Techniques For Feature Selection
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Updated
Dec 1, 2020 - Jupyter Notebook
Techniques For Feature Selection
Customer Segmentation using KMeans Clustering with PCA for dimensionality reduction and Variance Thresholding for feature selection
Praktikum Machine Learning 5 - Naive Bayes dengan Variance Thresholding, Mutual Information, dan K-Fold Cross ValidationAssignment
Delved into advanced techniques to enhance ML performance during the uOttawa 2023 ML course. This repository offers Python implementations of Naïve Bayes (NB) and K-Nearest Neighbor (KNN) classifiers on the MCS dataset.
This project is to build a model that *predicts the human activities* such as __Walking, Walking_Upstairs, Walking_Downstairs, Sitting, Standing__ and __Laying__ as done in Smart-Watches.
Predicting toxicity of molecules. Project on course "Data Mining 2"
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