Techniques For Feature Selection
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Updated
Dec 1, 2020 - Jupyter Notebook
Techniques For Feature Selection
Praktikum Machine Learning 5 - Naive Bayes dengan Variance Thresholding, Mutual Information, dan K-Fold Cross ValidationAssignment
Customer Segmentation using KMeans Clustering with PCA for dimensionality reduction and Variance Thresholding for feature selection
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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