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This repository contains Python scripts for calculating the Gini Impurity measure for each feature in a relational dataset, great for feature selection, data preprocessing, decision tree construction, binary classification tasks.
The complete Python code for the Attribute Selection Algorithm, using the parameters Entropy, Information gain and Gini Index. The following code will help in induction of the Decision Tree using a custom data set present in CSV format.
A Python-powered ML toolkit featuring a Decision Tree builder and Naive Bayes classifier implemented from scratch. Supports attribute selection using Entropy (ID3) and Gini Index (CART), with custom metric calculations, recursive tree construction, and Graphviz-based visualization for decision boundaries and probabilistic classification.
The objective of this work is to provide tools to be used for the classification of ordinal categorical distributions. To demonstrate how to do it, we propose an Homogeneity (HI) and Location (LI) Index to measure the concentration and central value of an ordinal categorical distribution.
Décorticage les jeux de données commerciale pour faciliter la prise de décision appuyée sur data: sortir les business insights, identifier les anomalies et des opportunités
⚖️ A Reproducible Pipeline for Processing DATASUS Data on the Gini Index of Per Capita Household Income by Brazilian Municipality for the Years 1991, 2000, and 2010
A collection of experiments I have performed for the course "Machine Learning" as part of the curriculum for Semester 6 of TY B. Tech. Computer Engineering at KJ Somaiya College of Engineering.
Udacity Project 1 - Investigate economic, inequality, & corruption data. This project sets out to find a relationship between the fastest-growing countries, corruption, & inequality.
Comparative analysis of political ideologies, polarization, and internal order across 35+ democracies from 1900–2023. Includes ideology scores, Gini-based fragmentation metrics, and Ray Dalio’s framework applied to democratic stability.