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This repository contains implementations of Decision Tree, Logistic Regression, and Naïve Bayes models applied to the Iris and MTCars datasets. It explores classification and regression tasks, hyperparameter tuning, and performance evaluation using accuracy and RMSE, with visualizations for model... Read more

Decision Tree Implementation from Scratch

Package implements decision tree and isolation forest

Implementation of Grid Search to find better hyper-parameters for decision tree to reduce the over fitting.

Implementation of the ID3 to create a decision tree in C#. Also available import/export of training data and printing the tree

Julia implementation of Modal Decision Trees & Forests, for interpretable classification of spatial and temporal data. Long live Symbolic Learning!!

Decision Tree implementation from scratch using Golang

A Python implementation of decision trees, compatible with sklearn.

In this project, I used Decision Tree Learning Model as the main algorithm to build the model. Due to the big amount of flight data, we implement the project using MRJob, PySpark and Spark's MLlib then compare the performance and accuracy of those implementations.

This project implements a Decision Tree Classifier to predict different leaf species based on features like sepal length, sepal width, petal length, and petal width. The dataset used is similar to the Iris dataset, and the model is trained using Scikit-learn.