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

Hyper-parameter tuning of classification model with Mealpy

Text classification with Machine Learning and 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)

Hyper-parameter tuning of Time series forecasting models with Mealpy

The code and dataset used in the published paper: Smart grid stability prediction using Adaptive Aquila Optimizer and ensemble stacked BiLSTM

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

Meta-Heuristic Algorithm for Travelling Salesman Problem

EvoRBF: A Nature-inspired Algorithmic Framework for Evolving Radial Basis Function Networks

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

X-ANFIS: An Extensible and Cross-Learning ANFIS Framework for Machine Learning Tasks

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