Jingwei Too

Last seen: circa un anno fa | Attivo dal 2019

Followers: 6 Following: 0

Professional Interests: Feature Selection, Metaheuristics, Machine Learning, Data Mining, and Signal Processing

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Whale Optimization Algorithm for Feature Selection
Application of Whale Optimization Algorithm (WOA) in the feature selection tasks.

oltre 3 anni fa | 8 download |

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Binary Grey Wolf Optimization for Feature Selection
Demonstration on how binary grey wolf optimization (BGWO) applied in the feature selection task.

oltre 3 anni fa | 10 download |

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Wrapper Feature Selection Toolbox
This toolbox offers more than 40 wrapper feature selection methods include PSO, GA, DE, ACO, GSA, and etc.

oltre 3 anni fa | 13 download |

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Salp Swarm Algorithm for Feature Selection
Application of Salp Swarm Algorithm (SSA) in the feature selection tasks.

quasi 4 anni fa | 2 download |

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Equilibrium Optimizer for Feature Selection
Application of Equilibrium Optimizer (EO) in the feature selection tasks.

quasi 4 anni fa | 3 download |

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Binary Dragonfly Algorithm for Feature Selection
Application of Binary Dragonfly Algorithm (BDA) in the feature selection tasks.

quasi 4 anni fa | 1 download |

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Ant Colony Optimization for Feature Selection
Implantation of ant colony optimization (ACO) without predetermined number of selected features in feature selection tasks.

quasi 4 anni fa | 2 download |

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Sine Cosine Algorithm for Feature Selection
Application of Sine Cosine Algorithm (SCA) in the feature selection tasks.

quasi 4 anni fa | 4 download |

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Henry Gas Solubility Optimization for Feature Selection
Application of Henry Gas Solubility Optimization (HGSO) in the feature selection tasks.

quasi 4 anni fa | 4 download |

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Particle Swarm Optimization for Feature Selection
Application of Particle Swarm Optimization (PSO) in the feature selection tasks.

quasi 4 anni fa | 4 download |

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Dimensionality Reduction Demonstration
Application of principal component analysis (PCA) for feature reduction.

quasi 4 anni fa | 3 download |

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Filter Feature Selection Toolbox
Simple, fast and ease of implementation. The filter feature selection methods include Relief-F, PCC, TV, and NCA.

quasi 4 anni fa | 9 download |

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Deep Learning Toolbox
This toolbox offers convolution neural networks (CNN) using k-fold cross-validation, which are simple and easy to implement.

quasi 4 anni fa | 13 download |

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Neural Network Toolbox
This toolbox contains 6 types of neural networks, which is simple and easy to implement.

quasi 4 anni fa | 4 download |

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Ant Colony System for Feature Selection
Application of ant colony system (ACS) for feature selection problems.

quasi 4 anni fa | 2 download |

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Binary Differential Evolution for Feature Selection
The binary version of Differential Evolution (DE), named as Binary Differential Evolution (BDE) is applied for feature selection...

quasi 4 anni fa | 7 download |

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Binary Tree Growth Algorithm for Feature Selection
A feature selection algorithm, named as Binary Tree Growth Algorithm (BTGA) is applied for feature selection tasks.

quasi 4 anni fa | 2 download |

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Atom Search Optimization for Feature Selection
Application of Atom Search Optimization (ASO) in the feature selection tasks.

quasi 4 anni fa | 1 download |

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Binary Particle Swarm Optimization for Feature Selection
Simple algorithm shows how binary particle swarm optimization (BPSO) used in feature selection problem.

quasi 4 anni fa | 8 download |

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Binary Harris Hawk Optimization for Feature Selection
The binary version of Harris Hawk Optimization (HHO), called Binary Harris Hawk Optimization (BHHO) is applied for feature selec...

quasi 4 anni fa | 6 download |

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Genetic Algorithm for Feature Selection
Simple algorithm shows how the genetic algorithm (GA) used in the feature selection problem.

quasi 4 anni fa | 4 download |

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Binary Atom Search Optimization for Feature Selection
A new feature selection algorithm, named as Binary Atom Search Optimization (BASO) is applied for feature selection tasks.

quasi 4 anni fa | 3 download |

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Machine Learning Toolbox
This toolbox offers 8 machine learning methods including KNN, SVM, DA, DT, NB, and etc., which are simpler and easy to implement...

quasi 4 anni fa | 41 download |

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EMG Feature Extraction Toolbox
This toolbox offers 40 feature extraction methods (EMAV, EWL, MAV, WL, SSC, ZC, and etc.) for Electromyography (EMG) signals app...

quasi 4 anni fa | 37 download |

Inviato

EEG Feature Extraction Toolbox
This toolbox offers 30 types of EEG feature extraction methods (HA, HM, HC, and etc.) for Electroencephalogram (EEG) application...

quasi 4 anni fa | 40 download |

Risposto
Can anyone tell me how to solve this error?
Why don't you try on this toolbox https://www.mathworks.com/matlabcentral/fileexchange/71461-simple-machine-learning-algorithms-...

oltre 4 anni fa | 0

Risposto
Eyes closed and Open EEG data predict?
Let say you have 10 participants, and 38 channels. You extract one feature (alpha power) from each participant. Then your featur...

oltre 4 anni fa | 1

Risposto
what can I do to implement the features like Mean Absolute Value and variance using their given definition per channel or formula for a given signal in order to generate a feature vector?
you may have a look on this toolbox https://www.mathworks.com/matlabcentral/fileexchange/71514-emg-feature-extraction-toolbox?s_...

oltre 4 anni fa | 0

Risposto
Eyes closed and Open EEG data predict?
You may follow these step (1) Extract the features from the EEG signals (for both eye closed and open) (2) You may perform the...

oltre 4 anni fa | 0

| accettato

Risposto
How to use ReliefF algorithm for a dataset?
you may have a look on this toolbox https://www.mathworks.com/matlabcentral/fileexchange/71611-simple-filter-feature-selection-a...

oltre 4 anni fa | 0

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