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PyExplainer: A Local Rule-Based Model-Agnostic Technique (Explainable AI)

Evolutionary algorithm toolbox and framework with high performance for Python

Implemented 3 ranking techniques: Fisher Discriminant Ratio (FDR), Signal-Noise Ratio (SNR), Corelation Coefficient (CC). Made different combinations of the above 3 to eliminate low ranked features…

Code metrics for Java code by means of static analysis

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…

Feature selection library in python

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.

A Tree based feature selection tool which combines both the Boruta feature selection algorithm with shapley values.

A python implementation of "Majority Weighted Minority Oversampling Technique for Imbalanced Data Set Learning"

Automated Machine Learning with scikit-learn

Distributed Asynchronous Hyperparameter Optimization in Python

Genetic Algorithm, Particle Swarm Optimization, Simulated Annealing, Ant Colony Optimization Algorithm,Immune Algorithm, Artificial Fish Swarm Algorithm, Differential Evolution and TSP(Traveling sa…

Library for machine learning stacking generalization.

Python implementations of the k-modes and k-prototypes clustering algorithms, for clustering categorical data

A high performance implementation of HDBSCAN clustering.

pyclustering is a Python, C++ data mining library.

Oversampling method based on relative density

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Implementation of "MWMOTE--Majority Weighted Minority Oversampling Technique for Imbalanced Data Set Learning" (https://ieeexplore.ieee.org/document/6361394)