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1. Simulation_paper---Effect_of_missing_data_on_K-means_performance---MATH60603A_STATISTICAL_LEARNING Simulation_paper---Effect_of_missing_data_on_K-means_performance---MATH60603A_STATISTICAL_LEARNING Public

   K-means clustering is a popular method for categorizing data into clusters based on similarity. Its efficacy can be influenced by various factors, one of which could be missing data. Understanding …

2. PCA_explainability_Paper---MATH60629A_MACHINE_LEARNING_I PCA_explainability_Paper---MATH60629A_MACHINE_LEARNING_I Public

   This project aims to enhance the interpretability of Principal Component Analysis (PCA) by integrating explainability tools and advanced dimensionality reduction techniques such as UMAP or t-SNE.

   Jupyter Notebook

3. Executive_report-Profile_clustering_for_a_fundraising_association-MATH60603A_STATISTICAL_LEARNING Executive_report-Profile_clustering_for_a_fundraising_association-MATH60603A_STATISTICAL_LEARNING Public

   This repository contains the research and analysis exploring the impact of online engagement on charitable donations of a fake association, focusing on how digital interactions through emails and s…

4. Executive_report---Analysis_Of_Factor_Influencing_Trip_Duration_And_Revenue_From_Bixi_Data Executive_report---Analysis_Of_Factor_Influencing_Trip_Duration_And_Revenue_From_Bixi_Data Public

   This repository contains the code and reports for the statistical analysis of BIXI Montreal's bike-sharing system data. The analysis focuses on understanding the factors that influence trip duratio…