ren-algorithm 0.1.2

A collection of machine learning algorithms

ML_algorithms

A collection of machine learning algorithms implemented in Python. This package includes implementations for various supervised learning models such as XGBoost, Decision Trees, Random Forest, K-Nearest Neighbors (KNN), and Linear SVM, Linear regression, Logistics Regression . Each algorithm is organized in its own module for easy use and experimentation.

Features

• XGBoost Regressor: Implementation of XGBoost regression with helper functions for model building.
• Decision Trees: Code for constructing decision trees used by various algorithms.
• Random Forest Regressor: Ensemble method combining multiple decision trees for robust predictions.
• K-Nearest Neighbors (KNN): A simple and effective algorithm for classification and regression.
• Linear SVM: Linear Support Vector Machine implementation for classification tasks.
• Linear Regression: implements sinmple and multivariate linear regression algorithm.
• Logistic Regression: implements logistics regression.

Installation

Install the package directly from PyPI using pip:

pip install ren_algorithm