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This toolbox offers 13 wrapper feature selection methods (PSO, GA, GWO, HHO, BA, WOA, and etc.) with examples. It is simple and easy to implement.
This toolbox offers more than 40 wrapper feature selection methods include PSO, GA, DE, ACO, GSA, and etc. They are simple and easy to implement.
This toolbox offers advanced feature selection tools. Several modifications, variants, enhancements, or improvements of algorithms such as GWO, FPA, SCA, PSO and SSA are provided.
Application of Whale Optimization Algorithm (WOA) in the feature selection tasks.
Joint Task Offloading and Radio Resource Management in Stochastic MEC Systems, IEEE Transactions on Communications, 2024
IntelELM: A Python Framework for Intelligent Metaheuristic-based Extreme Learning Machine
MetaCluster: An Open-Source Python Library for Metaheuristic-based Clustering Problems
EO-CNN: An Enhanced CNN Model Trained by Equilibrium Optimization for Traffic Transportation Prediction
MetaPerceptron: A Standardized Framework For Metaheuristic-Driven Multi-layer Perceptron Optimization
reflame: Revolutionizing Functional Link Neural Network by Metaheuristic Optimization
EvoRBF: A Nature-inspired Algorithmic Framework for Evolving Radial Basis Function Networks
MNSWOA: A nondominated-sorting-based whale optimization algorithm for feature selection.
GrafoRVFL: A Gradient-Free Optimization Framework for Boosting Random Vector Functional Link Network
Python3 framework for comparative study of recent metaheuristics
simple implementation of portfolio optimization using WOA
simple WOA (Whale Optimization Algorithm) implementation
Interpretation of Black-Box Model with Counterfactual with Whale optimization and Genetic Algorithm
Melanoma Image Classification using ANN, Whale Optimization Algorithm, and Digital Image Processing
Parallel WOAmM is a GPU implementation of the WOAmM metaheuristic optimization algorithm in CUDA.
Project for a 4 months internship