Filter-Feature-Selection-Toolbox

KO | EN

gitlite — search

#python #java #python3 #arduino #golang #machine-learning #rust #html #flask #javascript #seismology #nodejs

Filter-Feature-Selection-Toolbox

★ 24 Open GitHub ↗

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

// repository documentation

Was this content helpful?

★ 0 (0 ratings)

# Jx-FFST : A Filter Feature Selection Toolbox

[![View Filter Feature Selection Toolbox on File Exchange](https://www.mathworks.com/matlabcentral/images/matlab-file-exchange.svg)](https://www.mathworks.com/matlabcentral/fileexchange/71611-filter-feature-selection-toolbox)
[![License](https://img.shields.io/badge/license-BSD_3-yellow.svg)](https://github.com/JingweiToo/Filter-Feature-Selection-Toolbox/blob/master/LICENSE)
[![GitHub release](https://img.shields.io/badge/release-1.1.1-green.svg)](https://github.com/JingweiToo/Filter-Feature-Selection-Toolbox)

---
> "Toward Talent Scientist: Sharing and Learning Together"
>  --- [Jingwei Too](https://jingweitoo.wordpress.com/)
---

![Wheel](https://www.mathworks.com/matlabcentral/mlc-downloads/downloads/f5e02324-3814-410d-b47e-a5f4033497dc/41a6d04b-7f52-46f8-9ee6-64fc5be9caa4/images/screenshot.PNG)

## Introduction

* This toolbox contains 4 filter feature selection methods 
* The `A_Main` file shows the example of how to use these filter feature selection on the benchmark dataset

## Usage
The main function `jffs` is employed to perform feature selection. You may switch the method by changing the `'rf'` to [other abbreviations](/README.md#list-of-available-filter-feature-selection-methods)
* If you wish to use Relief-F ( RF ) then you may write
```code
FS = jffs('rf',feat,label,opts);
```

## Input
* *`feat`*   : feature vector matrix ( Instance *x* Features )
* *`label`*  : label matrix ( Instance *x* 1 )
* *`opts`*   : parameter settings
    + *`Nf`* : number of selected features ( *must be set for all methods* )

## Output
* *`Acc`*  : accuracy of validation model
* *`FS`*   : feature selection model ( It contains several results )
    + *`sf`* : index of selected features
    + *`ff`* : selected features
    + *`nf`* : number of selected features
    + *`s`*  : weight / score
    + *`t`*  : computational time (s)

### Example : Relief-F  ( RF ) 
```code 
% Parameters
opts.K  = 3;     % number of nearest neighbors
opts.Nf = 10;    % select 10 features

% Load dataset
load ionosphere.mat;

% Perform feature selection 
FS     = jffs('rf',feat,label,opts);

% Define index of selected features
sf_idx = FS.sf;

% Accuracy  
kfold  = 5;
Acc    = mSVM(feat(:,sf_idx),label,kfold);
```

## Requirement

* MATLAB 2016 or above 
* Statistics and Machine Learning Toolbox

## List of available filter feature selection methods
* The extra parameter represent the parameter other than number of selected features
* Note : Relief-F contains extra parameter to be adjusted. If you do not set the parameter then the algorithm will be executed using default setting
* You can use *`opts`* to set the parameter
    + *`K`* : number of nearest neighbors

| No. | Abbreviation | Name                                |  Extra Parameter        |
|-----|--------------|-------------------------------------|-------------------------|
| 4   | `'nca'`      | Neighborhood Component Analysis     | -                       |
| 3   | `'rf'`       | Relief-F                            | opts.K = 5              |
| 2   | `'tv'`       | Term Variance                       | -                       |
| 1   | `'pcc'`      | Pearson Correlation Coefficient     | -                       |

Filter-Feature-Selection-Toolbox

Explore Similar Repositories

Was this content helpful?

Recent Feedback

Download README