This repository contains a reading list of papers on Time Series Segmentation. This repository is still being continuously improved.
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Updated
Sep 3, 2024 - MATLAB
This repository contains a reading list of papers on Time Series Segmentation. This repository is still being continuously improved.
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.
Demonstration on how binary grey wolf optimization (BGWO) applied in the feature selection task.
GNU Octave library for connectivity analysis in large fMRI datasets
Application of Whale Optimization Algorithm (WOA) in the feature selection tasks.
Simple, fast and ease of implementation. The filter feature selection methods include Relief-F, PCC, TV, and NCA.
Feature Selection by Optimized LASSO algorithm
A system to recognize hand gestures by applying feature extraction, feature selection (PCA) and classification (SVM, decision tree, Neural Network) on the raw data captured by the sensors while performing the gestures.
The binary version of Harris Hawk Optimization (HHO), called Binary Harris Hawk Optimization (BHHO) is applied for feature selection tasks.
Implantation of ant colony optimization (ACO) without predetermined number of selected features in feature selection tasks.
The binary version of Differential Evolution (DE), named as Binary Differential Evolution (BDE) is applied for feature selection tasks.
Application of Salp Swarm Algorithm (SSA) in the feature selection tasks.
Application of Sine Cosine Algorithm (SCA) in the feature selection tasks.
Simple algorithm shows how binary particle swarm optimization (BPSO) used in feature selection problem.
Application of Particle Swarm Optimization (PSO) in the feature selection tasks.
Application of Binary Dragonfly Algorithm (BDA) in the feature selection tasks.
Application of Equilibrium Optimizer (EO) in the feature selection tasks.
Application of Henry Gas Solubility Optimization (HGSO) in the feature selection tasks.
Simple algorithm shows how the genetic algorithm (GA) used in the feature selection problem.
Application of Atom Search Optimization (ASO) in the feature selection tasks.
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