knn-imputation

Here are 8 public repositories matching this topic...

miriamspsantos / heterogeneous-distance-functions

A collection of heterogeneous distance functions handling missing values.

machine-learning missing-data distance-measures knn research-paper distance-functions heterogeneous-data missing-values heom hvdm knn-imputer knn-imputation

Updated Jan 24, 2022
MATLAB

ieee-sun / interpolation

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Interpolation for Missing Data

knn linear-interpolation interpolation-methods trend-analysis spline-interpolation polynomial-interpolation seasonal-time-series knn-imputation seasonal-trend-decomposition

Updated Jun 13, 2024
HTML

Kamal-Shirupa / Solar-Power-Forecasting

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This project predicts solar panel energy output based on weather conditions and irradiance levels using a hybrid model of Gradient Boosting and LSTM .

machine-learning deep-learning lstm pca-analysis gradient-boosting shap-values knn-imputation

Updated Mar 30, 2025

sandipanpaul21 / KNN-Naive-Bayes-SVM-in-Python

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ML Topics include KNN. Naive Bayes and Support vectors both in Theory and Python Code. KNN Imputation technique is also explained in this branch.

naive-bayes-classifier support-vector-machine knn-classification support-vector-regression bayes-theorem support-vector-classification support-vector knn-imputation

Updated Dec 16, 2021
Jupyter Notebook

vahadruya / Capstone_Classification_Cardiovascular_Risk_Prediction

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This project explores the Framingham Heart disease dataset with the objective to predict its risk in 10 years. Various methods for handling missing values and outliers are explored as iterations. After analysing the dataset, important and necessary features are selected. Seven ML models are implemented, with evaluation on the basis of Test Recall.

python sklearn pandas t-test classification trimming decision-trees smote random-forest-classifier knn-classifier shap heart-disease-prediction xgboost-classifier recall-score chi-squared-test knn-imputation winsorization shapiro regression-imputation

Updated Apr 7, 2023
Jupyter Notebook

MOHD-AFROZ-ALI / Customer-Segmentation-on-Credit-Details

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Customer Segmentation with Credit Insights helps businesses personalize marketing and boost retention by analyzing credit card usage patterns. Using K-Means, DBSCAN, and PCA, it identifies meaningful customer segments from high-dimensional transaction data.

credit-card eda business-intelligence pca-analysis segmentation schema-validation kmeans-clustering dbscan-clustering business-service knn-imputation