The biggest module developed with complete focus on Feature Selection (FS) using Meta-Heuristic Algorithm / Nature-inspired evolutionary / Swarm-based computing.

MetaCluster: An Open-Source Python Library for Metaheuristic-based Clustering Problems

Meta-Heuristic Algorithm for Travelling Salesman Problem

EvoRBF: Evolving Radial Basis Function Network by Intelligent Nature-inspired Algorithms

Text classification with Machine Learning and Mealpy

Hyper-parameter tuning of classification model with Mealpy

Hyper-parameter tuning of Time series forecasting models with Mealpy

Proposing a novel approach on using Naives Bayes by using Robust Kernel Density Estimation (RKDE) and optimising the bandwith(h) with Harris Hawks Optimization (HHO)

BIO-ANFIS: A Bio-inspired Optimization Framework for Improving ANFIS Networks

GrafoRVFL: A Gradient-Free Optimization Framework for Boosting Random Vector Functional Link Network

Explore EMS for predicting Building Energy Consumption using Stacked Ensemble with Heap-Based Optimization (HBO). This innovative approach leverages corporate hierarchy insights to optimize model parameters and boost accuracy. See significant performance improvements compared to traditional methods.

Solutions for Labs of Nature Inspired Computing course offered at Innopolis University