Classification of Data Using Decision Tree and Random Forest

Assignments and Project from NJIT CS 675

Decision Tree Classification via CART Algorithm

Udacity Project 1 - Investigate economic, inequality, & corruption data. This project sets out to find a relationship between the fastest-growing countries, corruption, & inequality.

The AdaBoost algorithm is an ensemble learning method that combines multiple weak learners (base estimators) to create a stronger predictive model.

Content: Root node, Decision node & Leaf nodes, Attribute Selection Measure (ASM), Feature Importance (Information Gain), Gini index

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

Fast computation of the Gini coefficient

Contains KNN regression, Linear regression, KNN classification and Decision trees (using gini index, entropy & misclassification rate), all implemented from scratch.

Here are some projects based on static methods of information processing. There are many different methods that you can use to process your information, depending on your needs.

Implemented a Decision Tree from Scratch using binary univariate split, entropy, and information gain. Used Gini index and Pruning for performance improvement.

Supervised and unsupervised analysis

Code created during a Machine Learning class at Columbia University

Using pyhthon with pandas and scikit-learn libraries to split, train, test and check the accuracy of DecisionTree model on top of diabetes dataset

This repository contains ml model for applying decision tree on Iris dataset

A decision tree classification model based on bank marketing data

A decision tree built in python for my 4th year module CA4010, Data Mining

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.

These are coding assignments and projects for the CS 675 Machine Learning course.