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Java Implementation for Multi-Class Decision Tree Machine Learning Algorithm training with large files

A python 3 implementation of decision tree (machine learning classification algorithm) from scratch

Python Implementation of STreeD: Dynamic Programming Approach for Optimal Decision Trees with Separable objectives and Constraints

An implementation of the TREPAN algorithm in python. TREPAN extracts a decision tree from an ANN using a sampling method.

A program to predict the stock market. ML Algorithms: Random Forest, Decision Trees ans also a CNN (TensorFlow) were implemented and their performance compared.

A Java-based implementation of the classic Connect Four game with support for human and AI players. The game features an intuitive GUI, AI decision-making using Monte Carlo Tree Search (MCTS), and winner detection. Perfect for learning game development and AI strategies.

This project implements a method that converts a trained XGBoost classification tree into a single decision tree.

Implementation of the paper End-to-end Learning of Deterministic Decision Trees

This repo is an implementation of the research paper "A Data Mining Approach to Predict Forest Fires using Meteorological Data." by P. Cortez and A. Morais. The algorithms used are : SVR, Decision Trees, Random Forests, Simple Deep Neural Network ( Keras with Tensorflow backend)

An adaboost implementation with decision trees in pure python.