Code repository for the machine learning book Feature Engineering & Selection for Explainable Models: A Second Course for Data Scientists

This repository provides a collection of Jupyter Notebook examples demonstrating various feature selection techniques using Python.

Metaheuristics feature selection library for machine learning feature selection. Genetic Algorithm, Simulated Annealing, Particle Swarm Optimization, and Ant Colony Optimization

Research project utilizing multiple regression to model wOBA for minor league batters

This repository contains functions/codes related to different methods of machine learning for classification and clustering in python.

in this section will be categorical feature selection on breast cancer dataset

High data dimensionality and irrelevant features can negatively impact the performance of machine learning algorithms. This repository implements the Permutation feature importance method to enhance the performance of some machine learning models by identifying the contribution of each feature used.

Dive into feature selection and classification with this Python repository, utilizing a genetic algorithm and various classifiers on a breast cancer dataset. Achieving high accuracy levels, SVM and ANN stand out with 97.37%. Ideal for machine learning enthusiasts and those interested in cancer diagnostics.

in this section, we will be wrapper feature selection on the diabetes dataset

Breast Cancer Prediction with Hybrid Filter-Wrapper Feature Selection

The goal of this project is to build a model that can accurately predict the price of a house based on its features.

This repo contains some projects about artificial intelligence that I made.

Identified the optimal order of preprocessing for Pima Diabetes Dataset, how feature selection and upsampling affects the evaluation metrics

Includes all of my Jupyter Notebook assignments from MIT's Break Through AI/ML Machine Learning Foundations Program.

This is our Machine Learning course project. Predict the user based on its cursor movements.

Data Science project for the diagnosis of psychiatric disorders from neuroimaging data. This is our project for the Data Science competition of the faculty of computer and information science (FRI) from the university of Ljubljana (UL) that I'm one of the contributors.

🟧 Публичный репозиторий работ по курсу