=0.5, + initial_step_size=0.05, + max_iter=300, + tol=1e-6, + distance_params={ + "lmbda": 0.01, + "nu": 2.0, + }, + decay_rate=0.1, + verbose=False, + random_state=random_state, + ) + + +def dba_clusterer(n_clusters: int, random_state: int, n_jobs: int) -> BaseClusterer: + return TimeSeriesKMeans( + n_clusters=n_clusters, + init="kmeans++", + distance="dtw", + n_init=1, + max_iter=300, + tol=1e-6, + verbose=False, + random_state=random_state, + averaging_method="ba", + distance_params=None, + average_params=None, + n_jobs=n_jobs, + ) + + +def shape_dba_clusterer( + n_clusters: int, random_state: int, n_jobs: int +) -> BaseClusterer: + return TimeSeriesKMeans( + n_clusters=n_clusters, + init="kmeans++", + distance="shape_dtw", + n_init=1, + max_iter=300, + tol=1e-6, + verbose=False, + random_state=random_state, + averaging_method="ba", + distance_params={"reach": 15}, + average_params={"reach": 15}, + n_jobs=n_jobs, + ) + + +def mba_clusterer(n_clusters: int, random_state: int, n_jobs: int) -> BaseClusterer: + return TimeSeriesKMeans( + n_clusters=n_clusters, + init="kmeans++", + distance="msm", + n_init=1, + max_iter=300, + tol=1e-6, + verbose=False, + random_state=random_state, + averaging_method="ba", + distance_params={"c": 1.0}, + average_params={"c": 1.0}, + n_jobs=n_jobs, + ) + + +def soft_dba_clusterer( + n_clusters: int, random_state: int, n_jobs: int +) -> BaseClusterer: + return TimeSeriesKMeans( + n_clusters=n_clusters, + init="kmeans++", + distance="soft_dtw", + n_init=1, + max_iter=300, + tol=1e-6, + verbose=False, + random_state=random_state, + averaging_method="soft", + distance_params={"gamma": 1.0}, + average_params={"gamma": 1.0}, + n_jobs=n_jobs, + ) + + +def euclid_clusterer(n_clusters: int, random_state: int, n_jobs: int) -> BaseClusterer: + return TimeSeriesKMeans( + n_clusters=n_clusters, + init="kmeans++", + distance="euclidean", + n_init=1, + max_iter=300, + tol=1e-6, + verbose=False, + random_state=random_state, + averaging_method="mean", + distance_params=None, + average_params=None, + n_jobs=n_jobs, + ) + + +def euclid_clusterer_vldb( + n_clusters: int, random_state: int, n_jobs: int +) -> BaseClusterer: + return TimeSeriesKMeans( + n_clusters=n_clusters, + init="random", + distance="euclidean", + n_init=1, + max_iter=100, + tol=1e-6, + verbose=False, + random_state=random_state, + averaging_method="mean", + distance_params=None, + average_params=None, + n_jobs=n_jobs, + ) + + +def msm_clusterer(n_clusters: int, random_state: int, n_jobs: int) -> BaseClusterer: + return TimeSeriesKMeans( + n_clusters=n_clusters, + init="kmeans++", + distance="msm", + n_init=1, + max_iter=300, + tol=1e-6, + verbose=False, + random_state=random_state, + averaging_method="mean", + distance_params={"c": 1.0}, + average_params=None, # This isn't used when mean selected + n_jobs=n_jobs, + ) + + +def k_sc_clusterer(n_clusters: int, random_state: int, n_jobs: int) -> BaseClusterer: + return KSpectralCentroid( + n_clusters=n_clusters, + max_shift=None, # This means it will be calculated automatically to length m + init="kmeans++", + n_init=1, + max_iter=300, + tol=1e-6, + verbose=False, + random_state=random_state, + n_jobs=n_jobs, + ) + + +def pam_clusterer(n_clusters: int, random_state: int, n_jobs: int) -> BaseClusterer: + return TimeSeriesKMedoids( + n_clusters=n_clusters, + init="kmeans++", + distance="msm", + method="pam", + n_init=1, + max_iter=300, + tol=1e-6, + verbose=False, + random_state=random_state, + distance_params={ + "c": 1.0, + }, + n_jobs=n_jobs, + ) + + +def kshape_clusterer(n_clusters: int, random_state: int, n_jobs: int) -> BaseClusterer: + return TimeSeriesKShape( + n_clusters=n_clusters, + centroid_init="kmeans++", + max_iter=300, + n_init=1, + random_state=random_state, + verbose=False, + tol=1e-6, + ) + + +def kshape_clusterer_vldb( + n_clusters: int, random_state: int, n_jobs: int +) -> BaseClusterer: + return TimeSeriesKShape( + n_clusters=n_clusters, + centroid_init="random", + max_iter=100, + n_init=1, + random_state=random_state, + verbose=True, + tol=1e-6, + ) + + +EXPERIMENT_MODELS = { + "KASBA": kasba_clusterer, + "DBA": dba_clusterer, + "shape-DBA": shape_dba_clusterer, + "soft-DBA": soft_dba_clusterer, + "MBA": mba_clusterer, + "Euclid": euclid_clusterer, + "MSM": msm_clusterer, + "k-Shape": kshape_clusterer, + "k-SC": k_sc_clusterer, + "PAM-MSM": pam_clusterer, + "KASBA-twe": kasba_twe_clusterer, + "KASBA-vldb": kasba_clusterer_vldb, + "Euclid-vldb": euclid_clusterer_vldb, + "k-Shape-vldb": kshape_clusterer_vldb, +} diff --git a/tsml_eval/publications/clustering/kasba/_utils.py b/tsml_eval/publications/clustering/kasba/_utils.py new file mode 100644 index 00000000..2c25c9e2 --- /dev/null +++ b/tsml_eval/publications/clustering/kasba/_utils.py @@ -0,0 +1,176 @@ +import csv +import os + +import numpy as np +from aeon.datasets import load_from_ts_file +from aeon.transformations.collection import Normalizer + +from tsml_eval.utils.resampling import stratified_resample_data + + +def load_results_from_csv(path: str) -> dict[str, dict[str, float]]: + """ + Load results from custom CSV format. + + Returns + ------- + dict[str, dict[str, float]] + { estimator: { dataset: score } } + """ + with open(path) as f: + reader = csv.reader(f) + + # Get header row + header = next(reader) + if header[0].lower().startswith("estimators"): + estimators = [h.strip() for h in header[1:]] + else: + raise ValueError("First row must begin with 'Estimators:'") + + # Output structure + results: dict[str, dict[str, float]] = {est: {} for est in estimators} + + # Process remaining rows + for row in reader: + if not row: + continue + + dataset = row[0].strip() + values = row[1:] + + if len(values) != len(estimators): + raise ValueError( + f"Row for dataset '{dataset}' has {len(values)} values " + f"but expected {len(estimators)}" + ) + + for est, val in zip(estimators, values): + results[est][dataset] = float(val) + + return results + + +def results_to_matrix( + results: dict[str, dict[str, float]], +) -> tuple[np.ndarray, list[str], list[str]]: + """ + Convert results dict into a (n_datasets, n_estimators) matrix. + + Returns + ------- + matrix : np.ndarray + Shape (n_datasets, n_estimators) + datasets : list[str] + estimators : list[str] + """ + estimators: list[str] = sorted(results.keys()) + datasets: list[str] = sorted({d for est in estimators for d in results[est]}) + + matrix = np.zeros((len(datasets), len(estimators)), dtype=float) + + for j, est in enumerate(estimators): + for i, ds in enumerate(datasets): + matrix[i, j] = results[est][ds] + + return matrix, datasets, estimators + + +def _parse_command_line_bool(s: str) -> bool: + """Parse a boolean from common CLI strings.""" + t = s.strip().lower() + if t in {"1", "true", "t", "yes", "y"}: + return True + if t in {"0", "false", "f", "no", "n"}: + return False + raise ValueError( + f"Invalid boolean value: {s!r}. Use one of: true/false/1/0/yes/no." + ) + + +def check_experiment_results_exist( + model_name: str, + dataset: str, + combine_test_train: bool, + path_to_results: str, + resample_id: int = 0, +) -> bool: + """ + Check if the results of the experiment already exist. + + Returns + ------- + bool + True if results already exist. + """ + path_to_train = os.path.join( + path_to_results, + model_name, + "Predictions", + dataset, + f"trainResample{resample_id}.csv", + ) + path_to_test = os.path.join( + path_to_results, + model_name, + "Predictions", + dataset, + f"testResample{resample_id}.csv", + ) + + if combine_test_train: + return os.path.exists(path_to_train) + else: + return os.path.exists(path_to_train) and os.path.exists(path_to_test) + + +def _normalize_data(X: np.ndarray) -> np.ndarray: + """Normalize time series collection data.""" + scaler = Normalizer() + return scaler.fit_transform(X) + + +def load_dataset_from_file( + dataset_name: str, + path_to_data: str, + normalize: bool = True, + combine_test_train: bool = False, + resample_id: int | None = None, +) -> tuple[np.ndarray, np.ndarray, np.ndarray | None, np.ndarray | None]: + """ + Load dataset from file, optionally doing stratified resampling. + + Returns + ------- + (X_train, y_train, X_test, y_test) + Or (X, y, None, None) if combine_test_train=True + """ + path_to_train_data = os.path.join( + path_to_data, f"{dataset_name}/{dataset_name}_TRAIN.ts" + ) + path_to_test_data = os.path.join( + path_to_data, f"{dataset_name}/{dataset_name}_TEST.ts" + ) + + X_train, y_train = load_from_ts_file(path_to_train_data) + X_test, y_test = load_from_ts_file(path_to_test_data) + + if not combine_test_train and resample_id is not None and resample_id > 0: + X_train, y_train, X_test, y_test = stratified_resample_data( + X_train, + y_train, + X_test, + y_test, + random_state=resample_id, + ) + + if combine_test_train: + X = np.concatenate((X_train, X_test), axis=0) + y = np.concatenate((y_train, y_test), axis=0) + if normalize: + X = _normalize_data(X) + return X, y, None, None + else: + if normalize: + X_train = _normalize_data(X_train) + X_test = _normalize_data(X_test) + return X_train, y_train, X_test, y_test diff --git a/tsml_eval/publications/clustering/kasba/kasba.ipynb b/tsml_eval/publications/clustering/kasba/kasba.ipynb index 66a06671..c13cb2eb 100644 --- a/tsml_eval/publications/clustering/kasba/kasba.ipynb +++ b/tsml_eval/publications/clustering/kasba/kasba.ipynb @@ -2,15 +2,261 @@ "cells": [ { "cell_type": "code", - "execution_count": null, "id": "initial_id", "metadata": { - "collapsed": true + "collapsed": true, + "ExecuteTime": { + "end_time": "2025-11-27T20:43:04.781507Z", + "start_time": "2025-11-27T20:43:03.689004Z" + } }, + "source": [ + "import warnings\n", + "\n", + "import numpy as np\n", + "from aeon.clustering import KASBA\n", + "from aeon.datasets import load_basic_motions, load_gunpoint, load_japanese_vowels\n", + "\n", + "warnings.filterwarnings(\"ignore\")" + ], "outputs": [], + "execution_count": 1 + }, + { + "metadata": { + "ExecuteTime": { + "end_time": "2025-11-27T20:43:13.736829Z", + "start_time": "2025-11-27T20:43:05.481062Z" + } + }, + "cell_type": "code", + "source": [ + "# Univariate example\n", + "uni_X_train, uni_y_train = load_gunpoint(split=\"train\")\n", + "uni_X_test, uni_y_test = load_gunpoint(split=\"test\")\n", + "\n", + "n_clusters = len(np.unique(uni_y_train))\n", + "\n", + "print(\n", + " f\"Train shape: {uni_X_train.shape}, Test shape: {uni_X_test.shape}, \"\n", + " f\"n_clusters: {n_clusters}\"\n", + ")\n", + "\n", + "univariate_KASBA = KASBA(\n", + " n_clusters=n_clusters,\n", + " distance=\"msm\",\n", + " ba_subset_size=0.5,\n", + " initial_step_size=0.05,\n", + " max_iter=300,\n", + " tol=1e-6,\n", + " distance_params={\"c\": 1.0},\n", + " decay_rate=0.1,\n", + " verbose=False,\n", + " random_state=0,\n", + ")\n", + "\n", + "univariate_KASBA.fit(uni_X_train)\n", + "\n", + "print(f\"Train labels: {univariate_KASBA.labels_}\")\n", + "\n", + "test_labels = univariate_KASBA.predict(uni_X_test)\n", + "\n", + "print(f\"Test labels: {test_labels}\")" + ], + "id": "30e7c72aad3b3aec", + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Train shape: (50, 1, 150), Test shape: (150, 1, 150), n_clusters: 2\n", + "Train labels: [1 1 1 1 1 1 0 0 0 0 1 0 0 0 1 0 1 1 0 0 1 0 0 0 1 0 0 0 0 0 1 0 0 1 1 1 0\n", + " 1 0 0 1 0 0 0 0 1 1 1 1 0]\n", + "Test labels: [0 1 0 0 1 1 0 0 1 1 1 0 1 0 0 1 1 1 1 1 0 0 1 1 0 0 0 0 1 1 1 0 0 1 1 1 1\n", + " 1 1 1 1 0 1 1 0 0 0 1 1 1 1 0 1 0 1 0 0 1 1 1 0 0 0 1 1 1 0 1 1 1 1 1 1 0\n", + " 0 1 1 0 0 1 0 0 0 1 1 1 0 1 1 1 1 0 1 0 1 1 1 0 0 1 0 0 0 1 1 1 1 0 1 1 1\n", + " 1 0 0 1 0 0 0 1 0 0 0 1 0 0 0 0 1 0 0 0 1 0 1 0 0 0 1 0 1 0 0 1 0 1 1 1 1\n", + " 0 0]\n" + ] + } + ], + "execution_count": 2 + }, + { + "metadata": { + "ExecuteTime": { + "end_time": "2025-11-27T20:43:15.161716Z", + "start_time": "2025-11-27T20:43:14.919546Z" + } + }, + "cell_type": "code", + "source": [ + "# Multivariate example\n", + "multi_X_train, multi_y_train = load_basic_motions(split=\"train\")\n", + "multi_X_test, multi_y_test = load_basic_motions(split=\"test\")\n", + "\n", + "n_clusters = len(np.unique(multi_y_train))\n", + "\n", + "print(\n", + " f\"Train shape: {multi_X_train.shape}, Test shape: {multi_X_test.shape}, \"\n", + " f\"n_clusters: {n_clusters}\"\n", + ")\n", + "\n", + "multivariate_KASBA = KASBA(\n", + " n_clusters=n_clusters,\n", + " distance=\"msm\",\n", + " ba_subset_size=0.5,\n", + " initial_step_size=0.05,\n", + " max_iter=300,\n", + " tol=1e-6,\n", + " distance_params={\"c\": 1.0},\n", + " decay_rate=0.1,\n", + " verbose=False,\n", + " random_state=0,\n", + ")\n", + "\n", + "multivariate_KASBA.fit(multi_X_train)\n", + "\n", + "print(f\"Train labels: {multivariate_KASBA.labels_}\")\n", + "\n", + "test_labels = multivariate_KASBA.predict(multi_X_test)\n", + "\n", + "print(f\"Test labels: {test_labels}\")" + ], + "id": "dd299ca3f1d1218a", + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Train shape: (40, 6, 100), Test shape: (40, 6, 100), n_clusters: 4\n", + "Train labels: [0 0 0 0 0 0 0 0 0 0 3 3 3 3 3 3 3 3 3 3 1 2 2 2 1 2 2 2 1 2 2 1 1 1 2 2 1\n", + " 1 2 2]\n", + "Test labels: [0 0 0 0 0 0 0 0 0 0 3 3 3 3 3 3 3 3 3 3 2 2 1 2 2 2 2 2 2 2 1 1 2 2 2 2 1\n", + " 1 2 2]\n" + ] + } + ], + "execution_count": 3 + }, + { + "metadata": { + "ExecuteTime": { + "end_time": "2025-11-27T19:32:35.976439Z", + "start_time": "2025-11-27T19:32:35.141208Z" + } + }, + "cell_type": "code", "source": [ - "# KESBA TSCL" - ] + "# Unequal length\n", + "unequal_X_train, unequal_y_train = load_japanese_vowels(split=\"train\")\n", + "unequal_X_test, unequal_y_test = load_japanese_vowels(split=\"test\")\n", + "\n", + "n_clusters = len(np.unique(unequal_y_train))\n", + "\n", + "print(\n", + " f\"Train n cases: {len(unequal_X_train)}, Test n cases: {len(unequal_X_test)}, \"\n", + " f\"n_clusters: {n_clusters}\"\n", + ")\n", + "print(f\"Train longest series length: {max(x.shape[1] for x in unequal_X_train)}\")\n", + "print(f\"Train shortest series length: {min(x.shape[1] for x in unequal_X_train)}\")\n", + "print(f\"Test longest series length: {max(x.shape[1] for x in unequal_X_test)}\")\n", + "print(f\"Test shortest series length: {min(x.shape[1] for x in unequal_X_test)}\")\n", + "\n", + "\n", + "def _pad_panel_ndims_length(X, max_len=None, value=0.0):\n", + " n_cases = len(X)\n", + " n_dims = X[0].shape[0]\n", + "\n", + " if max_len is None:\n", + " max_len = max(x.shape[1] for x in X)\n", + "\n", + " padded = np.full((n_cases, n_dims, max_len), value, dtype=float)\n", + "\n", + " for i, x in enumerate(X):\n", + " length = x.shape[1]\n", + " padded[i, :, :length] = x\n", + "\n", + " return padded\n", + "\n", + "\n", + "all_X = list(unequal_X_train) + list(unequal_X_test)\n", + "global_max_len = max(x.shape[1] for x in all_X)\n", + "\n", + "unequal_X_train = _pad_panel_ndims_length(\n", + " unequal_X_train, max_len=global_max_len, value=0.0\n", + ")\n", + "unequal_X_test = _pad_panel_ndims_length(\n", + " unequal_X_test, max_len=global_max_len, value=0.0\n", + ")\n", + "\n", + "print(f\"Padded train shape: {unequal_X_train.shape}\")\n", + "print(f\"Padded test shape: {unequal_X_test.shape}\")\n", + "\n", + "\n", + "print(\n", + " f\"Padded train shape: {unequal_X_train.shape}, Padded test \"\n", + " f\"shape: {unequal_X_test.shape}, n_clusters: {n_clusters}\"\n", + ")\n", + "\n", + "\n", + "unequal_KASBA = KASBA(\n", + " n_clusters=n_clusters,\n", + " distance=\"msm\",\n", + " ba_subset_size=0.5,\n", + " initial_step_size=0.05,\n", + " max_iter=300,\n", + " tol=1e-6,\n", + " distance_params={\"c\": 1.0},\n", + " decay_rate=0.1,\n", + " verbose=False,\n", + " random_state=0,\n", + ")\n", + "\n", + "unequal_KASBA.fit(unequal_X_train)\n", + "\n", + "print(f\"Train labels: {unequal_KASBA.labels_}\")\n", + "\n", + "test_labels = unequal_KASBA.predict(unequal_X_test)\n", + "\n", + "print(f\"Test labels: {test_labels}\")" + ], + "id": "6d86054f8842dcee", + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Train n cases: 270, Test n cases: 370, n_clusters: 9\n", + "Train longest series length: 26\n", + "Train shortest series length: 7\n", + "Test longest series length: 29\n", + "Test shortest series length: 7\n", + "Padded train shape: (270, 12, 29)\n", + "Padded test shape: (370, 12, 29)\n", + "Padded train shape: (270, 12, 29), Padded test shape: (370, 12, 29), n_clusters: 9\n", + "Train labels: [8 8 8 8 8 8 8 5 8 5 8 3 5 5 1 5 5 8 5 5 5 8 8 8 5 5 2 5 2 5 5 5 4 4 4 4 4\n", + " 4 4 6 4 2 4 4 4 4 4 4 4 2 4 4 2 2 4 4 2 4 4 4 6 3 3 3 3 4 3 3 3 3 3 3 3 3\n", + " 3 4 3 3 3 3 3 3 4 3 3 3 2 3 3 3 6 6 6 6 6 6 6 6 6 6 6 6 4 6 6 6 6 6 4 6 4\n", + " 4 4 6 6 6 6 4 6 6 2 1 1 1 1 1 1 1 1 1 1 1 1 1 5 1 5 1 1 1 1 1 1 1 1 1 1 1\n", + " 1 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 3 3 7 3\n", + " 3 7 7 7 3 7 7 7 7 7 7 7 7 7 3 7 7 7 7 7 7 7 7 7 7 1 3 2 2 2 2 2 2 2 2 2 2\n", + " 5 2 2 2 2 2 2 2 2 2 2 3 2 2 2 3 2 5 5 2 5 5 5 5 5 5 5 2 2 5 5 2 1 2 2 3 2\n", + " 3 3 5 2 1 2 5 1 2 1 2]\n", + "Test labels: [5 5 8 5 8 5 5 8 5 8 8 3 5 5 5 2 5 5 5 5 0 5 8 5 5 5 5 1 5 5 5 5 4 4 4 4 2\n", + " 4 4 4 4 4 4 2 4 4 3 4 4 4 2 4 4 4 2 4 2 4 4 4 4 4 2 2 4 4 4 5 3 3 3 3 3 3\n", + " 2 3 3 3 3 3 3 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 3\n", + " 3 3 3 2 3 3 3 3 2 3 3 3 3 3 3 3 3 2 3 3 3 3 3 3 3 3 3 3 3 4 3 3 3 3 3 3 3\n", + " 3 3 3 3 3 3 6 2 4 6 6 4 6 6 6 6 6 6 6 6 6 6 6 6 2 6 6 6 6 6 3 2 6 4 6 6 6\n", + " 2 6 6 6 6 6 6 6 3 4 2 6 6 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 5 1 1 8 1 1 1\n", + " 1 1 1 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 7 3 3 3 3 3 7\n", + " 7 7 7 7 7 7 3 7 3 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 2 1 3 2 2\n", + " 2 2 2 2 3 2 2 5 2 2 2 2 2 2 2 2 2 1 2 2 2 2 2 2 2 2 2 2 5 5 2 2 5 2 3 2 2\n", + " 2 3 2 2 2 2 2 2 5 2 5 5 5 5 5 2 5 5 2 5 5 5 2 5 5 5 5 8 3 1 5 1 2 1 1 1 3]\n" + ] + } + ], + "execution_count": 8 } ], "metadata": { diff --git a/tsml_eval/publications/clustering/kasba/result_visualisation.ipynb b/tsml_eval/publications/clustering/kasba/result_visualisation.ipynb new file mode 100644 index 00000000..8ecee4d2 --- /dev/null +++ b/tsml_eval/publications/clustering/kasba/result_visualisation.ipynb @@ -0,0 +1,154 @@ +{ + "cells": [ + { + "metadata": { + "ExecuteTime": { + "end_time": "2025-11-27T20:01:16.845750Z", + "start_time": "2025-11-27T20:01:16.843170Z" + } + }, + "cell_type": "code", + "source": [ + "import os\n", + "\n", + "import pandas as pd\n", + "from aeon.visualisation.results._critical_difference import plot_critical_difference\n", + "from aeon.visualisation.results._mcm import create_multi_comparison_matrix\n", + "\n", + "from tsml_eval.publications.clustering.kasba._utils import (\n", + " load_results_from_csv,\n", + " results_to_matrix,\n", + ")\n", + "\n", + "RESULT_PATH = f\"{os.getcwd()}/results\"\n", + "METRICS_TO_EVALUATE = [\"ami\", \"ari\", \"clacc\", \"nmi\"]" + ], + "id": "549ddde1cd70fe1a", + "outputs": [], + "execution_count": 10 + }, + { + "metadata": { + "ExecuteTime": { + "end_time": "2025-11-27T19:59:04.566623Z", + "start_time": "2025-11-27T19:59:04.423208Z" + } + }, + "cell_type": "code", + "source": [ + "# CDs plot for test-train experiment\n", + "TRAIN_TEST_RESULT_PATH = f\"{RESULT_PATH}/train-test/section-5.1\"\n", + "METHODS = [\"DBA\", \"Euclid\", \"KASBA\", \"MSM\", \"Shape-DBA\", \"k-SC\", \"k-Shape\"]\n", + "\n", + "for metric in METRICS_TO_EVALUATE:\n", + " metric_res_path = f\"{TRAIN_TEST_RESULT_PATH}/{metric}_mean.csv\"\n", + " mat, datasets, estimators = results_to_matrix(\n", + " load_results_from_csv(metric_res_path)\n", + " )\n", + " fig, ax, *_ = plot_critical_difference(mat, METHODS, alpha=0.05)\n", + " fig.suptitle(f\"{metric.upper()}\", fontsize=16)\n", + " fig.subplots_adjust(top=0.88)" + ], + "id": "81c1bbd3ff1beeb9", + "outputs": [ + { + "data": { + "text/plain": [ + "
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" 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" 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" 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" + }, + "metadata": {}, + "output_type": "display_data", + "jetTransient": { + "display_id": null + } + } + ], + "execution_count": 9 + }, + { + "metadata": { + "ExecuteTime": { + "end_time": "2025-11-27T20:03:25.008463Z", + "start_time": "2025-11-27T20:03:24.652072Z" + } + }, + "cell_type": "code", + "source": [ + "# MCM plot for test-train experiment\n", + "CLACC_PATH = f\"{TRAIN_TEST_RESULT_PATH}/clacc_mean.csv\"\n", + "\n", + "df = pd.read_csv(CLACC_PATH)\n", + "df_no_first = df.iloc[:, 1:]\n", + "\n", + "plot = create_multi_comparison_matrix(df_no_first, font_size=17)" + ], + "id": "7c2d1d024b296f7", + "outputs": [ + { + "data": { + "text/plain": [ + "
" + ], + "image/png": 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" + }, + "metadata": {}, + "output_type": "display_data", + "jetTransient": { + "display_id": null + } + } + ], + "execution_count": 13 + } + ], + "metadata": { + "kernelspec": { + "name": "python3", + "language": "python", + "display_name": "Python 3 (ipykernel)" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/tsml_eval/publications/clustering/kasba/results/combined/k-shape-compare/README.md b/tsml_eval/publications/clustering/kasba/results/combined/k-shape-compare/README.md new file mode 100644 index 00000000..647656b0 --- /dev/null +++ b/tsml_eval/publications/clustering/kasba/results/combined/k-shape-compare/README.md @@ -0,0 +1,11 @@ +# K-Shape Compare +The results in this section are used for Section 5.4 of the paper. Each clusterer +is setup with the experiment setup outlined in [1]. We set each clusterer to use a +maximum of 100 iterations. For k-Shape and k-AVG we use random initialisation. For +KASBA we use the elastic kmeans++. We run the experiment 10 times and average the +results. Each experiment uses a different random seed (0, 1, ..., 9). + +## References +[1] Paparrizos J, Bogireddy SPTR (2025). *Time-series clustering: A comprehensive study of +data mining, machine learning, and deep learning methods*. Proceedings of the VLDB +Endowment, 18(11):4380–4395. https://doi.org/10.14778/3749646.3749700 diff --git a/tsml_eval/publications/clustering/kasba/results/combined/k-shape-compare/ami_mean.csv b/tsml_eval/publications/clustering/kasba/results/combined/k-shape-compare/ami_mean.csv new file mode 100644 index 00000000..9203df0b --- /dev/null +++ b/tsml_eval/publications/clustering/kasba/results/combined/k-shape-compare/ami_mean.csv @@ -0,0 +1,113 @@ +clacc_mean.csvEstimators:,KASBA,k-AVG,k-Shape +ACSF1,0.4173623098640766,0.3713329426105463,0.3321424868672949 +Adiac,0.49542606064349803,0.47406484186418874,0.4745376382897152 +ArrowHead,0.2338767488541643,0.2521575389794862,0.2560161995293391 +BME,0.20483636983666992,0.19510627320701934,0.27791837038361955 +Beef,0.19289126982737312,0.22271741109906093,0.1964101952351905 +BeetleFly,0.09287806025721294,0.023162527166278528,0.03285179476323776 +BirdChicken,0.005660178584827228,0.05091038807206011,0.05492656891297315 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+FiftyWords,0.6138054710108201,0.49045808759400267,0.548488940161793 +Fish,0.49142152959608554,0.27640677530250335,0.2965168606225613 +FordA,0.0359241555551409,-4.937416421121501e-05,0.09803561672250302 +FordB,0.016356420349255184,0.00021446507120829032,0.02006228008284903 +FreezerRegularTrain,0.21174421937620594,0.2203973353984164,0.21129450584059595 +FreezerSmallTrain,0.2121254638070987,0.22149333659193657,0.21171650342840714 +GunPoint,-0.003574986429085745,-0.0036472861196852105,-0.0036472861196852105 +GunPointAgeSpan,0.062445120116509725,0.29374768845544297,0.03343461049568726 +GunPointMaleVersusFemale,0.5277046970815005,-0.00139978768796447,0.624445545800629 +GunPointOldVersusYoung,0.052276656770055406,0.2268476427076022,0.023852297785746292 +Ham,0.0514425555952515,0.03849200456609932,0.03306034568233876 +HandOutlines,0.06149917848875562,0.21056589114293747,0.2505756881167668 +Haptics,0.11151816217685968,0.07712838476002767,0.08468473493523547 +Herring,0.013588767464761616,0.0017331270580053545,0.0024246941781640003 +HouseTwenty,0.17906984272508691,0.07331791524042816,0.04355940776139604 +InlineSkate,0.06644998064228134,0.027569616229629716,0.09439343075434888 +InsectEPGRegularTrain,0.21589139985600028,0.21305274950214542,0.3416224699949666 +InsectEPGSmallTrain,0.1868261888239981,0.17319500965119913,0.3375457047676096 +InsectWingbeatSound,0.5283993379886852,0.5174611029533154,0.4302257943255948 +ItalyPowerDemand,0.1479222103879517,0.0005345216490067726,0.1967411402820766 +LargeKitchenAppliances,0.10052480735270905,0.028164330496428087,0.15743364168996138 +Lightning2,0.06759200765607835,0.03305535306928044,0.09939977579608274 +Lightning7,0.4819721614024178,0.3586441295808024,0.4932450250937025 +Mallat,0.8779375319643536,0.8597049835422697,0.908140783052217 +Meat,0.5609515896054097,0.5825746665781111,0.5549530364003002 +MedicalImages,0.22543618280057537,0.22798019441135517,0.2045540434733955 +MiddlePhalanxOutlineAgeGroup,0.39408148810681914,0.3923029269780952,0.3937150180745704 +MiddlePhalanxOutlineCorrect,-0.0001628584905732526,-0.00010092397524351533,0.00012121324565167656 +MiddlePhalanxTW,0.4104197808866301,0.4124035824544851,0.4103381105382365 +MixedShapesRegularTrain,0.490920516694809,0.5040421046297932,0.4606735079772826 +MixedShapesSmallTrain,0.48773824000365573,0.5098709232467219,0.5130467582261082 +MoteStrain,0.41845593309068246,0.30065579897501965,0.4923577888021466 +NonInvasiveFetalECGThorax1,0.7349185756734623,0.6994512014354922,0.6938680830276749 +NonInvasiveFetalECGThorax2,0.7782581570202552,0.7568596462520807,0.7596175862360307 +OSULeaf,0.24477810329494448,0.20035071265414786,0.35729374420001614 +OliveOil,0.6251130077311702,0.6036119493793588,0.5901386654265026 +PhalangesOutlinesCorrect,0.0074538094489972105,0.009846783788464531,0.00992524297346492 +Phoneme,0.22652610375645765,0.07048194729194253,0.12875709410451774 +PigAirwayPressure,0.06457440927814831,0.049777580636910256,0.11630878014269068 +PigArtPressure,0.35871767675918853,0.17134865108314573,0.45457362967057946 +PigCVP,0.20943364575642578,0.024826082384248122,0.33495773182598065 +Plane,0.9093648996086767,0.808724012953166,0.8776819248690794 +PowerCons,0.23247257629523826,0.033975081570356835,0.15374583475729042 +ProximalPhalanxOutlineAgeGroup,0.5244366558159278,0.45924294227905704,0.4632770049268994 +ProximalPhalanxOutlineCorrect,0.08176327024395715,0.0865001254793686,0.08886272950604637 +ProximalPhalanxTW,0.5355363898860505,0.4892678927380003,0.5011715208795797 +RefrigerationDevices,0.1049406069150752,0.001201330871326468,0.00895023861788483 +Rock,0.2381257359534601,0.31611611900134673,0.2752898766354374 +ScreenType,0.01955023419197946,0.017287291606654875,0.009246658768987835 +SemgHandGenderCh2,0.017947088130876494,0.0790669583553992,0.05772938594179409 +SemgHandMovementCh2,0.14319399722295642,0.20742291626121512,0.23236559831043996 +SemgHandSubjectCh2,0.28803067303277546,0.28385531110055173,0.28097004344298615 +ShapeletSim,0.006916837834536643,0.001478188779091509,0.4271798412224478 +ShapesAll,0.6306569756155499,0.5774692068068434,0.6357875069323606 +SmallKitchenAppliances,0.12944764737905656,0.01341531875211761,0.03644640872245658 +SmoothSubspace,0.31175065649833444,0.3511887853771004,0.11577018969056944 +SonyAIBORobotSurface1,0.18674669525408572,0.3094252904546436,0.3721948642353832 +SonyAIBORobotSurface2,0.2150951359818038,0.23874977993413857,0.1022382725410105 +StarLightCurves,0.6033738770651589,0.6020270516391226,0.6180890150466982 +Strawberry,0.09290356123471993,0.12262822341653734,0.12148099574954083 +SwedishLeaf,0.6374409926635455,0.5258205154466694,0.5605850799986818 +Symbols,0.8422362210628801,0.776277188134129,0.8063760914650693 +SyntheticControl,0.8084521733159965,0.7643796848951396,0.6917178112038328 +ToeSegmentation1,0.06653597141970352,-0.0019966478060725037,3.1569590857944733e-05 +ToeSegmentation2,0.07655737138037162,0.0037557274509800237,0.21585251224501203 +Trace,0.5398820608903226,0.5013543743228092,0.6944235481422139 +TwoLeadECG,0.06303458978817375,0.002985584917160977,0.06763287627996914 +TwoPatterns,0.1015393020808878,0.019604878785422185,0.33759386490326765 +UMD,0.23798154791412557,0.20288261874500027,0.19186150037593128 +UWaveGestureLibraryAll,0.4826795215339509,0.6703606498445359,0.6723718897067885 +UWaveGestureLibraryX,0.400365319700307,0.44026526782222986,0.4602520436039569 +UWaveGestureLibraryY,0.4082316973960999,0.432558911138336,0.34635635506617923 +UWaveGestureLibraryZ,0.390371283040842,0.41429349119984965,0.46236238417603814 +Wafer,0.0004422963050001841,-1.6724768273275335e-05,0.013950494023755866 +Wine,-0.00068104329562481,-0.002128206745339271,-0.006237094168820739 +WordSynonyms,0.3974913825266973,0.34070464270442835,0.39857973191731644 +Worms,0.11237908106530026,0.02605668908068906,0.05029123113992988 +WormsTwoClass,0.011937291838388145,-0.0002221232737485146,0.0007495139477645316 +Yoga,0.0008224775549168604,0.0005728022111783426,-2.1142732676625115e-05 diff --git a/tsml_eval/publications/clustering/kasba/results/combined/k-shape-compare/ari_mean.csv b/tsml_eval/publications/clustering/kasba/results/combined/k-shape-compare/ari_mean.csv new file mode 100644 index 00000000..ec64538d --- /dev/null +++ b/tsml_eval/publications/clustering/kasba/results/combined/k-shape-compare/ari_mean.csv @@ -0,0 +1,113 @@ +Estimators:,KASBA,k-AVG,k-Shape +ACSF1,0.22045754202433523,0.1665736616911258,0.14628523403261848 +Adiac,0.25333288676613425,0.24356863328271924,0.23457072592937234 +ArrowHead,0.20547683652298132,0.19635230997328576,0.19279830539922757 +BME,0.16785543650810722,0.13482870045430267,0.188211115374291 +Beef,0.09312184905853199,0.10777932416609212,0.10638843446378099 +BeetleFly,0.10674111246922371,0.0307554278862677,0.04097455807172601 +BirdChicken,-0.007644507339259877,0.0671668210830713,0.06743647376221458 +CBF,0.42049494107265784,0.3355437975826473,0.6743800834211983 +Car,0.2466451376796103,0.14894662578138945,0.13378536341737032 +Chinatown,0.21131339661381876,0.1267994936949273,0.045222413151416174 +ChlorineConcentration,0.003148722088236589,0.00018187340569461065,-0.0010137331297468124 +CinCECGTorso,0.10957030660497198,0.16208548201333886,0.036680813971274664 +Coffee,0.4052157607544847,0.4874173726610736,0.486569235574868 +Computers,0.03172337859910962,-0.0005741258710670808,0.055005776134865146 +CricketX,0.11398320492746575,0.0987579049476516,0.1891686542600158 +CricketY,0.16911465137982967,0.11664509613057705,0.20158634811676798 +CricketZ,0.1074894627714607,0.10851718308268295,0.17978369687445853 +Crop,0.25243830905658177,0.2640067219983789,0.24990893621919308 +DiatomSizeReduction,0.6627539963072087,0.8666187012189932,0.7698469522482503 +DistalPhalanxOutlineAgeGroup,0.4359159383020123,0.3279875759467432,0.4041430795352953 +DistalPhalanxOutlineCorrect,-0.0008989873052559696,-0.001070553507461574,0.000861010261751331 +DistalPhalanxTW,0.4624080353230665,0.5529378600447333,0.5144513758953548 +ECG200,0.18681289890476896,0.16946167610401108,0.22285728932353593 +ECG5000,0.519528555295479,0.4967767429119063,0.5163348563496869 +ECGFiveDays,0.13938721812943844,5.013259792589527e-05,0.7669250895275855 +EOGHorizontalSignal,0.1819663687039975,0.19117284478312127,0.22276674552136927 +EOGVerticalSignal,0.1342601523144803,0.15538795967842156,0.20633389373398173 +Earthquakes,-0.006006951519559525,0.0012690073974694202,0.02147944919970729 +ElectricDevices,0.1542448796077287,0.18209642776060975,0.08579723811319082 +EthanolLevel,0.00249431081504195,0.003336314014488637,0.003345913746716175 +FaceAll,0.6295724917050867,0.21365940470636424,0.4332262098627625 +FaceFour,0.694272598176637,0.33581303671144835,0.37877959555195295 +FacesUCR,0.6076492624330426,0.2129454987554737,0.4413141244071035 +FiftyWords,0.42403833053207507,0.27100416619630413,0.35127522403776995 +Fish,0.3643907853660799,0.17008162754112893,0.18318703940022468 +FordA,0.022215423807317263,-7.956526883985079e-05,0.13243595540541692 +FordB,0.016719778880224977,0.00032287578588037166,0.027802413067945286 +FreezerRegularTrain,0.27551350413834463,0.28849044211733965,0.2774183873923949 +FreezerSmallTrain,0.2752340875178022,0.28980974554394295,0.27795310755492103 +GunPoint,-0.004949492572190557,-0.00505050505050505,-0.00505050505050505 +GunPointAgeSpan,0.06571576279048497,0.2564975021015511,0.04210027745062535 +GunPointMaleVersusFemale,0.5203265157224356,-0.0005237911099590341,0.6496548327080618 +GunPointOldVersusYoung,0.04142293833576739,0.17753987775270733,0.03390547589524497 +Ham,0.054515377971241355,0.052129750471043845,0.04630894057979952 +HandOutlines,0.07292175075627344,0.2588875127635982,0.35984755926470635 +Haptics,0.09497705318041619,0.05697021820808562,0.06339547156507033 +Herring,0.01957067912361296,0.004415104144308464,0.004112630020957257 +HouseTwenty,0.21662957775184077,0.08657219385142882,0.06488214120218132 +InlineSkate,0.031720119517738156,0.01154185398025235,0.04340413903344681 +InsectEPGRegularTrain,0.2162631139985852,0.21122636903645536,0.33419807212454217 +InsectEPGSmallTrain,0.16595671962285524,0.16429859503997218,0.33242024095885253 +InsectWingbeatSound,0.354519383395372,0.3420265021631586,0.23906134905503418 +ItalyPowerDemand,0.1687343451798203,0.0003042317856476606,0.2275221905791096 +LargeKitchenAppliances,0.07347145064724603,0.023098434749388743,0.16200139402926889 +Lightning2,0.0987339277180684,0.05731033852346197,0.0632231698136255 +Lightning7,0.34047597892053794,0.2446383009448027,0.3555405893451767 +Mallat,0.7588134645106753,0.6939701907702372,0.8025192474891452 +Meat,0.4747900157320302,0.5271530896398403,0.48689746500060577 +MedicalImages,0.07170465324205728,0.04609239801471794,0.06578549111696809 +MiddlePhalanxOutlineAgeGroup,0.39138623010339973,0.40708228452881656,0.42559531620950974 +MiddlePhalanxOutlineCorrect,-0.003057970547361612,-0.0035521567348166445,-0.0038005047646403277 +MiddlePhalanxTW,0.3829113081579812,0.4002159930081145,0.38222792788500026 +MixedShapesRegularTrain,0.4545288567979136,0.463515665603197,0.37352045461600963 +MixedShapesSmallTrain,0.4526027345006941,0.4741968221904638,0.4543839290898499 +MoteStrain,0.500202653986608,0.3893548900849384,0.5986084747754776 +NonInvasiveFetalECGThorax1,0.4855385161539722,0.43341399005496173,0.40362890694077047 +NonInvasiveFetalECGThorax2,0.5335235952912766,0.5115831073963953,0.4956993101656967 +OSULeaf,0.18284710034841867,0.1454384660920242,0.261980213284209 +OliveOil,0.6442852999960604,0.5934675056521277,0.6146252289390034 +PhalangesOutlinesCorrect,0.007079487536343537,0.010542697394235096,0.010671491834589552 +Phoneme,0.07510273892728762,0.017254123085613183,0.037717155403790587 +PigAirwayPressure,0.026967017174503154,0.02397615046100081,0.04961615897758079 +PigArtPressure,0.21285570576367094,0.08918371025071564,0.2830396972459327 +PigCVP,0.10534852438143161,0.009893653397402552,0.21638624661373837 +Plane,0.7985537316561163,0.6585408763566428,0.7837098522711712 +PowerCons,0.2721460625118288,0.03828668084711428,0.17891482335036724 +ProximalPhalanxOutlineAgeGroup,0.5343748847178457,0.44150371043977243,0.4593945952584826 +ProximalPhalanxOutlineCorrect,0.06468874734849475,0.06757990326837464,0.06817228069249599 +ProximalPhalanxTW,0.4866193259998465,0.3845481800428983,0.4111019164019029 +RefrigerationDevices,0.10042126701370084,0.0013257268018801252,0.008513570621908615 +Rock,0.1732310072611712,0.22734776457613134,0.19914623189231237 +ScreenType,0.02256315960359607,0.017747016742616546,0.00991086199859829 +SemgHandGenderCh2,0.023583150876124066,0.10000631547788116,0.09268975612088583 +SemgHandMovementCh2,0.09013144008645049,0.12681840621647417,0.1446340625857451 +SemgHandSubjectCh2,0.21614213546689404,0.20815018030202026,0.2177294878331062 +ShapeletSim,0.006536589158853245,0.0020450479164982743,0.4245715390595054 +ShapesAll,0.3757684369478955,0.3629035912116624,0.4152193793321346 +SmallKitchenAppliances,0.11239127340256924,0.004877568905959377,0.0233393858362785 +SmoothSubspace,0.2924596031948413,0.34502825136886883,0.11345683817170538 +SonyAIBORobotSurface1,0.1794137203785658,0.23141820310867828,0.36448804327531964 +SonyAIBORobotSurface2,0.296566609393439,0.3214270202896314,0.15155689451886617 +StarLightCurves,0.518401712470443,0.5198663806254121,0.5317466942827987 +Strawberry,-0.005704975462964687,-0.019398783006872176,-0.01918084988317377 +SwedishLeaf,0.39448208365841575,0.300263888434408,0.3458913692043159 +Symbols,0.7191063339894483,0.6295367734912197,0.6871962905925646 +SyntheticControl,0.6800423767498168,0.5968222349736465,0.5706551313587476 +ToeSegmentation1,0.0636815172588968,-0.0027334117298041236,0.0009193454095800744 +ToeSegmentation2,0.13478149420891236,-0.0019748447492720853,0.26751578249085783 +Trace,0.38951668081931884,0.3431832582711716,0.5720790293043678 +TwoLeadECG,0.07684680461439652,0.004126415409795284,0.08840126986967231 +TwoPatterns,0.08223282006583611,0.017476068908866018,0.235865868502318 +UMD,0.18357176595369104,0.14024053359460378,0.14510691931485367 +UWaveGestureLibraryAll,0.3887553407387051,0.5697149406378024,0.6066358222351937 +UWaveGestureLibraryX,0.32393468383584667,0.3486280584206378,0.35425664060379597 +UWaveGestureLibraryY,0.3127147021538953,0.32634634077556607,0.24819961706935983 +UWaveGestureLibraryZ,0.2930977351274676,0.30945903544688,0.3503805631263713 +Wafer,0.00184642905912972,0.003605161666667726,0.017614482348466638 +Wine,-0.004602334800405382,-0.004171829729738254,-0.005187919471714703 +WordSynonyms,0.2366833692286247,0.1590419956244062,0.21440175444022952 +Worms,0.0844134223806284,0.013012113653081286,0.034003984934994104 +WormsTwoClass,0.0048530675025704895,-0.0008483808835680855,0.00023100012245647647 +Yoga,2.162276014828615e-05,-0.000617916880703451,-0.000236423109837167 diff --git a/tsml_eval/publications/clustering/kasba/results/combined/k-shape-compare/clacc_mean.csv b/tsml_eval/publications/clustering/kasba/results/combined/k-shape-compare/clacc_mean.csv new file mode 100644 index 00000000..be706846 --- /dev/null +++ b/tsml_eval/publications/clustering/kasba/results/combined/k-shape-compare/clacc_mean.csv @@ -0,0 +1,113 @@ +nmi_mean.csvEstimators:,KASBA,k-AVG,k-Shape +ACSF1,0.41900000000000004,0.33949999999999997,0.32599999999999996 +Adiac,0.3943661971830986,0.3790012804097311,0.3737516005121639 +ArrowHead,0.5492890995260664,0.49810426540284364,0.5052132701421801 +BME,0.5383333333333333,0.5033333333333333,0.5744444444444444 +Beef,0.38166666666666665,0.4066666666666666,0.41166666666666674 +BeetleFly,0.64,0.6024999999999999,0.6075 +BirdChicken,0.5475,0.65,0.6200000000000001 +CBF,0.7192473118279571,0.6394623655913978,0.8609677419354839 +Car,0.5833333333333333,0.5416666666666667,0.5133333333333333 +Chinatown,0.7300275482093663,0.6564738292011019,0.6214876033057852 +ChlorineConcentration,0.3939633155328535,0.38558161133039237,0.38272579521708844 +CinCECGTorso,0.4053521126760563,0.4306338028169014,0.3664788732394367 +Coffee,0.7696428571428572,0.8196428571428573,0.8339285714285714 +Computers,0.583,0.515,0.6185999999999999 +CricketX,0.29525641025641025,0.26192307692307687,0.3741025641025641 +CricketY,0.32858974358974363,0.2819230769230769,0.37615384615384617 +CricketZ,0.29192307692307684,0.2703846153846154,0.3573076923076924 +Crop,0.36690000000000006,0.37787916666666665,0.3708458333333333 +DiatomSizeReduction,0.7844720496894411,0.9142857142857143,0.8360248447204969 +DistalPhalanxOutlineAgeGroup,0.7283858998144713,0.6742115027829314,0.7189239332096474 +DistalPhalanxOutlineCorrect,0.5068493150684932,0.5018264840182648,0.5277397260273973 +DistalPhalanxTW,0.5150278293135436,0.5680890538033394,0.5510204081632653 +ECG200,0.7275,0.7224999999999999,0.7430000000000001 +ECG5000,0.69488,0.63468,0.66236 +ECGFiveDays,0.668212669683258,0.5169683257918551,0.93789592760181 +EOGHorizontalSignal,0.3301104972375691,0.373756906077348,0.3802486187845304 +EOGVerticalSignal,0.30524861878453036,0.3301104972375691,0.38439226519337016 +Earthquakes,0.5440347071583514,0.5219088937093275,0.6477223427331887 +ElectricDevices,0.34853639478271325,0.3947286169381499,0.31183506641822445 +EthanolLevel,0.28396414342629483,0.29362549800796817,0.2931274900398407 +FaceAll,0.6866222222222221,0.36844444444444446,0.5881333333333334 +FaceFour,0.7928571428571429,0.58125,0.6142857142857142 +FacesUCR,0.6907555555555556,0.36777777777777776,0.5941333333333334 +FiftyWords,0.5056353591160222,0.3794475138121547,0.4439779005524862 +Fish,0.564,0.41657142857142854,0.42942857142857144 +FordA,0.566429587482219,0.5039626092257671,0.6819345661450924 +FordB,0.5529014844804319,0.5110436347278452,0.5793297345928925 +FreezerRegularTrain,0.7625000000000001,0.7686666666666666,0.7634666666666667 +FreezerSmallTrain,0.7622654621264768,0.7692842251563585,0.7637248088950661 +GunPoint,0.5029999999999999,0.5,0.5 +GunPointAgeSpan,0.6270509977827051,0.753880266075388,0.5995565410199557 +GunPointMaleVersusFemale,0.8541019955654102,0.5210643015521066,0.9026607538802661 +GunPointOldVersusYoung,0.5944567627494457,0.7117516629711752,0.5944567627494457 +Ham,0.6098130841121495,0.6182242990654205,0.6098130841121495 +HandOutlines,0.6481751824817519,0.7635036496350365,0.8024817518248174 +Haptics,0.3786177105831533,0.3434125269978402,0.33844492440604756 +Herring,0.571875,0.5546875,0.553125 +HouseTwenty,0.7226415094339622,0.6484276729559748,0.6226415094339622 +InlineSkate,0.23276923076923078,0.21415384615384614,0.24753846153846154 +InsectEPGRegularTrain,0.5794212218649517,0.5861736334405145,0.6225080385852091 +InsectEPGSmallTrain,0.5248120300751881,0.5436090225563909,0.6375939849624059 +InsectWingbeatSound,0.48090909090909084,0.510909090909091,0.403 +ItalyPowerDemand,0.6308394160583941,0.5145985401459854,0.6746350364963504 +LargeKitchenAppliances,0.4705333333333333,0.4181333333333333,0.5704 +Lightning2,0.6495867768595042,0.6256198347107438,0.6355371900826446 +Lightning7,0.5125874125874126,0.45874125874125876,0.5741258741258741 +Mallat,0.7645416666666667,0.6989166666666666,0.8024166666666666 +Meat,0.6841666666666668,0.7325,0.7 +MedicalImages,0.3238387379491674,0.29614373356704643,0.3016652059596845 +MiddlePhalanxOutlineAgeGroup,0.6411552346570397,0.646389891696751,0.6559566787003611 +MiddlePhalanxOutlineCorrect,0.5140291806958472,0.5140291806958474,0.5124579124579125 +MiddlePhalanxTW,0.467992766726944,0.4887884267631103,0.4674502712477396 +MixedShapesRegularTrain,0.637846153846154,0.6493675213675213,0.56191452991453 +MixedShapesSmallTrain,0.6270099009900989,0.656039603960396,0.6256237623762376 +MoteStrain,0.8426100628930818,0.8121069182389938,0.8869496855345913 +NonInvasiveFetalECGThorax1,0.5761221779548473,0.5503320053120849,0.5122177954847278 +NonInvasiveFetalECGThorax2,0.6071713147410358,0.5922709163346613,0.5641699867197876 +OSULeaf,0.3945701357466064,0.3744343891402715,0.46561085972850674 +OliveOil,0.7933333333333333,0.7733333333333333,0.7850000000000001 +PhalangesOutlinesCorrect,0.5440180586907449,0.5522949586155004,0.5525959367945823 +Phoneme,0.189478672985782,0.10398104265402844,0.1324644549763033 +PigAirwayPressure,0.21378205128205127,0.21891025641025644,0.2516025641025641 +PigArtPressure,0.41282051282051285,0.2987179487179487,0.45769230769230773 +PigCVP,0.3266025641025641,0.21730769230769234,0.4125 +Plane,0.8028571428571428,0.6880952380952381,0.8209523809523809 +PowerCons,0.7513888888888889,0.5816666666666668,0.6947222222222222 +ProximalPhalanxOutlineAgeGroup,0.7434710743801652,0.651404958677686,0.6618181818181819 +ProximalPhalanxOutlineCorrect,0.6294051627384961,0.6323232323232324,0.632996632996633 +ProximalPhalanxTW,0.5406611570247934,0.4940495867768595,0.503801652892562 +RefrigerationDevices,0.4915999999999999,0.36506666666666665,0.386 +Rock,0.4957142857142857,0.5299999999999999,0.5157142857142857 +ScreenType,0.40800000000000003,0.4021333333333333,0.3853333333333333 +SemgHandGenderCh2,0.573,0.661,0.6541111111111111 +SemgHandMovementCh2,0.3313333333333333,0.3755555555555556,0.40044444444444444 +SemgHandSubjectCh2,0.4775555555555556,0.48288888888888887,0.4651111111111111 +ShapeletSim,0.5455,0.5344999999999999,0.808 +ShapesAll,0.5081666666666667,0.4923333333333334,0.5460833333333334 +SmallKitchenAppliances,0.47973333333333334,0.37733333333333335,0.4182666666666667 +SmoothSubspace,0.6213333333333334,0.6419999999999999,0.5026666666666667 +SonyAIBORobotSurface1,0.6698872785829307,0.7212560386473431,0.7735909822866345 +SonyAIBORobotSurface2,0.773061224489796,0.7840816326530611,0.683061224489796 +StarLightCurves,0.7596903421394543,0.7616717193590299,0.7574058033780857 +Strawberry,0.5571719226856561,0.5483214649033571,0.5484231943031537 +SwedishLeaf,0.5005333333333333,0.3854222222222222,0.4512888888888889 +Symbols,0.7555882352941177,0.6804901960784314,0.7414705882352941 +SyntheticControl,0.7335,0.6551666666666666,0.6445 +ToeSegmentation1,0.5992537313432836,0.5156716417910449,0.5298507462686567 +ToeSegmentation2,0.6602409638554217,0.5307228915662652,0.7572289156626505 +Trace,0.5349999999999999,0.5145000000000001,0.6255 +TwoLeadECG,0.6302925989672978,0.5352839931153184,0.6490533562822719 +TwoPatterns,0.39776,0.31592000000000003,0.50174 +UMD,0.5272222222222221,0.5038888888888889,0.5094444444444444 +UWaveGestureLibraryAll,0.5491960696739616,0.7026574363555159,0.7404644930772666 +UWaveGestureLibraryX,0.5110763733809736,0.5453550692273336,0.5342563644484145 +UWaveGestureLibraryY,0.470567217507816,0.5002679767753462,0.42965609647163916 +UWaveGestureLibraryZ,0.4564984368021438,0.4930549352389459,0.485238945958017 +Wafer,0.6236460078168621,0.6330262423227248,0.6378699050809603 +Wine,0.5225225225225225,0.5243243243243243,0.5225225225225225 +WordSynonyms,0.3407734806629834,0.272596685082873,0.336353591160221 +Worms,0.3922480620155039,0.28488372093023256,0.313953488372093 +WormsTwoClass,0.5391472868217055,0.5236434108527133,0.5255813953488373 +Yoga,0.5125757575757575,0.5093636363636364,0.5056666666666667 diff --git a/tsml_eval/publications/clustering/kasba/results/combined/k-shape-compare/nmi_mean.csv b/tsml_eval/publications/clustering/kasba/results/combined/k-shape-compare/nmi_mean.csv new file mode 100644 index 00000000..c03f3dd3 --- /dev/null +++ b/tsml_eval/publications/clustering/kasba/results/combined/k-shape-compare/nmi_mean.csv @@ -0,0 +1,113 @@ +Estimators:,KASBA,k-AVG,k-Shape +ACSF1,0.47592949136897394,0.4361655103912792,0.40625627589930086 +Adiac,0.6041598759845417,0.5901206710729956,0.5866858687515825 +ArrowHead,0.24115115328459097,0.25963338466888997,0.2632377037145063 +BME,0.21334816422556382,0.20378183557653284,0.28582009351002025 +Beef,0.27617903399836874,0.3030660504316916,0.27763813712698593 +BeetleFly,0.11152800907051452,0.04158359062555757,0.051245110997851305 +BirdChicken,0.025691390530736817,0.06888904542297626,0.07362299438494904 +CBF,0.49785838162957485,0.3502032257629939,0.7192099892838251 +Car,0.3574217197980393,0.23338274247601426,0.21738157839722178 +Chinatown,0.14404729809224648,0.09348731202809131,0.017802554087985346 +ChlorineConcentration,0.0027650550357702524,0.001321269719300009,0.0007669774508616701 +CinCECGTorso,0.16136066484815065,0.24666708882459204,0.06806408167075972 +Coffee,0.3739538123477144,0.446545986022583,0.4543534372321932 +Computers,0.04045091309865465,0.000986093245943491,0.0461665648810657 +CricketX,0.2779334121847883,0.24416798027708322,0.3702811252906651 +CricketY,0.3462337615301026,0.2833119325663237,0.36695406885174736 +CricketZ,0.26989944853161973,0.25482978225028524,0.3617361716598003 +Crop,0.45233006641852197,0.4641094153837592,0.43895070377227663 +DiatomSizeReduction,0.7099731991102184,0.874784539194262,0.8047118127582914 +DistalPhalanxOutlineAgeGroup,0.38680586784500526,0.3071111506607057,0.3207450925359794 +DistalPhalanxOutlineCorrect,0.00040996112917425774,2.1065407555223235e-05,0.00376719332254643 +DistalPhalanxTW,0.5155772748388479,0.49379220374040694,0.5171952727979314 +ECG200,0.11819063847150695,0.09358895068553619,0.13736900936774968 +ECG5000,0.5125139456551618,0.5016091441475763,0.5078508544488279 +ECGFiveDays,0.11204967752825254,0.0008532763127686362,0.7226805017388442 +EOGHorizontalSignal,0.35167885663450527,0.37338528259338993,0.40171655345953744 +EOGVerticalSignal,0.2726457635667151,0.31689238691102944,0.3712364481588686 +Earthquakes,0.048528759187135805,0.0024973598327275234,0.005185504395283338 +ElectricDevices,0.30583820897071634,0.1840296967512828,0.17706564433679284 +EthanolLevel,0.007609722925004543,0.007903797774510614,0.00764509787328522 +FaceAll,0.7790172773056068,0.3628363620153383,0.6122465536129462 +FaceFour,0.7725538834881223,0.4433497537587069,0.46638490071959593 +FacesUCR,0.7679641878478174,0.35876368840663775,0.6119521488369093 +FiftyWords,0.7142432389212884,0.6269829546669609,0.6687635780367694 +Fish,0.5064721478566911,0.2973442484527433,0.31676356374132475 +FordA,0.036079925813793684,9.738925990619318e-05,0.0981679489915837 +FordB,0.01652704278972538,0.00037686666919006155,0.02022155258753979 +FreezerRegularTrain,0.21193440839563063,0.2205850498703969,0.21148438211638565 +FreezerSmallTrain,0.2123238152394335,0.22168874245249973,0.2119143251306889 +GunPoint,7.217223644468455e-05,0.0,0.0 +GunPointAgeSpan,0.06402103730129058,0.294979693583295,0.035019284069550474 +GunPointMaleVersusFemale,0.5285109633337521,0.0003488046534582718,0.6250637075749884 +GunPointOldVersusYoung,0.053985331394674464,0.2281974485281376,0.025465667314069785 +Ham,0.05502828286758432,0.04178617356069679,0.0363539972970638 +HandOutlines,0.06214458692237172,0.2111067309641607,0.25100116844293024 +Haptics,0.12207041100393312,0.08768912490610177,0.09506136988010154 +Herring,0.019488771495729067,0.00753492270190278,0.008206569762925872 +HouseTwenty,0.18301279057554193,0.07760173204232747,0.0481527820788388 +InlineSkate,0.08085379699690207,0.042186012905917794,0.10828327592176953 +InsectEPGRegularTrain,0.2209956229902747,0.2179712696375143,0.3457445346028755 +InsectEPGSmallTrain,0.19295730078171475,0.1792457497091786,0.34251357932762816 +InsectWingbeatSound,0.5330539603506181,0.5221442221131903,0.43578164717386897 +ItalyPowerDemand,0.1485517424586546,0.0013162067254957402,0.19731697842902757 +LargeKitchenAppliances,0.10322278130790204,0.03072723778996265,0.1595130417157778 +Lightning2,0.07370774875629288,0.039482635369215514,0.10513170237318319 +Lightning7,0.5223702268505059,0.407493831361737,0.5319958087410709 +Mallat,0.8785615895345854,0.8604411287586015,0.9086114673771247 +Meat,0.5681307001427354,0.5893339784496552,0.562226889906629 +MedicalImages,0.24098799275905022,0.24328565800769217,0.2200533590330168 +MiddlePhalanxOutlineAgeGroup,0.3962179471203771,0.39443172203723553,0.3958252390905438 +MiddlePhalanxOutlineCorrect,0.0006817138111835009,0.000745944387318363,0.0009683868651363881 +MiddlePhalanxTW,0.4187523417144118,0.42089744074690544,0.41871562152729414 +MixedShapesRegularTrain,0.4918236871485484,0.5049251445102737,0.4616167928137041 +MixedShapesSmallTrain,0.48880762259082244,0.5108784668200992,0.5140386953039401 +MoteStrain,0.4187980573041171,0.3010550773802839,0.4926485894829459 +NonInvasiveFetalECGThorax1,0.7525106538957,0.7196825986525679,0.7143506097206833 +NonInvasiveFetalECGThorax2,0.792837288134082,0.7732010792814428,0.7757544236441282 +OSULeaf,0.25760033058775894,0.21367165983770472,0.36794604769542033 +OliveOil,0.6509021506502937,0.6316053696758294,0.6190549417288131 +PhalangesOutlinesCorrect,0.007731736928882999,0.01012353388661226,0.01020196792366308 +Phoneme,0.30004816682502555,0.16184392971892753,0.21523395016679325 +PigAirwayPressure,0.5500118990809598,0.5548476187670711,0.579816756256972 +PigArtPressure,0.6948309826812087,0.617169673841122,0.7406959446060399 +PigCVP,0.6232854733038912,0.525592795621765,0.6937598332425229 +Plane,0.9138816764867164,0.8186773216540588,0.8836874031269568 +PowerCons,0.23407407827113205,0.036046465131834106,0.15548838417964148 +ProximalPhalanxOutlineAgeGroup,0.5260174283524702,0.46102100486467246,0.46503670548909887 +ProximalPhalanxOutlineCorrect,0.08254869946234773,0.0872818538902111,0.08964282534223286 +ProximalPhalanxTW,0.5420305567962673,0.49634491321417135,0.5080198892773102 +RefrigerationDevices,0.10731428012034042,0.003638842663564746,0.011385404817481308 +Rock,0.28005361521555466,0.35319043631687463,0.31368099620947215 +ScreenType,0.02200681222649935,0.01969248559796033,0.011671425907492154 +SemgHandGenderCh2,0.018764314015998547,0.07985456860312576,0.05850850892652835 +SemgHandMovementCh2,0.15027681035842932,0.21410230477930514,0.2385342603936334 +SemgHandSubjectCh2,0.2921808175795326,0.28816545127279697,0.28509987442591644 +ShapeletSim,0.010627375202259134,0.005109509258003898,0.4293241672455409 +ShapesAll,0.7365350133100294,0.7026422157574476,0.744128581349816 +SmallKitchenAppliances,0.13231108817341522,0.01641041382071091,0.038892065313958085 +SmoothSubspace,0.3160038973922463,0.35520275138310237,0.12120465026210851 +SonyAIBORobotSurface1,0.18775073644480972,0.3103024541993716,0.372959357359682 +SonyAIBORobotSurface2,0.21569143552381326,0.2393266410101881,0.10295172120984004 +StarLightCurves,0.6034588195688205,0.6021122288682111,0.6181730223742706 +Strawberry,0.09366679266456693,0.12339650719566002,0.12224948868452071 +SwedishLeaf,0.6505830132026489,0.5435206098628982,0.5765287253885635 +Symbols,0.8433881113609042,0.7778878636498049,0.8077628367083916 +SyntheticControl,0.8108064579364853,0.7673491874879245,0.6954596419036843 +ToeSegmentation1,0.06923792662759862,0.0007181133046158087,0.0027853414407533763 +ToeSegmentation2,0.0813792386206205,0.008599346180344062,0.2197266214139256 +Trace,0.5479489342883758,0.5097471813757704,0.6997307264826361 +TwoLeadECG,0.06362821704680574,0.0036056758691772966,0.0682184437985301 +TwoPatterns,0.10213367391039015,0.020243067129321005,0.3380497674270951 +UMD,0.24610279526304107,0.21155635096228403,0.20063483072210309 +UWaveGestureLibraryAll,0.4840773752335619,0.6712460725186873,0.6732434004350127 +UWaveGestureLibraryX,0.40198717138321244,0.4417514739176741,0.4616901539111142 +UWaveGestureLibraryY,0.40983813665772334,0.43407654755140274,0.34809574248718417 +UWaveGestureLibraryZ,0.39204237953403426,0.41585363969768563,0.46380811724119686 +Wafer,0.0005846431900208099,0.0001263179123237744,0.014090762437043916 +Wine,0.006327719580076526,0.005814946268162363,0.0010564787158772687 +WordSynonyms,0.46513020926276577,0.41709183188758675,0.46811605997405925 +Worms,0.13162905501777722,0.04650557046044568,0.07028624630794675 +WormsTwoClass,0.014913638066944328,0.0026293483602155467,0.003590527618541195 +Yoga,0.0010522396915234502,0.000804938208969304,0.00019968446406699132 diff --git a/tsml_eval/publications/clustering/kasba/results/combined/k-shape-compare/ri_mean.csv b/tsml_eval/publications/clustering/kasba/results/combined/k-shape-compare/ri_mean.csv new file mode 100644 index 00000000..83f7ca51 --- /dev/null +++ b/tsml_eval/publications/clustering/kasba/results/combined/k-shape-compare/ri_mean.csv @@ -0,0 +1,113 @@ +Estimators:,KASBA,k-AVG,k-Shape +ACSF1,0.7948643216080403,0.7246683417085428,0.7302211055276382 +Adiac,0.9505617387307529,0.9530621491184871,0.9495278899504251 +ArrowHead,0.628490182802979,0.6100925299029566,0.619359061160009 +BME,0.6171818746120422,0.5978212290502792,0.6163314711359404 +Beef,0.6789830508474577,0.6845762711864407,0.6989265536723164 +BeetleFly,0.5520512820512821,0.5155128205128205,0.5203846153846154 +BirdChicken,0.4947435897435898,0.5335897435897435,0.5325641025641026 +CBF,0.7335629709364908,0.7014884776091763,0.8524214961167635 +Car,0.6772549019607843,0.6638235294117648,0.6599019607843137 +Chinatown,0.61765520600277,0.568445885271601,0.5282285435977048 +ChlorineConcentration,0.5284896933248253,0.5269623295489655,0.52620942090728 +CinCECGTorso,0.6440960208041766,0.6812347517096944,0.6198798995523528 +Coffee,0.7013636363636364,0.7430519480519481,0.7430519480519481 +Computers,0.5156416833667334,0.49965931863727453,0.5274476953907816 +CricketX,0.8553885652216847,0.8552450544748362,0.8713765182186235 +CricketY,0.8612711892301108,0.8532556532043054,0.8731062177018531 +CricketZ,0.8511938382541719,0.8588535597906587,0.8713380073071987 +Crop,0.9282684188230064,0.9336246135255635,0.932953640776699 +DiatomSizeReduction,0.8599698148255644,0.9428629476983804,0.9033397186586948 +DistalPhalanxOutlineAgeGroup,0.7221199936547785,0.6692546433916589,0.7066059272644509 +DistalPhalanxOutlineCorrect,0.49954859752120023,0.49943587736464445,0.5054327462491847 +DistalPhalanxTW,0.7950134835955336,0.8241263250822465,0.8118910828948003 +ECG200,0.6060653266331659,0.5980150753768845,0.6165527638190954 +ECG5000,0.7661279055811161,0.7559784276855371,0.7646975555111022 +ECGFiveDays,0.5696660910204312,0.5000256222360012,0.8834605904388064 +EOGHorizontalSignal,0.853094839641457,0.8662184880371075,0.8720807256443763 +EOGVerticalSignal,0.8533340210754758,0.8543492048936674,0.871627197909264 +Earthquakes,0.504708101480713,0.5006036027539376,0.5536451947562011 +ElectricDevices,0.7260327826907709,0.7271927934103083,0.7290521841549273 +EthanolLevel,0.6050877248731893,0.6229568267309624,0.6226801666713009 +FaceAll,0.9385772244454325,0.880769527197273,0.9133732523096685 +FaceFour,0.8764157014157015,0.7426158301158302,0.7592181467181467 +FacesUCR,0.936693048762413,0.8808317770861123,0.914271113087298 +FiftyWords,0.9595433432748252,0.9520842908130837,0.9564088397790055 +Fish,0.818408514121981,0.7709079001227997,0.7798493655341793 +FordA,0.5111681477920245,0.4999605969439089,0.5662181326751289 +FordB,0.5083652600105149,0.5001614980313696,0.5139013190152851 +FreezerRegularTrain,0.637755807491386,0.6442449705457375,0.6387089918861844 +FreezerSmallTrain,0.6376157215345013,0.6449046051415904,0.6389763485678633 +GunPoint,0.497537688442211,0.4974874371859296,0.4974874371859296 +GunPointAgeSpan,0.5327459965508745,0.6280857354028085,0.5209953190440995 +GunPointMaleVersusFemale,0.7601773835920177,0.49977827050997786,0.8248317319536833 +GunPointOldVersusYoung,0.5207055925104707,0.5887657058388766,0.5169509731460951 +Ham,0.5268878065903206,0.5260365933921285,0.5231494888333115 +HandOutlines,0.5507484284442266,0.6426648467366557,0.682767857618913 +Haptics,0.6728039419184129,0.6729095958037643,0.680440006357933 +Herring,0.5109251968503936,0.5022145669291338,0.5019438976377952 +HouseTwenty,0.6086139638563809,0.5433006926200143,0.5327760528620332 +InlineSkate,0.731565248311011,0.7361213701552684,0.7453189522342065 +InsectEPGRegularTrain,0.6270283165646717,0.632745565812675,0.6909926356187117 +InsectEPGSmallTrain,0.6045112781954888,0.6115448999858136,0.6875386579656689 +InsectWingbeatSound,0.8833184505353673,0.8864374715779901,0.8661168299640332 +ItalyPowerDemand,0.5842615738426157,0.4999700029997,0.6136859647368597 +LargeKitchenAppliances,0.5174878504672897,0.5297007565643079,0.6232494882064975 +Lightning2,0.5515702479338843,0.5313498622589532,0.5329752066115702 +Lightning7,0.8166354771988574,0.7888407367280607,0.826268098099084 +Mallat,0.9413501458941227,0.9181163679310824,0.9508673058218703 +Meat,0.7551680672268909,0.7818067226890756,0.7615126050420168 +MedicalImages,0.6690768331872626,0.663517843688977,0.6742036071774529 +MiddlePhalanxOutlineAgeGroup,0.7139814990109741,0.7228912201904936,0.7331052806810244 +MiddlePhalanxOutlineCorrect,0.49986708533525015,0.4998322803566249,0.49975258199977296 +MiddlePhalanxTW,0.7899526954425139,0.7920656760227481,0.7921154702937862 +MixedShapesRegularTrain,0.809555976475265,0.8112584797783157,0.7871215873349937 +MixedShapesSmallTrain,0.8040084731135554,0.816245186800772,0.8125405218810313 +MoteStrain,0.7502182206849457,0.6946909529959573,0.7993225756968465 +NonInvasiveFetalECGThorax1,0.972951057971444,0.9715260107286052,0.9669559805411723 +NonInvasiveFetalECGThorax2,0.9742475369510268,0.9747608079901436,0.9728334412968035 +OSULeaf,0.7508531617775315,0.7464503750218036,0.7842449800432993 +OliveOil,0.85,0.821864406779661,0.8326553672316385 +PhalangesOutlinesCorrect,0.503737617712968,0.5052834017670715,0.5053466105830022 +Phoneme,0.9247921006564059,0.9159404852595173,0.9301409216649926 +PigAirwayPressure,0.9598111963063733,0.9620372660565586,0.9597472998598402 +PigArtPressure,0.9677632121362025,0.9663760408937258,0.970343804105862 +PigCVP,0.9632657267705497,0.9554662379421222,0.9711126226399538 +Plane,0.9455821371610845,0.8975985418090682,0.9415538847117795 +PowerCons,0.6359780253791396,0.5189384091612503,0.5893918291550604 +ProximalPhalanxOutlineAgeGroup,0.7800235345629687,0.7346762629303267,0.7437009468556729 +ProximalPhalanxOutlineCorrect,0.5329857879670613,0.5344985434873075,0.5348718142725633 +ProximalPhalanxTW,0.807550763505008,0.7732198566033606,0.7827486180285699 +RefrigerationDevices,0.5707549621717847,0.5558778816199378,0.556000712060525 +Rock,0.6642236024844721,0.6944927536231883,0.6896066252587991 +ScreenType,0.5534202047174009,0.5618912327547841,0.5583761459724077 +SemgHandGenderCh2,0.5127581263131875,0.5514509949326413,0.5470198986528241 +SemgHandMovementCh2,0.692924236806328,0.7285724879495736,0.7474987022617723 +SemgHandSubjectCh2,0.7201033246817452,0.7140180447410703,0.734058830799654 +ShapeletSim,0.503110552763819,0.5010301507537689,0.7121809045226131 +ShapesAll,0.9729093689185433,0.9761053655824299,0.9781316374756741 +SmallKitchenAppliances,0.5360893635959056,0.4617235425011126,0.5500069425901202 +SmoothSubspace,0.6835451505016723,0.7067224080267558,0.605768115942029 +SonyAIBORobotSurface1,0.590420237909719,0.6167804269908057,0.6826533686561735 +SonyAIBORobotSurface2,0.6487682141293698,0.6610593900481541,0.5788943319922454 +StarLightCurves,0.7689357010994617,0.7696935252301264,0.7732399407886514 +Strawberry,0.507279142572407,0.5041655184987973,0.5041854085647454 +SwedishLeaf,0.9047781731909845,0.885712613681297,0.9023762752075919 +Symbols,0.9106426908349208,0.8836733437241431,0.9044012776847736 +SyntheticControl,0.9023288814691153,0.871557039510295,0.8719048414023373 +ToeSegmentation1,0.5317178154172956,0.4986360333165633,0.5004248420817261 +ToeSegmentation2,0.5809419496166484,0.49905074844833885,0.6370427163198247 +Trace,0.7531658291457287,0.7503417085427134,0.8277537688442212 +TwoLeadECG,0.538403744175669,0.5020628842427666,0.5441899009845212 +TwoPatterns,0.6445551110222045,0.6304641968393679,0.6856180916183237 +UMD,0.6267659838609559,0.5976039726877717,0.6030043451272502 +UWaveGestureLibraryAll,0.8556040735422765,0.899738557540336,0.9116042363514856 +UWaveGestureLibraryX,0.8407344750395624,0.8547843511220018,0.8543966916211019 +UWaveGestureLibraryY,0.8355836385922869,0.8459524802616281,0.8312999008479945 +UWaveGestureLibraryZ,0.8246996135176735,0.8445181131729509,0.8486995365025329 +Wafer,0.5317267616878192,0.5353271000791725,0.5387074474549052 +Wine,0.4971662571662572,0.49670761670761676,0.4964782964782965 +WordSynonyms,0.8955779103310026,0.8942409426490002,0.9003943186818558 +Worms,0.6597532651645401,0.6453835248695442,0.6520465719542726 +WormsTwoClass,0.5038548547642747,0.49966217235242666,0.500129701686122 +Yoga,0.5002992458688124,0.5000464971019685,0.4999342500482239 diff --git a/tsml_eval/publications/clustering/kasba/results/combined/section-5.1/ami_mean.csv b/tsml_eval/publications/clustering/kasba/results/combined/section-5.1/ami_mean.csv new file mode 100644 index 00000000..f8364c69 --- /dev/null +++ b/tsml_eval/publications/clustering/kasba/results/combined/section-5.1/ami_mean.csv @@ -0,0 +1,94 @@ +Estimators:,DBA,Euclid,KASBA,MSM,k-SC,k-shape,shape-DBA +ACSF1,0.26359095614176675,0.3699933500579274,0.40363962394734615,0.3909884355319827,0.3132197225971678,0.3297886660540669,0.19005522296365887 +Adiac,0.47848956490345645,0.4774790037196139,0.4864262572449494,0.5097165021502486,0.485271643560185,0.39835548565,0.5338667077001981 +ArrowHead,0.23002748893846162,0.22548583863715754,0.22535919696548345,0.2037823888081891,0.2778337996523792,0.22262040487791632,0.20576206712201958 +BME,0.5780871393289885,0.16180599945902602,0.195081066302107,0.18454084141362653,0.00544767555620641,0.45574327428470723,0.19998400388556614 +Beef,0.20243064939044722,0.14839275918226572,0.2742026215230786,0.1648151336812848,0.2096211919021944,0.3035047941593613,0.16856782802697975 +BeetleFly,0.08166429338346506,-0.002459881830489101,0.10895262962296555,0.027481576343632807,-0.011736609070046101,-0.0021509415231554057,-0.011736609070046101 +BirdChicken,0.12013395464535473,0.0489963849927744,-0.0014756081228843043,-0.01762400637801239,-0.011500411767335902,0.20591312503644996,-0.0116464309346967 +CBF,0.7801353793054507,0.3491297761004368,0.512665681143807,0.3398832372441667,0.5938992993802166,0.7882040869012367,0.7907055223974996 +Car,0.13551391738083224,0.20929365838343597,0.4068774732561941,0.4352261342289531,0.18926317734978704,0.2232896388795944,0.09723467224563659 +Chinatown,0.04351221756379893,0.01667562351685354,0.014851790973966023,0.021736864654591986,0.014621199492563474,0.01152698948143243,0.014621199492563474 +ChlorineConcentration,0.006408074084790499,0.0011593684654230137,0.00256582646283792,0.0028485389161376734,0.002036631852227657,0.000883240480338031,-0.00011779933909927445 +Coffee,0.7461889807963462,0.6420825664763679,0.5096534008423445,0.5343696466537273,0.6910634229485068,0.41576236683683127,0.5822036366943331 +Computers,0.07249868795656945,-0.001292414241265844,0.05614811460678932,0.05383594209880441,0.03618836790477716,0.03031444487411846,0.05953562125337601 +CricketX,0.39376167299956355,0.25130409169245915,0.2717478939109911,0.1947039319921261,0.3068916944666727,0.396128048750739,0.42802465082764074 +CricketY,0.4557013096651578,0.26976532861337654,0.34385672078916235,0.2928272263655762,0.32528674102840066,0.346518036637708,0.47699884543984045 +CricketZ,0.4243841572364048,0.23723546910554583,0.2539342524490182,0.17502507096855974,0.10664958876444798,0.3678755870047825,0.4438838853582865 +Crop,0.41295450662829397,0.46834202529139657,0.4524456430980634,0.45786172174222173,0.0,0.39246660078611023,0.4358466949855746 +DiatomSizeReduction,0.36268564967359984,0.8374077194388141,0.7104613904424311,0.7018709633703276,0.942684151638642,0.5295632386105266,0.5184234703422331 +DistalPhalanxOutlineAgeGroup,0.33110795298456475,0.3259858494992793,0.36196712845941986,0.4195524232073901,0.32491302190098126,0.3140669614876906,0.3028004929125451 +DistalPhalanxOutlineCorrect,0.0035017604109216006,-0.0008333163596907423,0.0004432644066315546,-8.900587613733577e-05,-0.0007843773335295956,-0.0008292759814985144,-0.00045503773369478384 +DistalPhalanxTW,0.5032548787294004,0.4884075577893999,0.5103833648826065,0.5255345604759833,0.4834492041538721,0.5413490527634464,0.5710448810906839 +ECG200,0.07045733469695684,0.12523259357059555,0.06677682926191847,0.12523259357059555,0.13002001073611927,0.11025375911232364,0.12207046290266439 +ECG5000,0.4509664421665351,0.5073833404434576,0.5855287243516815,0.5495530709064234,0.4903750073167328,0.5112343046227142,0.5158266151400686 +ECGFiveDays,0.013610278037824764,0.0002503066603904021,0.012606023830505079,0.06447005205985479,0.7466158103783839,0.7466158103783839,0.0380048656187067 +EOGVerticalSignal,0.3423219183643837,0.30524210040898225,0.2330918136445073,0.24792050160245746,0.2696914440965469,0.3413595367386589,0.3639123095372669 +Earthquakes,0.03264224750281197,-0.0013695152418613534,0.0447729996608642,0.06427856356441837,0.0,0.001863689778216577,0.004783742191281787 +ElectricDevices,0.35199116811752074,0.1920481076544265,0.29971456833788535,0.1250268383227671,0.0,0.2578487919040799,0.3348067978698925 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+MixedShapesSmallTrain,0.42902945622386884,0.4260852972793287,0.5596799917263238,0.5817686117590901 +MoteStrain,0.008740885208063607,0.0026594652156438094,0.001186999150582405,0.4679076223837065 +NonInvasiveFetalECGThorax1,0.6794236345859058,0.7185317546497204,0.7215411767965537,0.7207827017013589 +NonInvasiveFetalECGThorax2,0.726934060050075,0.7810958325060263,0.7696411168639377,0.787988971723044 +OSULeaf,0.21141393869714947,0.2961220909973847,0.33564906922231785,0.286956783538515 +OliveOil,0.36349173880718527,0.4142923676524595,0.3768658249005062,0.6598015943392109 +PhalangesOutlinesCorrect,0.02274948000612115,0.02833163926607458,0.030065870529786796,0.03484989041438794 +Phoneme,0.20121155385405046,0.22648858571495448,0.2084090879788366,0.20983108541020945 +PigAirwayPressure,0.045998692403945614,0.052364726308432565,0.05859782891741441,0.05249732204191972 +PigArtPressure,0.18187182249437192,0.2694906555222167,0.27768776975815557,0.3303864858270918 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+SemgHandMovementCh2,0.1437349868556152,0.1610826413001978,0.1221610351739497,0.15689881795073965 +SemgHandSubjectCh2,0.23663110448375088,0.251326203007963,0.2514092036158359,0.1728169329485816 +ShapeletSim,-0.006847016496397698,-0.0017974949785548873,-0.0037327121241439477,0.06071943985924569 +ShapesAll,0.5483888583159796,0.5644528516352961,0.5716691410691309,0.6171021445987899 +SmallKitchenAppliances,0.29782970883807924,0.14559328948083552,0.1546483347489675,0.2117138985013054 +SmoothSubspace,0.24961455791359946,0.3549976267389449,0.2897207242322907,0.38944164461789504 +SonyAIBORobotSurface1,0.12671108483678797,0.08176184338895578,0.029452219374533604,0.053654308309866325 +SonyAIBORobotSurface2,0.1469147208823898,0.20988475160889933,0.21203303225576553,0.20988475160889933 +StarLightCurves,0.6462257019623272,0.603364269402947,0.6016862094128927,0.6016208087013803 +Strawberry,0.12033360221720896,0.11430314796056715,0.10378078371161602,0.11470523948590162 +SwedishLeaf,0.5252541887913257,0.6241219548057649,0.6740409830003531,0.6172147617358691 +Symbols,0.872990878929087,0.842176844517027,0.8613248128676735,0.8817928264739339 +SyntheticControl,0.8819311116354541,0.8114598997642195,0.8007358974892856,0.7884158344276807 +ToeSegmentation1,0.0077787652503635745,0.02507762714250741,0.007947379556721609,-0.003214680963620936 +ToeSegmentation2,-0.002712625446356019,0.2589530458614786,-0.0017542907898334033,0.0002533112937734584 +Trace,0.7632692390057285,0.5037188058161782,0.4882962643881863,0.49059048036639685 +TwoLeadECG,0.008656436372430751,0.12447591360609542,0.10984998044168502,0.18736922593848965 +TwoPatterns,0.844561898891886,0.05882229215486425,0.011922939088940303,0.1937523305848987 +UMD,0.24482177092289034,0.18927844040271863,0.1731216237360475,0.16557319018962902 +UWaveGestureLibraryAll,0.49292669009902035,0.6361026623356322,0.6703842423842375,0.6129032633200323 +UWaveGestureLibraryX,0.47923848002793756,0.45648186635509747,0.463744974182872,0.4567612680831283 +UWaveGestureLibraryY,0.4071843938454069,0.3996474534569895,0.4434936715143124,0.4233708509637164 +UWaveGestureLibraryZ,0.45430972906771366,0.4592475424307365,0.44646148889344595,0.45511110908276226 +Wafer,-0.00016516099057367888,7.14556170907269e-05,-0.00013494953855287985,-0.00016305893390051082 +Wine,0.0,0.0,0.0,-0.014753918064186314 +WordSynonyms,0.42660972003904274,0.37160682565838715,0.42554403230200555,0.45108922542119034 +Worms,0.1498851423850268,0.16623664792343942,0.11498543117203856,0.1679210757873799 +WormsTwoClass,0.000613547646535669,0.02922814260978894,-0.009400270113672752,0.007885286840213482 +Yoga,0.017519447531826656,0.0019259344656923226,0.0008271143284267976,-0.00015669564951874276 diff --git a/tsml_eval/publications/clustering/kasba/results/train-test/section-5.2/ari_mean.csv b/tsml_eval/publications/clustering/kasba/results/train-test/section-5.2/ari_mean.csv new file mode 100644 index 00000000..f375b092 --- /dev/null +++ b/tsml_eval/publications/clustering/kasba/results/train-test/section-5.2/ari_mean.csv @@ -0,0 +1,112 @@ +Estimators:,DBA,KASBA,MBA,PAM-MSM +ACSF1,0.09260865375349331,0.2443644124316393,0.13793103448275862,0.21064814814814814 +Adiac,0.2561805294510227,0.23423593164242065,0.2589694597418574,0.2683519357174329 +ArrowHead,0.23921314163169208,0.2187386093526287,0.170827014353695,0.15154541828647095 +BME,0.5010491753373126,0.13566770875040274,0.1408912899621397,0.1530850897957448 +Beef,0.102055982164974,0.055541529916687704,0.07425854652479058,0.017059483726150394 +BeetleFly,0.0,0.1211453744493392,0.3303964757709251,0.4619655746807329 +BirdChicken,-0.04441976679622432,-0.004405286343612335,-0.04441976679622432,-0.011086474501108648 +CBF,0.5736853771159853,0.35688368418783095,0.3421693676937751,0.3037722670358111 +Car,0.09179728684894918,0.32594376284011206,0.2753983676642052,0.25480184576057113 +Chinatown,0.12164890586333783,0.06973426035734383,0.05352733744991758,0.13348069127733644 +ChlorineConcentration,0.0002051227671614247,0.004697199288738433,0.0048503113811092565,0.004516718958153018 +CinCECGTorso,0.03185302970418559,0.1341889063749661,0.09820973038009219,0.11264289373541855 +Coffee,0.7245901639344262,0.6029745399546257,0.6029745399546257,0.8569746909947028 +Computers,0.06255400310810369,0.0003244979745918086,0.07114200789383923,0.08044244893288499 +CricketX,0.2756758310616598,0.08370664677927571,0.09863835551339085,0.13226886770611695 +CricketY,0.2132904008066299,0.19114730596100596,0.16707286296201487,0.1831933027106445 +CricketZ,0.2599097110574411,0.0988621213093179,0.08929514594016397,0.11799084574931482 +DiatomSizeReduction,0.5573301543749086,0.49821153456368134,0.7218431277647909,0.5730971245891572 +DistalPhalanxOutlineAgeGroup,0.12204917860685537,0.14478091719061018,0.13880389539506188,0.13493690585733864 +DistalPhalanxOutlineCorrect,0.0227490294741602,0.04428023004963268,0.0409370738290982,0.041172975820825256 +DistalPhalanxTW,0.3823324300004276,0.5042578501426888,0.5083917564805468,0.3139809585067391 +ECG200,0.06514998692517464,0.23525119356431898,0.2144023756495917,0.2144023756495917 +ECG5000,0.4257853236359796,0.6985959819857679,0.7140095987480214,0.4916872619234566 +ECGFiveDays,0.0568225099610168,0.17886555788180827,0.028216549028073103,0.20324316137794524 +EOGHorizontalSignal,0.17890044578650915,0.13917334188530517,0.16751627547408424,0.16795011557847378 +EOGVerticalSignal,0.19100301858790386,0.11635278180486176,0.11052563768781962,0.140175059688854 +Earthquakes,-0.06883911151393915,-0.03890690001305775,-0.07360090871259432,-0.04814127200683452 +ElectricDevices,0.3164970177637447,0.1568937165186581,0.23240782494395978,0.21217643634414052 +EthanolLevel,-0.0018221815664526558,-0.0009704739225344128,-0.00029512883625414246,-0.0003495072477758018 +FaceAll,0.5198281325635,0.5002991512927215,0.5372637444469118,0.5701332469790424 +FaceFour,0.08939419816039232,0.4739971318356817,0.6812352629556149,0.5848924566385398 +FacesUCR,0.2941799980085854,0.6155932149697018,0.6328247393642797,0.7047512780283517 +FiftyWords,0.38952722405586915,0.40723162578574995,0.4778377019239514,0.45444429781393836 +Fish,0.3153436489867669,0.2330668502279762,0.3841330269075089,0.43872927124856953 +FordA,-0.0004818064980644929,0.011398718535390257,0.06169969137458979,0.005692653340985779 +FordB,0.01060098062084156,-6.697901364215425e-06,0.015496805192167196,0.0012317148427486025 +FreezerRegularTrain,0.2730721241646444,0.27823454849449264,0.2767561627406338,0.2826976006965658 +FreezerSmallTrain,0.2752797531449849,0.26723530388247846,0.2760175100010252,0.27087766167984817 +GunPoint,-0.005997289919124703,-0.005115359852913385,-0.00019537231838481542,-0.005115359852913385 +GunPointAgeSpan,0.06473520077995035,0.06798475021503127,0.06800776999196559,0.08219634620273854 +GunPointMaleVersusFemale,0.537579859981811,0.5659054585723198,0.5563831611541222,0.5659054585723198 +GunPointOldVersusYoung,0.013873221168440515,0.0021622428390057125,0.021152103321712093,0.023197161634378294 +Ham,0.04818301919886458,0.04908887763550283,0.06834730829796029,-0.0006510887651016422 +HandOutlines,0.02777263238668033,-0.002107960440724597,0.004223000756603835,0.011982466849751999 +Haptics,0.0385353915657001,0.0716090752526205,0.06585134805059838,0.09930411564240472 +Herring,0.032566710372444095,0.06328565065374807,-0.006647224813157491,0.06165819680869967 +HouseTwenty,0.21896680399888854,0.4111555587070966,0.37047192774284093,0.3689463518621462 +InlineSkate,0.026509912688302138,0.021222707566240603,0.02505810840162477,0.02209513514022032 +InsectEPGRegularTrain,0.293067118403188,0.31136809896459505,0.19775469317758945,0.1643902488071624 +InsectEPGSmallTrain,0.21611397452361664,0.29628137093985507,0.2683881687728029,0.27208924800675766 +InsectWingbeatSound,0.028489769981556976,0.3655593295847043,0.3620795062678999,0.3053132834288466 +ItalyPowerDemand,0.0034667825389679825,0.5125261454164635,0.0008314302213935166,0.0008742347615274845 +LargeKitchenAppliances,0.13858031367203602,0.015844920674138188,0.08828000990698881,0.07215412803158922 +Lightning2,0.04539366723247602,0.0821152192605331,0.046008603351155586,-0.016426221753993678 +Lightning7,0.2773367276763631,0.24828144079082942,0.2915343469259665,0.3077887330588148 +Mallat,0.862634958002986,0.8221034353032259,0.7930173453153451,0.7232689328956805 +Meat,0.48857368006304175,0.29711971391025227,0.2742411512527198,0.32306075618177527 +MedicalImages,0.0649548210573436,0.04036209302246069,0.07412375218452058,0.04735115922869442 +MiddlePhalanxOutlineAgeGroup,0.08065686388635962,0.07962382111832941,0.05834251180235105,0.04642170355222335 +MiddlePhalanxOutlineCorrect,0.015124599151389211,0.03592334416406122,0.02951479046342067,0.02060084124050057 +MiddlePhalanxTW,0.2597626798340104,0.2712602319459799,0.25157513919652713,0.2756747936441474 +MixedShapesRegularTrain,0.47219159065893124,0.40455026438171876,0.5320025718838169,0.5318287651913991 +MixedShapesSmallTrain,0.39479167492090383,0.3818150286000059,0.5362484118200171,0.5459136471422706 +MoteStrain,0.014366728826095519,0.006733939700696405,0.004441482823575846,0.558457594688777 +NonInvasiveFetalECGThorax1,0.4082339626806552,0.468893114707966,0.46152856299374434,0.4881962270645694 +NonInvasiveFetalECGThorax2,0.45092257355641513,0.5725996303844039,0.5481813279067438,0.5643467123557322 +OSULeaf,0.13278319673977934,0.19525862492559823,0.25259900091781584,0.2001107465423282 +OliveOil,0.2672987584558124,0.31230976144970624,0.297674539725528,0.7114575095032784 +PhalangesOutlinesCorrect,0.050126187207643454,0.057161335752853905,0.05964871388802398,0.06616574931974797 +Phoneme,0.06079826443837749,0.08746038969700026,0.07601194334126996,0.06955610475348523 +PigAirwayPressure,0.022060506201656827,0.02627122522769921,0.030218612776807215,0.028200882097358628 +PigArtPressure,0.0954950535524487,0.1823458282950423,0.16935922138234277,0.20441833578102053 +PigCVP,0.013657212200991382,0.06476262923135438,0.07966296438146304,0.06104386762750997 +Plane,0.8707894491197301,0.7713697145009271,0.7713697145009271,0.9774191369368053 +PowerCons,0.02827806906326647,0.2573335071317438,0.2688538184672326,0.22396242602380692 +ProximalPhalanxOutlineAgeGroup,0.439108889156308,0.44426195236547267,0.561271203011928,0.5906861821378842 +ProximalPhalanxOutlineCorrect,0.07389257747720981,0.08130537128937242,0.07755576974957634,0.08130537128937242 +ProximalPhalanxTW,0.3894374290154792,0.5501955095345865,0.5497529118585245,0.42870779929622266 +RefrigerationDevices,0.011713557069930138,0.07118369708963575,0.03413458762634421,0.07806680546833665 +Rock,0.09652835092278786,0.1608326088759596,0.1456697101769874,0.19418928078909847 +ScreenType,0.02038459475761865,0.02106872173323338,0.0127041370760048,0.019435999843058945 +SemgHandGenderCh2,0.11936156322480491,0.03140761594099455,0.013998457297595152,0.01683522376484202 +SemgHandMovementCh2,0.0947268285892083,0.09479070933928975,0.05915937081189489,0.07913515607980304 +SemgHandSubjectCh2,0.1893715471316471,0.1685322755558619,0.1578910961839384,0.07246987495809709 +ShapeletSim,-0.00024286430853702543,-0.002430091523738124,-0.004942942576432538,0.06664097865769988 +ShapesAll,0.29750227587071193,0.2940054307342984,0.2942461775329803,0.4229756024768369 +SmallKitchenAppliances,0.2701638278045716,0.11528388388957152,0.07988846828716221,0.21288789406409342 +SmoothSubspace,0.1928151865092144,0.3842875431460565,0.3262761236247082,0.38853587503309506 +SonyAIBORobotSurface1,-0.0016961448009491609,0.08060385920236315,0.011228113789382703,0.04162975651225063 +SonyAIBORobotSurface2,0.19598811995833543,0.290290577060023,0.2925949623458801,0.290290577060023 +StarLightCurves,0.5892610778871974,0.5219801296467216,0.5162912674701027,0.5119869555889641 +Strawberry,-0.047177236605349594,-0.021286697505857335,-0.04011645466373323,-0.028148598602485586 +SwedishLeaf,0.26871473757380965,0.3769291363758545,0.4549665147399498,0.4144898630266903 +Symbols,0.7713892693007667,0.7389038898076614,0.7600713794273926,0.842317054169458 +SyntheticControl,0.7638460909702383,0.7128764867819993,0.7150938562417344,0.6536066931496387 +ToeSegmentation1,0.01311175321807336,0.03650690083386775,0.013054318712691084,-0.0020719259143547235 +ToeSegmentation2,0.019515376976893106,0.4268765283427481,0.004635741258097197,-0.005242254905795084 +Trace,0.7080659637678516,0.36774146304202493,0.3285382196089156,0.3346845211085694 +TwoLeadECG,0.01196021538516443,0.13083058046685458,0.11479098665236659,0.19752850089194518 +TwoPatterns,0.8529012882789998,0.05424458367452428,0.0032352371995382147,0.1500797513685088 +UMD,0.1390561274033793,0.11896910794862894,0.10814856547198645,0.10299966369346272 +UWaveGestureLibraryAll,0.3976756970910999,0.5923933384877387,0.6344616604977332,0.5546580845714042 +UWaveGestureLibraryX,0.42759889605158913,0.3946852459526184,0.39700407112390607,0.40035116834671325 +UWaveGestureLibraryY,0.285573299878207,0.3151899048276799,0.3422308776482055,0.3164614396339158 +UWaveGestureLibraryZ,0.35108799882544944,0.371388123717569,0.34121423320961436,0.37057485473909835 +Wafer,0.0001144227004591358,0.0048481719752093465,0.0016923364912966757,0.0004300064709187287 +Wine,0.0,0.0,0.0,-0.011005135730007337 +WordSynonyms,0.3189979615618589,0.25083713173835637,0.2941374598064445,0.3218608088906553 +Worms,0.10685806805130317,0.1546744061840112,0.13247851050432527,0.12202827093852948 +WormsTwoClass,-0.01311428159677187,0.00639026950267033,-0.011625158034310148,-0.005627108879927578 +Yoga,0.02689699339414185,0.004844776256848145,0.0025386261430918925,-0.0005178792898613615 diff --git a/tsml_eval/publications/clustering/kasba/results/train-test/section-5.2/clacc_mean.csv b/tsml_eval/publications/clustering/kasba/results/train-test/section-5.2/clacc_mean.csv new file mode 100644 index 00000000..821dd8ba --- /dev/null +++ b/tsml_eval/publications/clustering/kasba/results/train-test/section-5.2/clacc_mean.csv @@ -0,0 +1,112 @@ +Estimators:,DBA,KASBA,MBA,PAM-MSM +ACSF1,0.29,0.41,0.38,0.45 +Adiac,0.40153452685422,0.3836317135549872,0.4092071611253197,0.42710997442455245 +ArrowHead,0.5714285714285714,0.6057142857142858,0.5314285714285715,0.5314285714285715 +BME,0.7066666666666667,0.5066666666666667,0.5066666666666667,0.6133333333333333 +Beef,0.4666666666666667,0.43333333333333335,0.43333333333333335,0.36666666666666664 +BeetleFly,0.55,0.7,0.8,0.85 +BirdChicken,0.55,0.6,0.55,0.6 +CBF,0.8411111111111111,0.7455555555555555,0.7388888888888889,0.7055555555555556 +Car,0.43333333333333335,0.6166666666666667,0.6,0.5666666666666667 +Chinatown,0.6938775510204082,0.6501457725947521,0.6326530612244898,0.7026239067055393 +ChlorineConcentration,0.3671875,0.39166666666666666,0.39609375,0.39348958333333334 +CinCECGTorso,0.3681159420289855,0.4528985507246377,0.4217391304347826,0.4326086956521739 +Coffee,0.9285714285714286,0.8928571428571429,0.8928571428571429,0.9642857142857143 +Computers,0.628,0.524,0.636,0.644 +CricketX,0.4564102564102564,0.27692307692307694,0.28717948717948716,0.3641025641025641 +CricketY,0.382051282051282,0.35128205128205126,0.3564102564102564,0.3717948717948718 +CricketZ,0.45897435897435895,0.3076923076923077,0.2923076923076923,0.3128205128205128 +DiatomSizeReduction,0.7418300653594772,0.6895424836601307,0.8758169934640523,0.7875816993464052 +DistalPhalanxOutlineAgeGroup,0.5971223021582733,0.5827338129496403,0.5899280575539568,0.5755395683453237 +DistalPhalanxOutlineCorrect,0.5869565217391305,0.6123188405797102,0.6086956521739131,0.6086956521739131 +DistalPhalanxTW,0.539568345323741,0.5683453237410072,0.5755395683453237,0.5107913669064749 +ECG200,0.65,0.75,0.74,0.74 +ECG5000,0.5544444444444444,0.7311111111111112,0.764,0.6022222222222222 +ECGFiveDays,0.6202090592334495,0.7119628339140535,0.5853658536585366,0.7259001161440186 +EOGHorizontalSignal,0.3342541436464088,0.30662983425414364,0.32044198895027626,0.3259668508287293 +EOGVerticalSignal,0.36464088397790057,0.30386740331491713,0.2955801104972376,0.31215469613259667 +Earthquakes,0.5323741007194245,0.5107913669064749,0.5539568345323741,0.5035971223021583 +ElectricDevices,0.47853715471404484,0.31682012709116847,0.42821942679289327,0.41719621320191935 +EthanolLevel,0.278,0.292,0.278,0.278 +FaceAll,0.5976331360946746,0.642603550295858,0.678698224852071,0.7355029585798817 +FaceFour,0.45454545454545453,0.7045454545454546,0.8409090909090909,0.7159090909090909 +FacesUCR,0.3985365853658537,0.6687804878048781,0.6921951219512195,0.7619512195121951 +FiftyWords,0.46813186813186813,0.5076923076923077,0.5736263736263736,0.5648351648351648 +Fish,0.5371428571428571,0.44571428571428573,0.5657142857142857,0.6628571428571428 +FordA,0.5083333333333333,0.5553030303030303,0.625,0.5401515151515152 +FordB,0.554320987654321,0.5148148148148148,0.562962962962963,0.5246913580246914 +FreezerRegularTrain,0.7614035087719299,0.763859649122807,0.7631578947368421,0.7659649122807017 +FreezerSmallTrain,0.7624561403508772,0.7585964912280702,0.7628070175438596,0.7603508771929824 +GunPoint,0.5133333333333333,0.52,0.54,0.52 +GunPointAgeSpan,0.629746835443038,0.6329113924050633,0.6329113924050633,0.6455696202531646 +GunPointMaleVersusFemale,0.8670886075949367,0.8765822784810127,0.8734177215189873,0.8765822784810127 +GunPointOldVersusYoung,0.5650793650793651,0.5365079365079365,0.5777777777777777,0.580952380952381 +Ham,0.6190476190476191,0.6190476190476191,0.638095238095238,0.5428571428571428 +HandOutlines,0.6567567567567567,0.5621621621621622,0.6432432432432432,0.5702702702702702 +Haptics,0.30844155844155846,0.36363636363636365,0.36688311688311687,0.38636363636363635 +Herring,0.609375,0.640625,0.546875,0.640625 +HouseTwenty,0.7394957983193278,0.8235294117647058,0.8067226890756303,0.8067226890756303 +InlineSkate,0.22,0.22363636363636363,0.2309090909090909,0.22363636363636363 +InsectEPGRegularTrain,0.6465863453815262,0.642570281124498,0.570281124497992,0.4939759036144578 +InsectEPGSmallTrain,0.5943775100401606,0.6104417670682731,0.5983935742971888,0.6024096385542169 +InsectWingbeatSound,0.1893939393939394,0.5272727272727272,0.5075757575757576,0.44595959595959594 +ItalyPowerDemand,0.531584062196307,0.858114674441205,0.5189504373177842,0.5189504373177842 +LargeKitchenAppliances,0.528,0.392,0.5386666666666666,0.5173333333333333 +Lightning2,0.6229508196721312,0.6557377049180327,0.6229508196721312,0.5081967213114754 +Lightning7,0.547945205479452,0.4794520547945205,0.5068493150684932,0.5205479452054794 +Mallat,0.9236673773987207,0.8550106609808102,0.8183368869936034,0.7897654584221748 +Meat,0.7,0.6833333333333333,0.6333333333333333,0.6833333333333333 +MedicalImages,0.3171052631578947,0.3078947368421053,0.3355263157894737,0.29736842105263156 +MiddlePhalanxOutlineAgeGroup,0.6103896103896104,0.5974025974025974,0.512987012987013,0.474025974025974 +MiddlePhalanxOutlineCorrect,0.5876288659793815,0.6116838487972509,0.6048109965635738,0.5945017182130584 +MiddlePhalanxTW,0.42207792207792205,0.461038961038961,0.43506493506493504,0.461038961038961 +MixedShapesRegularTrain,0.6325773195876289,0.5694845360824742,0.6602061855670103,0.650721649484536 +MixedShapesSmallTrain,0.6,0.5645360824742268,0.6593814432989691,0.6424742268041237 +MoteStrain,0.5654952076677316,0.5487220447284346,0.542332268370607,0.8738019169329073 +NonInvasiveFetalECGThorax1,0.49312977099236643,0.5384223918575064,0.5486005089058524,0.621882951653944 +NonInvasiveFetalECGThorax2,0.5318066157760815,0.6519083969465649,0.6325699745547074,0.6529262086513995 +OSULeaf,0.34710743801652894,0.3925619834710744,0.49173553719008267,0.45454545454545453 +OliveOil,0.5333333333333333,0.6,0.5666666666666667,0.8666666666666667 +PhalangesOutlinesCorrect,0.6188811188811189,0.6247086247086248,0.627039627039627,0.6328671328671329 +Phoneme,0.17457805907172996,0.1930379746835443,0.17141350210970463,0.18618143459915612 +PigAirwayPressure,0.25961538461538464,0.25961538461538464,0.27403846153846156,0.2644230769230769 +PigArtPressure,0.3173076923076923,0.4375,0.41346153846153844,0.4326923076923077 +PigCVP,0.2403846153846154,0.32211538461538464,0.33653846153846156,0.3173076923076923 +Plane,0.8761904761904762,0.8380952380952381,0.8380952380952381,0.9904761904761905 +PowerCons,0.5888888888888889,0.7555555555555555,0.7611111111111111,0.7388888888888889 +ProximalPhalanxOutlineAgeGroup,0.6487804878048781,0.6585365853658537,0.7317073170731707,0.8 +ProximalPhalanxOutlineCorrect,0.6426116838487973,0.6494845360824743,0.6460481099656358,0.6494845360824743 +ProximalPhalanxTW,0.5073170731707317,0.6195121951219512,0.6097560975609756,0.5414634146341464 +RefrigerationDevices,0.416,0.49866666666666665,0.45066666666666666,0.4693333333333333 +Rock,0.48,0.5,0.44,0.54 +ScreenType,0.4106666666666667,0.42133333333333334,0.4026666666666667,0.4186666666666667 +SemgHandGenderCh2,0.6833333333333333,0.615,0.575,0.5683333333333334 +SemgHandMovementCh2,0.3488888888888889,0.3244444444444444,0.2866666666666667,0.3466666666666667 +SemgHandSubjectCh2,0.45111111111111113,0.46,0.46444444444444444,0.3622222222222222 +ShapeletSim,0.5055555555555555,0.5277777777777778,0.5111111111111111,0.6333333333333333 +ShapesAll,0.47333333333333333,0.47333333333333333,0.48333333333333334,0.5866666666666667 +SmallKitchenAppliances,0.6346666666666667,0.48533333333333334,0.47733333333333333,0.5653333333333334 +SmoothSubspace,0.47333333333333333,0.7133333333333334,0.7066666666666667,0.74 +SonyAIBORobotSurface1,0.5507487520798668,0.6439267886855241,0.562396006655574,0.6056572379367721 +SonyAIBORobotSurface2,0.7219307450157397,0.770199370409234,0.7712486883525709,0.770199370409234 +StarLightCurves,0.7330014570179699,0.7620203982515784,0.7570422535211268,0.7527926177756192 +Strawberry,0.5108108108108108,0.5459459459459459,0.5081081081081081,0.5351351351351351 +SwedishLeaf,0.4112,0.4736,0.52,0.5376 +Symbols,0.8020100502512563,0.7829145728643216,0.7969849246231155,0.9256281407035176 +SyntheticControl,0.77,0.8433333333333334,0.8466666666666667,0.7 +ToeSegmentation1,0.5657894736842105,0.6008771929824561,0.5657894736842105,0.5219298245614035 +ToeSegmentation2,0.6230769230769231,0.8769230769230769,0.5538461538461539,0.5153846153846153 +Trace,0.8,0.59,0.55,0.55 +TwoLeadECG,0.5566286215978928,0.6812993854258121,0.6698858647936786,0.7225636523266022 +TwoPatterns,0.94475,0.38325,0.28375,0.4915 +UMD,0.5833333333333334,0.5555555555555556,0.5347222222222222,0.5069444444444444 +UWaveGestureLibraryAll,0.6066443327749861,0.7643774427694026,0.792573981016192,0.7216638749302066 +UWaveGestureLibraryX,0.6161362367392518,0.5979899497487438,0.6072026800670016,0.5985482970407594 +UWaveGestureLibraryY,0.48659966499162477,0.4963707426018984,0.4896705750977108,0.4916247906197655 +UWaveGestureLibraryZ,0.46733668341708545,0.49134561697375767,0.5217755443886097,0.4807370184254606 +Wafer,0.627514600908501,0.6299480856586632,0.6283257624918884,0.6276768332251784 +Wine,0.5,0.5,0.5,0.5185185185185185 +WordSynonyms,0.3777429467084639,0.3432601880877743,0.4012539184952978,0.4012539184952978 +Worms,0.4155844155844156,0.4675324675324675,0.4025974025974026,0.42857142857142855 +WormsTwoClass,0.5194805194805194,0.5714285714285714,0.5194805194805194,0.5454545454545454 +Yoga,0.5836666666666667,0.5383333333333333,0.5286666666666666,0.502 diff --git a/tsml_eval/publications/clustering/kasba/results/train-test/section-5.2/nmi_mean.csv b/tsml_eval/publications/clustering/kasba/results/train-test/section-5.2/nmi_mean.csv new file mode 100644 index 00000000..9b0773b4 --- /dev/null +++ b/tsml_eval/publications/clustering/kasba/results/train-test/section-5.2/nmi_mean.csv @@ -0,0 +1,112 @@ +Estimators:,DBA,KASBA,MBA,PAM-MSM +ACSF1,0.35383945779354287,0.5374208523965485,0.4479634958038584,0.5054863822593754 +Adiac,0.6375470250905653,0.623568434089461,0.6415408417164788,0.642707393644948 +ArrowHead,0.29643012561166004,0.2513352885967191,0.2648125233600215,0.2658556209479646 +BME,0.5843563884297436,0.19910294636892611,0.19385727522165028,0.31043220807296895 +Beef,0.362399611047738,0.2898835586391238,0.2985375894115358,0.2689189982122523 +BeetleFly,0.08068918390116703,0.15605571950205027,0.4207914918051405,0.3987532145992845 +BirdChicken,0.00732562257195427,0.037050681076412954,0.00732562257195427,0.03075180567649633 +CBF,0.6006694927473383,0.5052514594969757,0.4956953990435419,0.33387948732604283 +Car,0.1959457005016905,0.4871793649440263,0.39426411117273685,0.38008452610447285 +Chinatown,0.0531309116530706,0.027931043898821454,0.021074986002190366,0.059117117700911874 +ChlorineConcentration,0.0003894811173423732,0.002568379484547937,0.002908309037020895,0.002489593378990173 +CinCECGTorso,0.09823899203632493,0.15264844383889375,0.12229546412306509,0.17001330585147037 +Coffee,0.6953907421030353,0.604054963540982,0.604054963540982,0.8121962106666621 +Computers,0.0667291229792826,0.004244718832652609,0.08011495079348845,0.10815041527905132 +CricketX,0.49063506841275417,0.2672167254394314,0.2859134684692772,0.34045408945083155 +CricketY,0.40943430491108046,0.4058601365653581,0.36229449718880263,0.3864916421845877 +CricketZ,0.4591914629226061,0.2830293212559878,0.2694248244068143,0.3058618653054085 +DiatomSizeReduction,0.7103387495894317,0.5598800299531195,0.7264735714884517,0.6980839284370555 +DistalPhalanxOutlineAgeGroup,0.25374836830953235,0.18387058366194856,0.2097461075410133,0.21519708839592108 +DistalPhalanxOutlineCorrect,0.010579055442264259,0.024646177690453026,0.022377352267444143,0.02272152512827536 +DistalPhalanxTW,0.508905906193195,0.4861057282568561,0.5009864215890534,0.5196137519279127 +ECG200,0.029653665115550995,0.15279272139385752,0.13633480774843146,0.13633480774843146 +ECG5000,0.46214962726812514,0.5231640044175839,0.5868845534846435,0.4870482506330653 +ECGFiveDays,0.04889384575264635,0.1607152045400557,0.02862688193444752,0.16728145618026194 +EOGHorizontalSignal,0.3875468838812305,0.33676790273509083,0.369761517528025,0.3515907468414728 +EOGVerticalSignal,0.4140847200347209,0.30733972067760573,0.2892146206510721,0.3089086835449295 +Earthquakes,0.07023915050861004,0.06098846324137817,0.05976758351628091,0.07127208078342953 +ElectricDevices,0.3969228760092343,0.29825574675213984,0.32173904428111644,0.34945984658448687 +EthanolLevel,0.004198641145847507,0.005364241869609312,0.007836277970806145,0.007352252311258406 +FaceAll,0.6468805726478021,0.7189011013868107,0.7510992730153514,0.7321941035955527 +FaceFour,0.2676629569174973,0.5774855020612972,0.7935890390491593,0.6985348676146946 +FacesUCR,0.49794633316884007,0.7297507927370286,0.7631519069482406,0.7923797180075313 +FiftyWords,0.7108252702695419,0.7365478888590046,0.7773151346749823,0.755418848944105 +Fish,0.47708224191121085,0.38362218253481684,0.5666444298331772,0.5667552512623352 +FordA,0.00014230077745394252,0.021506632140750315,0.10798007283723791,0.004344119663191364 +FordB,0.008972200404034784,0.000689622885847421,0.07679721897837051,0.0019350047879034679 +FreezerRegularTrain,0.2074352169737503,0.21176077865580115,0.21265282294130813,0.21507224195367378 +FreezerSmallTrain,0.2107702396464477,0.20790201438350228,0.2117718612603298,0.2100120374977789 +GunPoint,0.00047704114409563445,0.0011106438333565868,0.0045279840055839505,0.0011106438333565868 +GunPointAgeSpan,0.057709884167047996,0.05806753757416144,0.05875269423797655,0.07283091658380218 +GunPointMaleVersusFemale,0.5408098602848245,0.5614631910034454,0.5544867158864274,0.5614631910034454 +GunPointOldVersusYoung,0.01104523123814151,0.0040822452843238795,0.016363474541610006,0.01803292698850128 +Ham,0.04955341646894403,0.061431206724673316,0.07304904230265058,0.009165494843918912 +HandOutlines,0.033513931034719495,0.07477309858390056,0.008252041073003636,0.04298581356306486 +Haptics,0.06142052593961523,0.10978682652494437,0.10363731416105759,0.12923629189532468 +Herring,0.028110616199652636,0.04406145569523074,0.005862520840092283,0.04028126349322462 +HouseTwenty,0.19287954907826735,0.4361549719235438,0.282089992758897,0.32094264140374623 +InlineSkate,0.07834404991474059,0.07102122073937205,0.07614345834804842,0.07566630608855378 +InsectEPGRegularTrain,0.30749042222589323,0.3106416571888718,0.19406592329232167,0.2016715138432619 +InsectEPGSmallTrain,0.24089084926838336,0.31747248367382674,0.2675258750383524,0.28757495636767605 +InsectWingbeatSound,0.11198421236962082,0.5403472534980323,0.5458651760692883,0.4981038109240118 +ItalyPowerDemand,0.0070432981627318375,0.4468814406309945,0.0021580154741368965,0.0023906068612844023 +LargeKitchenAppliances,0.16081548422402925,0.09840345369041449,0.13531980805976743,0.11635527348977204 +Lightning2,0.060385073862730385,0.06782178820853738,0.041608543137406334,0.0004936067574970536 +Lightning7,0.45865576471413005,0.4754432918697631,0.5092721915893511,0.5513164662188246 +Mallat,0.9093543522957996,0.9048942568119032,0.888933965865711,0.8474380690700876 +Meat,0.5833367752933948,0.4114873024772571,0.397399398204838,0.43166098822610427 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+SmoothSubspace,0.25890096652772804,0.3630312432347497,0.29856520913079265,0.39720402816007394 +SonyAIBORobotSurface1,0.12809229448545387,0.08289352369495208,0.030699258008789233,0.05483787633054959 +SonyAIBORobotSurface2,0.14757597792332797,0.2105022428756164,0.21264868490885308,0.2105022428756164 +StarLightCurves,0.6463241088940114,0.6034598032954775,0.6017818789310015,0.6017163142102289 +Strawberry,0.12264157609605783,0.11637097596008786,0.10601514780281704,0.11681347290758243 +SwedishLeaf,0.5570635682422584,0.6498379987234825,0.6962890684802249,0.643217533934396 +Symbols,0.8739399356790699,0.8433554400133222,0.8623637202719406,0.8826337860773654 +SyntheticControl,0.8849072590634538,0.8160728397736438,0.8055587461211591,0.7936836245939918 +ToeSegmentation1,0.011044866757555947,0.028211621071287114,0.0111679089028265,0.0003279255044384759 +ToeSegmentation2,0.004335655366058318,0.2666562095954819,0.004991753381149691,0.006979197968254056 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+Worms,0.22027780999652524,0.23423632635302075,0.1913696694386062,0.23609771968158813 +WormsTwoClass,0.011133073027485847,0.03923814647078223,0.00037451023820847166,0.017939120224354475 +Yoga,0.017772133701760864,0.002180530986216767,0.0010759782845229278,8.814360004426598e-05 diff --git a/tsml_eval/publications/clustering/kasba/results/train-test/section-5.3/ari_mean.csv b/tsml_eval/publications/clustering/kasba/results/train-test/section-5.3/ari_mean.csv new file mode 100644 index 00000000..d29021df --- /dev/null +++ b/tsml_eval/publications/clustering/kasba/results/train-test/section-5.3/ari_mean.csv @@ -0,0 +1,113 @@ +Estimators:,KESBA,R-Clust,TTC,U-Shape +ACSF1,0.2443644124316393,0.32212885154061627,0.05668016194331984,0.010193225958089018 +Adiac,0.23423593164242065,0.22413379065383046,0.13850751624278623,0.0010434672779856353 +ArrowHead,0.2187386093526287,0.15606382301055446,0.04830354678986829,-0.00781892324321399 +BME,0.13566770875040274,0.2638946068340881,0.5010491753373126,7.3058760247632665e-06 +Beef,0.055541529916687704,0.0,0.026767878545745107,0.00629142792944613 +BeetleFly,0.1211453744493392,0.21227197346600332,-0.011086474501108648,0.0 +BirdChicken,-0.004405286343612335,0.13071895424836602,-0.05555555555555555,0.0 +CBF,0.35688368418783095,0.9387848357002985,0.7822687762308659,0.08566628497717493 +Car,0.32594376284011206,0.3640627024225936,0.13373821172436098,-0.0005770371714884037 +Chinatown,0.06973426035734383,0.014166394787569807,0.12337408553078709,-0.003060910725025075 +ChlorineConcentration,0.004697199288738433,0.012055354242113717,-0.00043349690709759616,0.007740559381788398 +CinCECGTorso,0.1341889063749661,0.1339835014245881,0.03529161793170628,0.0 +Coffee,0.6029745399546257,0.30088272383354353,0.7249601208966502,0.0542907180385289 +Computers,0.0003244979745918086,0.09400726879474633,0.05392915392969579,0.0 +CricketX,0.08370664677927571,0.12804077679609557,0.1633162700368302,0.008035137873159133 +CricketY,0.19114730596100596,0.11472352982554991,0.18489172356508402,0.03750310504645328 +CricketZ,0.0988621213093179,0.13073309450355683,0.16707384692896127,0.0 +Crop,0.25413093788005386,0.21781608455807958,0.1624062486146408,2.835281568294271e-08 +DiatomSizeReduction,0.49821153456368134,0.6130526488052795,0.3170212050014104,0.4283578768356205 +DistalPhalanxOutlineAgeGroup,0.14478091719061018,0.2531268032160976,0.18881310856225392,0.023504959740991614 +DistalPhalanxOutlineCorrect,0.04428023004963268,0.07154803060438579,0.06704869245260746,0.0 +DistalPhalanxTW,0.5042578501426888,0.37733684700233044,0.3568036515484333,0.08654700877550611 +ECG200,0.23525119356431898,0.20149646214428088,0.013063691589639225,0.10822379799377378 +ECG5000,0.6985959819857679,0.5581241008072616,0.4125466251628732,-0.008520311740289926 +ECGFiveDays,0.17886555788180827,0.0909315731923672,-0.0007146114662175406,0.0 +EOGHorizontalSignal,0.13917334188530517,0.16688737373970694,0.2118510976931968,0.013395667970704827 +EOGVerticalSignal,0.11635278180486176,0.0765901051650399,0.2079197337188898,0.012038341263471688 +Earthquakes,-0.03890690001305775,-0.09551759511817433,-0.06883911151393915,0.0 +ElectricDevices,0.1568937165186581,0.18110528587632552,0.3365565889447312,0.0 +EthanolLevel,-0.0009704739225344128,0.0024338491624334192,-0.0018411932509570133,8.987506234169118e-05 +FaceAll,0.5002991512927215,0.2410825422216883,0.39771419970413846,0.0 +FaceFour,0.4739971318356817,0.3595374095229628,0.18660874492397772,0.0 +FacesUCR,0.6155932149697018,0.2522134256218966,0.41420061875487435,0.016634418780718876 +FiftyWords,0.40723162578574995,0.18009995602455972,0.36826597742131173,0.009660913108242615 +Fish,0.2330668502279762,0.22736836620659728,0.2624810270143266,0.0 +FordA,0.011398718535390257,0.0025588079729149905,0.0009626610234683776,-0.0006740652874494682 +FordB,-6.697901364215425e-06,-0.0010794444594624157,0.002930001083107624,-0.0005372858034429471 +FreezerRegularTrain,0.27823454849449264,0.15914440414218178,0.25220171519468393,0.9957924289648099 +FreezerSmallTrain,0.26723530388247846,0.18176197913499412,0.21555982582321115,0.055081356435453956 +GunPoint,-0.005115359852913385,0.16704372230175302,-0.005997289919124703,0.0 +GunPointAgeSpan,0.06798475021503127,0.7400921002658565,0.06476146893948061,0.3226315544812198 +GunPointMaleVersusFemale,0.5659054585723198,0.008437137307796976,0.5563831611541222,0.007249712714330803 +GunPointOldVersusYoung,0.0021622428390057125,0.013843684285901213,0.023197161634378294,0.08429822836499967 +Ham,0.04908887763550283,0.09003956349723925,0.006129646531228521,0.01717326711286547 +HandOutlines,-0.002107960440724597,0.06641239124983445,0.08425984775995203,0.0 +Haptics,0.0716090752526205,0.055675814315567444,0.01655436826050018,0.0 +Herring,0.06328565065374807,-0.015633117649837058,-0.009029906387209014,0.008284387298060674 +HouseTwenty,0.4111555587070966,0.371059100459787,0.7180214217699394,0.0 +InlineSkate,0.021222707566240603,0.047369943935807256,0.046335734913393864,0.0 +InsectEPGRegularTrain,0.31136809896459505,0.27203084048006554,0.14102188496407278,0.0 +InsectEPGSmallTrain,0.29628137093985507,0.2588415586673866,0.20389921953325854,0.0006077940350556123 +InsectWingbeatSound,0.3655593295847043,0.1511526288869105,0.06362968110806534,0.10869506316340265 +ItalyPowerDemand,0.5125261454164635,-0.0006842903895107149,0.003232554191246998,0.00428369274639077 +LargeKitchenAppliances,0.015844920674138188,0.008768364643545279,0.2101839415421918,0.0 +Lightning2,0.0821152192605331,-0.013913367436128903,0.18334765177548681,0.0 +Lightning7,0.24828144079082942,0.26613160220377347,0.37401662641018923,0.0 +Mallat,0.8221034353032259,0.39391004638163535,0.47446207410423347,0.10727337029146067 +Meat,0.29711971391025227,0.562962962962963,0.437082112538502,0.562962962962963 +MedicalImages,0.04036209302246069,0.0902756452267669,0.0936442994438316,-0.03743403465140181 +MiddlePhalanxOutlineAgeGroup,0.07962382111832941,0.09532145811346587,0.0472802671525964,-0.006816252917462338 +MiddlePhalanxOutlineCorrect,0.03592334416406122,0.07432861675109441,0.09775852588135821,0.0 +MiddlePhalanxTW,0.2712602319459799,0.3510918395475019,0.40739187325179216,0.06895861064631485 +MixedShapesRegularTrain,0.40455026438171876,0.28921971782765743,0.4665921692135175,0.0 +MixedShapesSmallTrain,0.3818150286000059,0.266764345734425,0.2522642782250936,0.0 +MoteStrain,0.006733939700696405,0.39725851300982223,0.5185577938735648,0.0011158354532234509 +NonInvasiveFetalECGThorax1,0.468893114707966,0.3451087640674484,0.1488690384546952,0.03462227322809121 +NonInvasiveFetalECGThorax2,0.5725996303844039,0.2897306389045231,0.26812393550001257,0.04058309754688268 +OSULeaf,0.19525862492559823,0.3125704238356418,0.0785827072168645,0.006769133666958596 +OliveOil,0.31230976144970624,0.44833255049318926,0.3547280093873846,0.0 +PhalangesOutlinesCorrect,0.057161335752853905,0.06590035900495769,-0.022761608852178702,0.0 +Phoneme,0.08746038969700026,0.04703448121538291,0.06850054908298818,0.010813278937721865 +PigAirwayPressure,0.02627122522769921,0.05540719230470067,0.03332321602581511,0.0023586574521782203 +PigArtPressure,0.1823458282950423,0.16939492043226484,0.08760522203740108,0.03072241141946236 +PigCVP,0.06476262923135438,0.09970747109535823,0.015932159835538997,0.016523911804672775 +Plane,0.7713697145009271,0.7007849363776639,0.6034767822755686,0.36404895010650756 +PowerCons,0.2573335071317438,0.15530198996279743,0.12303261095340304,-3.5936817546012946e-05 +ProximalPhalanxOutlineAgeGroup,0.44426195236547267,0.5850146205892631,0.465204128591856,-0.014954663351162132 +ProximalPhalanxOutlineCorrect,0.08130537128937242,0.07389257747720981,0.0760893072923484,0.0843996690209058 +ProximalPhalanxTW,0.5501955095345865,0.4574343353724778,0.5568109660243594,0.02029510979240905 +RefrigerationDevices,0.07118369708963575,0.027805014328007627,0.12448502667901294,0.0 +Rock,0.1608326088759596,0.08825650669029043,0.09660192631679329,0.0 +ScreenType,0.02106872173323338,0.032682281508057874,0.022329277988599273,0.0 +SemgHandGenderCh2,0.03140761594099455,0.0704062955581619,0.1132869199049421,0.0 +SemgHandMovementCh2,0.09479070933928975,0.07011499419820129,0.10966117442553391,0.0024372775792112795 +SemgHandSubjectCh2,0.1685322755558619,0.13290231171474523,0.10439539292693283,0.02016722743297107 +ShapeletSim,-0.002430091523738124,0.8291695681243775,-0.0020075852894465207,-0.00514670608037846 +ShapesAll,0.2940054307342984,0.2257934627611414,0.26766833830708014,0.003867257835126324 +SmallKitchenAppliances,0.11528388388957152,0.14120929321110332,0.2800204689775821,0.0 +SmoothSubspace,0.3842875431460565,0.15291150391990627,0.26072631739203417,-0.0007107656000555285 +SonyAIBORobotSurface1,0.08060385920236315,0.6233672339938188,0.08896526961836623,0.0 +SonyAIBORobotSurface2,0.290290577060023,0.4546798374361773,0.10366434470283722,0.0 +StarLightCurves,0.5219801296467216,0.4620944832064472,0.5916746309571813,0.012944929482004968 +Strawberry,-0.021286697505857335,-0.023283854929313508,-0.0025358274861893744,-0.01939795857321668 +SwedishLeaf,0.3769291363758545,0.31408587382758363,0.24209846406446467,0.00262249988416018 +Symbols,0.7389038898076614,0.6563295855206341,0.5973625739026807,0.23059285047374214 +SyntheticControl,0.7128764867819993,0.6925729603860646,0.7148137462237147,0.2742015617414314 +ToeSegmentation1,0.03650690083386775,0.01796773529116372,0.04433750770509616,0.30249854120817504 +ToeSegmentation2,0.4268765283427481,0.1756592643997224,0.3340890043430188,0.0 +Trace,0.36774146304202493,0.5833999791742929,0.7487164346932774,0.7487164346932774 +TwoLeadECG,0.13083058046685458,-0.0003818709873960303,0.05173384674099623,0.0107528113633854 +TwoPatterns,0.05424458367452428,0.2600441616383603,0.562285207189457,-0.00019526500688702865 +UMD,0.11896910794862894,0.4282722320844755,0.3746996044700325,0.0003940482298614674 +UWaveGestureLibraryAll,0.5923933384877387,0.15975636191208437,0.2644795996599823,0.0 +UWaveGestureLibraryX,0.3946852459526184,0.305535491349929,0.3595688988964607,0.0 +UWaveGestureLibraryY,0.3151899048276799,0.23703281827314182,0.28285003944950043,0.0 +UWaveGestureLibraryZ,0.371388123717569,0.22854790929309274,0.2146644849403332,0.0 +Wafer,0.0048481719752093465,0.006116573447743555,-0.00020116183880248309,-0.007616511826580255 +Wine,0.0,-0.01772525849335303,0.00841908325537886,0.0 +WordSynonyms,0.25083713173835637,0.12528027433287423,0.24836825669872464,0.007866288045669401 +Worms,0.1546744061840112,0.2730131647760146,0.08036953844592756,0.0 +WormsTwoClass,0.00639026950267033,0.007585101134681796,-0.012919338924518993,0.0 +Yoga,0.004844776256848145,0.007702731857451691,0.0014817736192238886,-2.902831294793416e-05 diff --git a/tsml_eval/publications/clustering/kasba/results/train-test/section-5.3/clacc_mean.csv b/tsml_eval/publications/clustering/kasba/results/train-test/section-5.3/clacc_mean.csv new file mode 100644 index 00000000..aa928fe2 --- /dev/null +++ b/tsml_eval/publications/clustering/kasba/results/train-test/section-5.3/clacc_mean.csv @@ -0,0 +1,113 @@ +Estimators:,KESBA,R-Clust,TTC,U-Shape +ACSF1,0.41,0.54,0.27,0.16 +Adiac,0.3836317135549872,0.38107416879795397,0.2659846547314578,0.05370843989769821 +ArrowHead,0.6057142857142858,0.5314285714285715,0.4342857142857143,0.36 +BME,0.5066666666666667,0.58,0.7066666666666667,0.3466666666666667 +Beef,0.43333333333333335,0.3,0.36666666666666664,0.26666666666666666 +BeetleFly,0.7,0.75,0.6,0.5 +BirdChicken,0.6,0.7,0.5,0.5 +CBF,0.7455555555555555,0.9788888888888889,0.9211111111111111,0.4855555555555556 +Car,0.6166666666666667,0.6666666666666666,0.5333333333333333,0.3333333333333333 +Chinatown,0.6501457725947521,0.5685131195335277,0.6869565217391305,0.5130434782608696 +ChlorineConcentration,0.39166666666666666,0.42604166666666665,0.38958333333333334,0.5395833333333333 +CinCECGTorso,0.4528985507246377,0.4492753623188406,0.3456521739130435,0.2536231884057971 +Coffee,0.8928571428571429,0.7857142857142857,0.9285714285714286,0.6428571428571429 +Computers,0.524,0.656,0.62,0.5 +CricketX,0.27692307692307694,0.3153846153846154,0.3769230769230769,0.1282051282051282 +CricketY,0.35128205128205126,0.2923076923076923,0.3282051282051282,0.16666666666666666 +CricketZ,0.3076923076923077,0.30512820512820515,0.37435897435897436,0.10256410256410256 +Crop,0.35333333333333333,0.3367857142857143,0.27339285714285716,0.04178571428571429 +DiatomSizeReduction,0.6895424836601307,0.8006535947712419,0.6993464052287581,0.5816993464052288 +DistalPhalanxOutlineAgeGroup,0.5827338129496403,0.7122302158273381,0.5035971223021583,0.5323741007194245 +DistalPhalanxOutlineCorrect,0.6123188405797102,0.6376811594202898,0.6340579710144928,0.5833333333333334 +DistalPhalanxTW,0.5683453237410072,0.5611510791366906,0.5035971223021583,0.4244604316546763 +ECG200,0.75,0.73,0.62,0.7 +ECG5000,0.7311111111111112,0.7104444444444444,0.5817777777777777,0.4331111111111111 +ECGFiveDays,0.7119628339140535,0.6515679442508711,0.5063879210220673,0.502903600464576 +EOGHorizontalSignal,0.30662983425414364,0.36187845303867405,0.4088397790055249,0.143646408839779 +EOGVerticalSignal,0.30386740331491713,0.2513812154696133,0.40331491712707185,0.13812154696132597 +Earthquakes,0.5107913669064749,0.5683453237410072,0.5323741007194245,0.7482014388489209 +ElectricDevices,0.31682012709116847,0.36285825444170666,0.5065490857216963,0.2536635974581766 +EthanolLevel,0.292,0.302,0.286,0.258 +FaceAll,0.642603550295858,0.3715976331360947,0.5106508875739645,0.16982248520710058 +FaceFour,0.7045454545454546,0.6136363636363636,0.5227272727272727,0.29545454545454547 +FacesUCR,0.6687804878048781,0.408780487804878,0.5663414634146341,0.18439024390243902 +FiftyWords,0.5076923076923077,0.2923076923076923,0.4725274725274725,0.13846153846153847 +Fish,0.44571428571428573,0.46285714285714286,0.44571428571428573,0.1657142857142857 +FordA,0.5553030303030303,0.5287878787878788,0.5212121212121212,0.509090909090909 +FordB,0.5148148148148148,0.5061728395061729,0.5320987654320988,0.5098765432098765 +FreezerRegularTrain,0.763859649122807,0.6996491228070175,0.7512280701754386,0.9989473684210526 +FreezerSmallTrain,0.7585964912280702,0.7133333333333334,0.732280701754386,0.6175438596491228 +GunPoint,0.52,0.7066666666666667,0.5133333333333333,0.5066666666666667 +GunPointAgeSpan,0.6329113924050633,0.930379746835443,0.629746835443038,0.7848101265822784 +GunPointMaleVersusFemale,0.8765822784810127,0.5537974683544303,0.8734177215189873,0.5506329113924051 +GunPointOldVersusYoung,0.5365079365079365,0.5650793650793651,0.580952380952381,0.6476190476190476 +Ham,0.6190476190476191,0.6571428571428571,0.5619047619047619,0.5714285714285714 +HandOutlines,0.5621621621621622,0.6324324324324324,0.654054054054054,0.6405405405405405 +Haptics,0.36363636363636365,0.32792207792207795,0.2857142857142857,0.21753246753246752 +Herring,0.640625,0.5,0.546875,0.578125 +HouseTwenty,0.8235294117647058,0.8067226890756303,0.9243697478991597,0.5798319327731093 +InlineSkate,0.22363636363636363,0.22545454545454546,0.2727272727272727,0.18363636363636363 +InsectEPGRegularTrain,0.642570281124498,0.6506024096385542,0.5341365461847389,0.4738955823293173 +InsectEPGSmallTrain,0.6104417670682731,0.5783132530120482,0.5220883534136547,0.4779116465863454 +InsectWingbeatSound,0.5272727272727272,0.2737373737373737,0.2398989898989899,0.25303030303030305 +ItalyPowerDemand,0.858114674441205,0.5063168124392614,0.5306122448979592,0.5335276967930029 +LargeKitchenAppliances,0.392,0.3893333333333333,0.6053333333333333,0.3333333333333333 +Lightning2,0.6557377049180327,0.5245901639344263,0.7213114754098361,0.5409836065573771 +Lightning7,0.4794520547945205,0.5068493150684932,0.5753424657534246,0.2602739726027397 +Mallat,0.8550106609808102,0.5471215351812366,0.5390191897654584,0.2771855010660981 +Meat,0.6833333333333333,0.6666666666666666,0.6666666666666666,0.6666666666666666 +MedicalImages,0.3078947368421053,0.32105263157894737,0.37105263157894736,0.2736842105263158 +MiddlePhalanxOutlineAgeGroup,0.5974025974025974,0.538961038961039,0.512987012987013,0.564935064935065 +MiddlePhalanxOutlineCorrect,0.6116838487972509,0.6391752577319587,0.6597938144329897,0.570446735395189 +MiddlePhalanxTW,0.461038961038961,0.487012987012987,0.5194805194805194,0.36363636363636365 +MixedShapesRegularTrain,0.5694845360824742,0.537319587628866,0.6284536082474227,0.26969072164948454 +MixedShapesSmallTrain,0.5645360824742268,0.5158762886597938,0.5567010309278351,0.26969072164948454 +MoteStrain,0.5487220447284346,0.8154952076677316,0.860223642172524,0.542332268370607 +NonInvasiveFetalECGThorax1,0.5384223918575064,0.46208651399491096,0.2564885496183206,0.11653944020356234 +NonInvasiveFetalECGThorax2,0.6519083969465649,0.4300254452926209,0.35521628498727736,0.0926208651399491 +OSULeaf,0.3925619834710744,0.5785123966942148,0.3347107438016529,0.23553719008264462 +OliveOil,0.6,0.6666666666666666,0.6666666666666666,0.4 +PhalangesOutlinesCorrect,0.6247086247086248,0.6293706293706294,0.5407925407925408,0.6130536130536131 +Phoneme,0.1930379746835443,0.1629746835443038,0.19251054852320676,0.10864978902953587 +PigAirwayPressure,0.25961538461538464,0.25961538461538464,0.27884615384615385,0.038461538461538464 +PigArtPressure,0.4375,0.38461538461538464,0.35096153846153844,0.07211538461538461 +PigCVP,0.32211538461538464,0.3557692307692308,0.2644230769230769,0.07211538461538461 +Plane,0.8380952380952381,0.780952380952381,0.7238095238095238,0.44761904761904764 +PowerCons,0.7555555555555555,0.7,0.6777777777777778,0.5222222222222223 +ProximalPhalanxOutlineAgeGroup,0.6585365853658537,0.7853658536585366,0.7073170731707317,0.47317073170731705 +ProximalPhalanxOutlineCorrect,0.6494845360824743,0.6426116838487973,0.6460481099656358,0.7147766323024055 +ProximalPhalanxTW,0.6195121951219512,0.5951219512195122,0.6292682926829268,0.3804878048780488 +RefrigerationDevices,0.49866666666666665,0.44,0.56,0.3333333333333333 +Rock,0.5,0.4,0.5,0.42 +ScreenType,0.42133333333333334,0.424,0.43733333333333335,0.3333333333333333 +SemgHandGenderCh2,0.615,0.655,0.6716666666666666,0.65 +SemgHandMovementCh2,0.3244444444444444,0.29777777777777775,0.3711111111111111,0.20444444444444446 +SemgHandSubjectCh2,0.46,0.4266666666666667,0.3711111111111111,0.27555555555555555 +ShapeletSim,0.5277777777777778,0.9555555555555556,0.5277777777777778,0.5 +ShapesAll,0.47333333333333333,0.36666666666666664,0.42333333333333334,0.03833333333333333 +SmallKitchenAppliances,0.48533333333333334,0.5653333333333334,0.6213333333333333,0.3333333333333333 +SmoothSubspace,0.7133333333333334,0.5333333333333333,0.64,0.34 +SonyAIBORobotSurface1,0.6439267886855241,0.8951747088186356,0.6505823627287853,0.5707154742096506 +SonyAIBORobotSurface2,0.770199370409234,0.8373557187827911,0.6694648478488983,0.6169989506820567 +StarLightCurves,0.7620203982515784,0.7039825157843613,0.8127731908693541,0.4448761534725595 +Strawberry,0.5459459459459459,0.5297297297297298,0.5594594594594594,0.6189189189189189 +SwedishLeaf,0.4736,0.4864,0.4032,0.112 +Symbols,0.7829145728643216,0.6653266331658292,0.6080402010050251,0.41105527638190953 +SyntheticControl,0.8433333333333334,0.7266666666666667,0.74,0.44 +ToeSegmentation1,0.6008771929824561,0.5745614035087719,0.6096491228070176,0.7763157894736842 +ToeSegmentation2,0.8769230769230769,0.7384615384615385,0.823076923076923,0.8153846153846154 +Trace,0.59,0.79,0.81,0.81 +TwoLeadECG,0.6812993854258121,0.5109745390693591,0.6145741878841089,0.553116769095698 +TwoPatterns,0.38325,0.5575,0.67775,0.258 +UMD,0.5555555555555556,0.6666666666666666,0.6597222222222222,0.3472222222222222 +UWaveGestureLibraryAll,0.7643774427694026,0.34952540480178673,0.4232272473478504,0.12841987716359576 +UWaveGestureLibraryX,0.5979899497487438,0.5039084310441094,0.5639307649357901,0.12841987716359576 +UWaveGestureLibraryY,0.4963707426018984,0.4586823003908431,0.43299832495812396,0.12841987716359576 +UWaveGestureLibraryZ,0.49134561697375767,0.40954773869346733,0.41317699609156894,0.12841987716359576 +Wafer,0.6299480856586632,0.631570408825438,0.6273523685918235,0.5631083711875405 +Wine,0.5,0.5185185185185185,0.5555555555555556,0.5 +WordSynonyms,0.3432601880877743,0.2664576802507837,0.3463949843260188,0.2304075235109718 +Worms,0.4675324675324675,0.5714285714285714,0.42857142857142855,0.42857142857142855 +WormsTwoClass,0.5714285714285714,0.5714285714285714,0.5064935064935064,0.5714285714285714 +Yoga,0.5383333333333333,0.5466666666666666,0.5266666666666666,0.5193333333333333 diff --git a/tsml_eval/publications/clustering/kasba/results/train-test/section-5.3/clacc_ranks.csv b/tsml_eval/publications/clustering/kasba/results/train-test/section-5.3/clacc_ranks.csv new file mode 100644 index 00000000..45c20f7a --- /dev/null +++ b/tsml_eval/publications/clustering/kasba/results/train-test/section-5.3/clacc_ranks.csv @@ -0,0 +1,113 @@ +Estimators:,KESBA,R-Clust,TTC,U-Shape +ACSF1,2.0,1.0,3.0,4.0 +Adiac,1.0,2.0,3.0,4.0 +ArrowHead,1.0,2.0,3.0,4.0 +BME,3.0,2.0,1.0,4.0 +Beef,1.0,3.0,2.0,4.0 +BeetleFly,2.0,1.0,3.0,4.0 +BirdChicken,2.0,1.0,3.5,3.5 +CBF,3.0,1.0,2.0,4.0 +Car,2.0,1.0,3.0,4.0 +Chinatown,2.0,3.0,1.0,4.0 +ChlorineConcentration,3.0,2.0,4.0,1.0 +CinCECGTorso,1.0,2.0,3.0,4.0 +Coffee,2.0,3.0,1.0,4.0 +Computers,3.0,1.0,2.0,4.0 +CricketX,3.0,2.0,1.0,4.0 +CricketY,1.0,3.0,2.0,4.0 +CricketZ,2.0,3.0,1.0,4.0 +Crop,1.0,2.0,3.0,4.0 +DiatomSizeReduction,3.0,1.0,2.0,4.0 +DistalPhalanxOutlineAgeGroup,2.0,1.0,4.0,3.0 +DistalPhalanxOutlineCorrect,3.0,1.0,2.0,4.0 +DistalPhalanxTW,1.0,2.0,3.0,4.0 +ECG200,1.0,2.0,4.0,3.0 +ECG5000,1.0,2.0,3.0,4.0 +ECGFiveDays,1.0,2.0,3.0,4.0 +EOGHorizontalSignal,3.0,2.0,1.0,4.0 +EOGVerticalSignal,2.0,3.0,1.0,4.0 +Earthquakes,4.0,2.0,3.0,1.0 +ElectricDevices,3.0,2.0,1.0,4.0 +EthanolLevel,2.0,1.0,3.0,4.0 +FaceAll,1.0,3.0,2.0,4.0 +FaceFour,1.0,2.0,3.0,4.0 +FacesUCR,1.0,3.0,2.0,4.0 +FiftyWords,1.0,3.0,2.0,4.0 +Fish,2.5,1.0,2.5,4.0 +FordA,1.0,2.0,3.0,4.0 +FordB,2.0,4.0,1.0,3.0 +FreezerRegularTrain,2.0,4.0,3.0,1.0 +FreezerSmallTrain,1.0,3.0,2.0,4.0 +GunPoint,2.0,1.0,3.0,4.0 +GunPointAgeSpan,3.0,1.0,4.0,2.0 +GunPointMaleVersusFemale,1.0,3.0,2.0,4.0 +GunPointOldVersusYoung,4.0,3.0,2.0,1.0 +Ham,2.0,1.0,4.0,3.0 +HandOutlines,4.0,3.0,1.0,2.0 +Haptics,1.0,2.0,3.0,4.0 +Herring,1.0,4.0,3.0,2.0 +HouseTwenty,2.0,3.0,1.0,4.0 +InlineSkate,3.0,2.0,1.0,4.0 +InsectEPGRegularTrain,2.0,1.0,3.0,4.0 +InsectEPGSmallTrain,1.0,2.0,3.0,4.0 +InsectWingbeatSound,1.0,2.0,4.0,3.0 +ItalyPowerDemand,1.0,4.0,3.0,2.0 +LargeKitchenAppliances,2.0,3.0,1.0,4.0 +Lightning2,2.0,4.0,1.0,3.0 +Lightning7,3.0,2.0,1.0,4.0 +Mallat,1.0,2.0,3.0,4.0 +Meat,1.0,3.0,3.0,3.0 +MedicalImages,3.0,2.0,1.0,4.0 +MiddlePhalanxOutlineAgeGroup,1.0,3.0,4.0,2.0 +MiddlePhalanxOutlineCorrect,3.0,2.0,1.0,4.0 +MiddlePhalanxTW,3.0,2.0,1.0,4.0 +MixedShapesRegularTrain,2.0,3.0,1.0,4.0 +MixedShapesSmallTrain,1.0,3.0,2.0,4.0 +MoteStrain,3.0,2.0,1.0,4.0 +NonInvasiveFetalECGThorax1,1.0,2.0,3.0,4.0 +NonInvasiveFetalECGThorax2,1.0,2.0,3.0,4.0 +OSULeaf,2.0,1.0,3.0,4.0 +OliveOil,3.0,1.5,1.5,4.0 +PhalangesOutlinesCorrect,2.0,1.0,4.0,3.0 +Phoneme,1.0,3.0,2.0,4.0 +PigAirwayPressure,2.5,2.5,1.0,4.0 +PigArtPressure,1.0,2.0,3.0,4.0 +PigCVP,2.0,1.0,3.0,4.0 +Plane,1.0,2.0,3.0,4.0 +PowerCons,1.0,2.0,3.0,4.0 +ProximalPhalanxOutlineAgeGroup,3.0,1.0,2.0,4.0 +ProximalPhalanxOutlineCorrect,2.0,4.0,3.0,1.0 +ProximalPhalanxTW,2.0,3.0,1.0,4.0 +RefrigerationDevices,2.0,3.0,1.0,4.0 +Rock,1.5,4.0,1.5,3.0 +ScreenType,3.0,2.0,1.0,4.0 +SemgHandGenderCh2,4.0,2.0,1.0,3.0 +SemgHandMovementCh2,2.0,3.0,1.0,4.0 +SemgHandSubjectCh2,1.0,2.0,3.0,4.0 +ShapeletSim,2.5,1.0,2.5,4.0 +ShapesAll,1.0,3.0,2.0,4.0 +SmallKitchenAppliances,3.0,2.0,1.0,4.0 +SmoothSubspace,1.0,3.0,2.0,4.0 +SonyAIBORobotSurface1,3.0,1.0,2.0,4.0 +SonyAIBORobotSurface2,2.0,1.0,3.0,4.0 +StarLightCurves,2.0,3.0,1.0,4.0 +Strawberry,3.0,4.0,2.0,1.0 +SwedishLeaf,2.0,1.0,3.0,4.0 +Symbols,1.0,2.0,3.0,4.0 +SyntheticControl,1.0,3.0,2.0,4.0 +ToeSegmentation1,3.0,4.0,2.0,1.0 +ToeSegmentation2,1.0,4.0,2.0,3.0 +Trace,4.0,3.0,1.5,1.5 +TwoLeadECG,1.0,4.0,2.0,3.0 +TwoPatterns,3.0,2.0,1.0,4.0 +UMD,3.0,1.0,2.0,4.0 +UWaveGestureLibraryAll,1.0,3.0,2.0,4.0 +UWaveGestureLibraryX,1.0,3.0,2.0,4.0 +UWaveGestureLibraryY,1.0,2.0,3.0,4.0 +UWaveGestureLibraryZ,1.0,3.0,2.0,4.0 +Wafer,2.0,1.0,3.0,4.0 +Wine,3.5,2.0,1.0,3.5 +WordSynonyms,2.0,3.0,1.0,4.0 +Worms,2.0,1.0,3.5,3.5 +WormsTwoClass,2.0,2.0,4.0,2.0 +Yoga,2.0,1.0,3.0,4.0 diff --git a/tsml_eval/publications/clustering/kasba/results/train-test/section-5.3/nmi_mean.csv b/tsml_eval/publications/clustering/kasba/results/train-test/section-5.3/nmi_mean.csv new file mode 100644 index 00000000..af1d6ca8 --- /dev/null +++ b/tsml_eval/publications/clustering/kasba/results/train-test/section-5.3/nmi_mean.csv @@ -0,0 +1,113 @@ +clacc_mean.csvEstimators:,KESBA,R-Clust,TTC,U-Shape +ACSF1,0.5374208523965485,0.5909709069819624,0.3163724171138812,0.12596163172859107 +Adiac,0.623568434089461,0.6088126231569829,0.5512411106260867,0.031572558947779314 +ArrowHead,0.2513352885967191,0.25541890252609156,0.14837741436083865,0.042041651679397565 +BME,0.19910294636892611,0.2733950000970741,0.5843563884297435,0.01567378145353249 +Beef,0.2898835586391238,0.19602205739058812,0.2743748744478315,0.11131221042700525 +BeetleFly,0.15605571950205027,0.22139341039056704,0.03075180567649633,0.0 +BirdChicken,0.037050681076412954,0.27463724921161203,0.0,0.0 +CBF,0.5052514594969757,0.9277945772967522,0.7310094605019878,0.1435720408692961 +Car,0.4871793649440263,0.49055886245944796,0.20597739423431063,0.04770958492792366 +Chinatown,0.027931043898821454,0.0355639274817777,0.06433602095054523,0.004048701561562199 +ChlorineConcentration,0.002568379484547937,0.02689784349890683,0.0006160913562375848,0.019671201520486438 +CinCECGTorso,0.15264844383889375,0.1612010982291313,0.05267624109773804,0.0 +Coffee,0.604054963540982,0.2486442060534681,0.6918703627543807,0.12113028023178381 +Computers,0.004244718832652609,0.08101471595230561,0.044049136492570556,0.0 +CricketX,0.2672167254394314,0.3075359290062403,0.3782370352871587,0.02132693078701479 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+EOGVerticalSignal,0.30733972067760573,0.21556727114569182,0.42258252359454995,0.03827284922326574 +Earthquakes,0.06098846324137817,0.1130396908305876,0.07023915050861004,0.0 +ElectricDevices,0.29825574675213984,0.2630356761187243,0.39205278331521565,0.0 +EthanolLevel,0.005364241869609312,0.009807773461393393,0.00452337254494207,0.007673170848819072 +FaceAll,0.7189011013868107,0.4312164847326213,0.5449943539898428,0.0 +FaceFour,0.5774855020612972,0.5188202426564844,0.3483563954493416,0.0 +FacesUCR,0.7297507927370286,0.44691466355299253,0.5468221334987579,0.07801434485504966 +FiftyWords,0.7365478888590046,0.581529080461152,0.6970627692282895,0.08037727690762408 +Fish,0.38362218253481684,0.4026835634008696,0.41425422843985843,0.0 +FordA,0.021506632140750315,0.002548551946519496,0.0007230358321463966,0.008224415106703005 +FordB,0.000689622885847421,9.877527688947378e-05,0.0033147969630888422,0.0006846888152465504 +FreezerRegularTrain,0.21176077865580115,0.11855840510452967,0.19310847318450947,0.9891215850540395 +FreezerSmallTrain,0.20790201438350228,0.13916266650908585,0.18035862185168072,0.0942023475972956 +GunPoint,0.0011106438333565868,0.24336868374143203,0.00047704114409563445,0.0 +GunPointAgeSpan,0.05806753757416144,0.6618623622780222,0.05852350996301143,0.33763361649249807 +GunPointMaleVersusFemale,0.5614631910034454,0.0085529296816148,0.5544867158864274,0.0060997222675514455 +GunPointOldVersusYoung,0.0040822452843238795,0.015011772901622419,0.01803292698850128,0.07465504754615211 +Ham,0.061431206724673316,0.0722344488699316,0.012863515844733178,0.05753817697956109 +HandOutlines,0.07477309858390056,0.08046143848766021,0.04194622442428473,0.0 +Haptics,0.10978682652494437,0.08562213305799796,0.04863841763371516,0.0 +Herring,0.04406145569523074,0.00010457804391447243,0.023061270077197042,0.010711604646834051 +HouseTwenty,0.4361549719235438,0.2914803415187233,0.6455585788140764,0.0 +InlineSkate,0.07102122073937205,0.11305601167575387,0.11592678629143724,0.0 +InsectEPGRegularTrain,0.3106416571888718,0.2658413786326411,0.14893505199525897,0.0 +InsectEPGSmallTrain,0.31747248367382674,0.318456178109987,0.24903391351629706,0.007912981466980966 +InsectWingbeatSound,0.5403472534980323,0.302695891216807,0.15645488512337108,0.2528992144106459 +ItalyPowerDemand,0.4468814406309945,0.00016459296656378192,0.006761479169359651,0.026884647924423227 +LargeKitchenAppliances,0.09840345369041449,0.013626229956479285,0.20944420859687868,0.0 +Lightning2,0.06782178820853738,0.0034536167101423864,0.21445598449782088,0.0 +Lightning7,0.4754432918697631,0.4443066465138467,0.5900683293924749,0.0 +Mallat,0.9048942568119032,0.5410604340957619,0.7371550982054919,0.18388882617496072 +Meat,0.4114873024772571,0.7336804366512109,0.5729935158609982,0.7336804366512109 +MedicalImages,0.24504856579572287,0.27215832649812943,0.313563113759933,0.14155008145578848 +MiddlePhalanxOutlineAgeGroup,0.13554099364822386,0.052082029503080204,0.049910207419776934,0.00718463360905174 +MiddlePhalanxOutlineCorrect,0.03711507385257839,0.056036399781530404,0.06501520140838894,0.0 +MiddlePhalanxTW,0.4088498834780239,0.42028259992486017,0.4177554929837624,0.1337651766634635 +MixedShapesRegularTrain,0.44903734215981317,0.30214236585397825,0.4863424732049395,0.0 +MixedShapesSmallTrain,0.4273450994016538,0.32059425071339465,0.30416629065968176,0.0 +MoteStrain,0.003334120178006842,0.3577534016796463,0.42637539785866424,0.006972532927766628 +NonInvasiveFetalECGThorax1,0.7516796733400711,0.6572446457289886,0.5378623205711236,0.3076561526536364 +NonInvasiveFetalECGThorax2,0.8082450437131323,0.6570298804486683,0.6370306202452239,0.27729364932902134 +OSULeaf,0.31856515275785247,0.4101510665436601,0.15735899681382964,0.02994899624356877 +OliveOil,0.5017911395562238,0.4946258601256751,0.3545894229827754,0.0 +PhalangesOutlinesCorrect,0.02919306364315016,0.051064689075006345,0.018033246177654248,0.0 +Phoneme,0.2944438286531319,0.2465559977873467,0.27561185611902456,0.053098939260638946 +PigAirwayPressure,0.6134703603190136,0.5933298160066958,0.6196060636876288,0.07924795143446917 +PigArtPressure,0.7227054911815867,0.7124766103125033,0.6635810414117448,0.35003896872795676 +PigCVP,0.652434587555941,0.6641795370453003,0.60934717536746,0.27200129480856 +Plane,0.9046416320159155,0.8434426109815282,0.812830455719783,0.5963623209604334 +PowerCons,0.2193360026194249,0.11951506814498275,0.16729761082649972,0.005429512345119535 +ProximalPhalanxOutlineAgeGroup,0.484880282470616,0.5617482888073476,0.37831611254629366,0.03575726847153746 +ProximalPhalanxOutlineCorrect,0.15013457305544223,0.13185905605676732,0.15451908129603698,0.06566193634511393 +ProximalPhalanxTW,0.5748279770856435,0.5527574372676257,0.5690444069535052,0.07570845810828052 +RefrigerationDevices,0.11396065595987526,0.03647796461698172,0.17375482488255428,0.0 +Rock,0.34137134687520315,0.22571905434074435,0.2678027057873534,0.0 +ScreenType,0.022092274157776086,0.03180770756112695,0.02860888812308172,0.0 +SemgHandGenderCh2,0.008341370689991728,0.027527846819655324,0.06899160746084512,0.0 +SemgHandMovementCh2,0.17539685382949957,0.14051202174130928,0.14840586484709808,0.01762844139304975 +SemgHandSubjectCh2,0.25998515993265336,0.23080857020463008,0.1990647546964342,0.04588591686784335 +ShapeletSim,0.0022736783907421404,0.739582623217314,0.002531976374271324,0.0 +ShapesAll,0.7400989721931078,0.6615190790502489,0.6997205438120613,0.10328119459164864 +SmallKitchenAppliances,0.15052545390109703,0.16088431620674928,0.2822053354858329,0.0 +SmoothSubspace,0.3630312432347497,0.22746284025898675,0.2713312864972497,0.002413766516710172 +SonyAIBORobotSurface1,0.08289352369495208,0.5530232394105472,0.06157735843145992,0.0 +SonyAIBORobotSurface2,0.2105022428756164,0.3954370721051784,0.05636526398639544,0.0 +StarLightCurves,0.6034598032954775,0.5483181466845939,0.627583798986545,0.013776415849996575 +Strawberry,0.11637097596008786,0.06947552474878708,0.0666806335986036,0.028461957281282545 +SwedishLeaf,0.6498379987234825,0.5634680293922298,0.5436712945402896,0.0671467628583119 +Symbols,0.8433554400133222,0.8048884669487106,0.7700203691103272,0.4061169092041406 +SyntheticControl,0.8160728397736438,0.8174263873158917,0.836407748247438,0.4530303377656806 +ToeSegmentation1,0.028211621071287114,0.0188851627608643,0.0421323784527198,0.27900643098305383 +ToeSegmentation2,0.2666562095954819,0.0907387461882999,0.17914018941955343,0.0 +Trace,0.5213885129142292,0.6867824620690156,0.8694925429995577,0.8694925429995577 +TwoLeadECG,0.125064594051529,0.00035226227781697596,0.04240638320602735,0.01598876036314365 +TwoPatterns,0.059598544671983805,0.34365103629577504,0.6609866159074433,0.0074353513378347 +UMD,0.20127313632230223,0.4581602979289466,0.48769521257562065,0.026378269927410082 +UWaveGestureLibraryAll,0.637315498123645,0.2564611766382776,0.3961947433213974,0.0 +UWaveGestureLibraryX,0.4583034849870913,0.39948201481188245,0.43168506483933394,0.0 +UWaveGestureLibraryY,0.401723816749617,0.3541457167169236,0.38818220943986326,0.0 +UWaveGestureLibraryZ,0.46110686872146855,0.32970821017686924,0.36905747448936804,0.0 +Wafer,0.00023660500417862622,0.0003678854846115293,1.9920250373583474e-07,0.0018920833289944369 +Wine,0.0,0.000997171222586786,0.08844954733586786,0.0 +WordSynonyms,0.4668754715146259,0.35610638823351787,0.5073974218116808,0.05709265334454846 +Worms,0.23423632635302075,0.3675466997742935,0.18238709486704807,0.0 +WormsTwoClass,0.03923814647078223,0.013336013991068556,0.00036997175518007724,0.0 +Yoga,0.002180530986216767,0.003931212045441256,0.0004074505691311001,9.333026449951936e-06