-
Notifications
You must be signed in to change notification settings - Fork 226
Commit
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
feat: add new gmm based synth for fast synthesis (#269)
* feat: Add new GMM model for fast synthesis * feat: add save and load for new model * fix: synthesis base class * fix: linter * fix: linter warnings
- Loading branch information
Showing
17 changed files
with
415 additions
and
36 deletions.
There are no files selected for viewing
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
203 changes: 203 additions & 0 deletions
203
examples/regular/models/Fast_Adult_Census_Income_Data.ipynb
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,203 @@ | ||
| { | ||
| "nbformat": 4, | ||
| "nbformat_minor": 0, | ||
| "metadata": { | ||
| "colab": { | ||
| "provenance": [] | ||
| }, | ||
| "kernelspec": { | ||
| "name": "python3", | ||
| "display_name": "Python 3" | ||
| }, | ||
| "language_info": { | ||
| "name": "python" | ||
| }, | ||
| "accelerator": "GPU", | ||
| "gpuClass": "standard" | ||
| }, | ||
| "cells": [ | ||
| { | ||
| "cell_type": "code", | ||
| "source": [ | ||
| "#Uncomment to install ydata-synthetic lib\n", | ||
| "#!pip install ydata-synthetic" | ||
| ], | ||
| "metadata": { | ||
| "id": "fwXSWiYu_tl0", | ||
| "pycharm": { | ||
| "name": "#%%\n" | ||
| } | ||
| }, | ||
| "execution_count": null, | ||
| "outputs": [] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "source": [ | ||
| "# Tabular Synthetic Data Generation with Gaussian Mixture\n", | ||
| "- This notebook is an example of how to use a synthetic data generation methods based on [GMM](https://scikit-learn.org/stable/modules/generated/sklearn.mixture.GaussianMixture.html) to generate synthetic tabular data with numeric and categorical features.\n", | ||
| "\n", | ||
| "## Dataset\n", | ||
| "- The data used is the [Adult Census Income](https://www.kaggle.com/datasets/uciml/adult-census-income) which we will fecth by importing the `pmlb` library (a wrapper for the Penn Machine Learning Benchmark data repository).\n" | ||
| ], | ||
| "metadata": { | ||
| "id": "6T8gjToi_yKA", | ||
| "pycharm": { | ||
| "name": "#%% md\n" | ||
| } | ||
| } | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "source": [ | ||
| "from pmlb import fetch_data\n", | ||
| "\n", | ||
| "from ydata_synthetic.synthesizers.regular import RegularSynthesizer\n", | ||
| "from ydata_synthetic.synthesizers import ModelParameters, TrainParameters" | ||
| ], | ||
| "metadata": { | ||
| "id": "Ix4gZ9iSCVZI", | ||
| "pycharm": { | ||
| "name": "#%%\n" | ||
| } | ||
| }, | ||
| "execution_count": null, | ||
| "outputs": [] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "source": [ | ||
| "## Load the data" | ||
| ], | ||
| "metadata": { | ||
| "id": "I0qyPwoECZ5x", | ||
| "pycharm": { | ||
| "name": "#%% md\n" | ||
| } | ||
| } | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "source": [ | ||
| "# Load data\n", | ||
| "data = fetch_data('adult')\n", | ||
| "num_cols = ['age', 'fnlwgt', 'capital-gain', 'capital-loss', 'hours-per-week']\n", | ||
| "cat_cols = ['workclass','education', 'education-num', 'marital-status', 'occupation', 'relationship', 'race', 'sex',\n", | ||
| " 'native-country', 'target']" | ||
| ], | ||
| "metadata": { | ||
| "id": "YeFPnJVOMVqd", | ||
| "pycharm": { | ||
| "name": "#%%\n" | ||
| } | ||
| }, | ||
| "execution_count": 2, | ||
| "outputs": [] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "source": [ | ||
| "## Create and Train the synthetic data generator" | ||
| ], | ||
| "metadata": { | ||
| "id": "68MoepO0Cpx6", | ||
| "pycharm": { | ||
| "name": "#%% md\n" | ||
| } | ||
| } | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "source": [ | ||
| "synth = RegularSynthesizer(modelname='fast')\n", | ||
| "synth.fit(data=data, num_cols=num_cols, cat_cols=cat_cols)" | ||
| ], | ||
| "metadata": { | ||
| "id": "oIHMVgSZMg8_", | ||
| "pycharm": { | ||
| "name": "#%%\n" | ||
| } | ||
| }, | ||
| "execution_count": null, | ||
| "outputs": [] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "source": [ | ||
| "## Generate new synthetic data" | ||
| ], | ||
| "metadata": { | ||
| "id": "xHK-SRPyDUin", | ||
| "pycharm": { | ||
| "name": "#%% md\n" | ||
| } | ||
| } | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "source": [ | ||
| "synth_data = synth.sample(1000)\n", | ||
| "print(synth_data)" | ||
| ], | ||
| "metadata": { | ||
| "id": "0aa2g0RLMkqe", | ||
| "colab": { | ||
| "base_uri": "https://localhost:8080/" | ||
| }, | ||
| "outputId": "01808aa4-a700-4385-e7df-b2f7abd162a0", | ||
| "pycharm": { | ||
| "name": "#%%\n" | ||
| } | ||
| }, | ||
| "execution_count": 8, | ||
| "outputs": [ | ||
| { | ||
| "output_type": "stream", | ||
| "name": "stdout", | ||
| "text": [ | ||
| " age workclass fnlwgt education education-num \\\n", | ||
| "0 38.753654 4 179993.565472 8 10.0 \n", | ||
| "1 36.408844 4 245841.807958 9 10.0 \n", | ||
| "2 56.251066 4 400895.076058 11 13.0 \n", | ||
| "3 26.846605 4 240156.201048 11 10.0 \n", | ||
| "4 29.083102 1 5601.059126 11 9.0 \n", | ||
| ".. ... ... ... ... ... \n", | ||
| "995 79.281276 4 30664.183560 1 10.0 \n", | ||
| "996 51.423132 4 414524.980527 1 10.0 \n", | ||
| "997 17.342915 6 177716.451926 11 13.0 \n", | ||
| "998 39.298867 4 132011.369567 15 12.0 \n", | ||
| "999 46.977763 2 92662.371635 9 13.0 \n", | ||
| "\n", | ||
| " marital-status occupation relationship race sex capital-gain \\\n", | ||
| "0 4 0 3 4 0 55.771499 \n", | ||
| "1 6 7 0 4 1 124.337939 \n", | ||
| "2 4 3 3 4 1 27.968087 \n", | ||
| "3 4 6 1 4 0 25.065678 \n", | ||
| "4 6 3 0 4 0 126.269337 \n", | ||
| ".. ... ... ... ... ... ... \n", | ||
| "995 2 0 3 4 1 4.393001 \n", | ||
| "996 4 7 3 2 0 54.841598 \n", | ||
| "997 4 4 4 4 0 99.394428 \n", | ||
| "998 4 14 1 4 1 97.834797 \n", | ||
| "999 4 8 1 4 0 51.258308 \n", | ||
| "\n", | ||
| " capital-loss hours-per-week native-country target \n", | ||
| "0 -1.271118 39.749641 39 1 \n", | ||
| "1 -2.114950 44.488198 39 1 \n", | ||
| "2 1.541738 40.042696 39 1 \n", | ||
| "3 1.148560 39.952615 39 1 \n", | ||
| "4 -1.786768 39.808085 39 0 \n", | ||
| ".. ... ... ... ... \n", | ||
| "995 0.224015 50.580637 39 1 \n", | ||
| "996 1.319341 4.441194 39 1 \n", | ||
| "997 -5.231663 39.779674 39 1 \n", | ||
| "998 1.595817 39.731359 13 1 \n", | ||
| "999 1.129814 39.838415 39 1 \n", | ||
| "\n", | ||
| "[1000 rows x 15 columns]\n" | ||
| ] | ||
| } | ||
| ] | ||
| } | ||
| ] | ||
| } |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,7 @@ | ||
| from ydata_synthetic.preprocessing.regular.processor import RegularDataProcessor | ||
| from ydata_synthetic.preprocessing.timeseries.timeseries_processor import TimeSeriesDataProcessor | ||
|
|
||
| __all__ = [ | ||
| "RegularDataProcessor", | ||
| "TimeSeriesDataProcessor" | ||
| ] |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1 +1,6 @@ | ||
| from ydata_synthetic.synthesizers.gan import ModelParameters, TrainParameters | ||
| from ydata_synthetic.synthesizers.base import ModelParameters, TrainParameters | ||
|
|
||
| __all__ = [ | ||
| "ModelParameters", | ||
| "TrainParameters" | ||
| ] |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Oops, something went wrong.