zoofs is a python library for performing feature selection using a variety of nature-inspired wrapper algorithms. The algorithms range from swarm-intelligence to physics-based to Evolutionary. It's easy to use , flexible and powerful tool to reduce your feature size.

Feature Selection using Metaheuristics Made Easy: Open Source MAFESE Library in Python

Contains a wide-ranging collection of compressed sensing and feature selection algorithms. Examples include matching pursuit algorithms, forward and backward stepwise regression, sparse Bayesian learning, and basis pursuit.

Learning with Subset Stacking

Machine learning library for classification tasks

Machine learning library for classification tasks

Efficient Variable Selection for GLMs in R

Machine learning library for classification tasks

Official implementation of the paper "Most Influential Subset Selection: Challenges, Promises, and Beyond" (NeurIPS2024)

PySpark Implementation of the ProtoDash subset selection algorithm.

Generalized Improved Second Order RBF Neural Network with Center Selection using OLS

Official implementation of PPSN'24 paper "Biased Pareto Optimization for Subset Selection with Dynamic Cost Constraints"

This project is on Data Mining process using R depending on ISLR book.

Find the simplest model and the best method to predict whether an observation belongs to categories LOWER/GREATER of 20% trimmed mean of "ncrim" variable. AUEB Computer Science course Statistical Learning.

Reproducing, then improving MiniPile with PyTorch and HuggingFace

A Laravel collection-powered PHP package, enables efficient extraction of subsets from collections, ideal for discount calculations and inventory management.

A Python package for flexible subset selection for data visualization.

This aims to run a subset selection process on the data set using R

Group fairness auditing methods for set selections. Corresponding to paper "FINS Auditing Framework: Group Fairness for Subset Selections" AAAI/ACM AIES 2022

Neighbourhood Functions for Local-Search Algorithms

R package of the Approximate Best Subset Maximum Binary Prediction Rule (PRESCIENCE) proposed by Chen and Lee (2018).

[JASA] Reconstruct Ising Model with Global Optimality via SLIDE

In this project, I have used Machine Learning (Linear Regression) for Prediction of fare and changes in airfare when a low cost airlines like Southwest Airline enters a new route in the US Aviation Market.

Machine learning library for classification tasks

Machine learning library for classification tasks

QReadSelector is a subset selection of high-depth next generation sequencing reads for de novo genome assembly using MapReduce framework.

Using 2016 MLB data, using Subset Selection approach to identify a subset of p predictors that are related to the salary variable..

Machine learning project using linear regression to analyze car data in Canada for CO2 emission prediction.

Data Analytics and Machine Learning in R. Linear-regression, Logistic-regression, Hierarchical-clustering, Boosting, Bagging, Random-forests, K-means-clustering, K-nearest-neighbors (K-N-N), Tree-pruning, Subset-selection, LDA, QDA, Support Vector Machines (SVM)

Fast Backward Elimination in R