c++ incremental decision tree

The code of AAAI20 paper "Efficient Inference of Optimal Decision Trees"

Machine learning library for classification tasks

Pope is a bot created to play a simplified version of the game "Papers, Please". The name of this AI was given in honor of the game creator Lucas Pope.

Decision Tree Classifier and Boosted Random Forest

Cpp implementation of the decision tree classifier discussed here (https://engineering.purdue.edu/kak/Tutorials/DecisionTreeClassifiers.pdf)

Methods for increasing generalization ability based on different ways of ensembles building

Random Forest library university project

Decision Tree and Perceptron performance comparison through a small dataset

A library to train, evaluate and make inference using random forests.

Deploys an optimized Decision Tree for Arrhythmia classification using Chapman ECG dataset on Arduino UNO board

Deploys an optimized Decision Tree for Arrhythmia classification using Chapman ECG dataset on ESP32-S3 dev kit

This repository provides a C++ implementation for managing missing clinical data using KNN Imputation and building a Decision Tree Classifier. The code allows for estimation of missing values from a dataset and construction of a classifier to categorize subjects as positive or negative cases, based on their clinical features.

Deploys a vanilla Decision Tree for Arrhythmia classification using Chapman ECG dataset on Arduino UNO board

Decision_tree module for C++ and Python