Feature Selection Package - Algorithms - T-test

Description

A t-test is a statistical hypothesis where the statistic follows a Student
distribution.

Usage

Method Signature:

Output:

*out: * A struct containing the following fields

Input:

*X: *
The features on current trunk, each column is a feature vector on all
instances, and each row is a part of the instance.

*Y: *
The label of instances, in single column form: 1 2 3 4 5 ...

[*out*] = fsTtest(*X*,*Y*)

Output:

- W - The distribution at each data point.
- fList - The list of features that are deemed useful.
- prf - This means that the smaller the feature weight is, the more useful it will be to the user.

Input:

Code Example

% Using the wine.dat data set, which can be found at

% [fspackage_location]/classifiers/knn/wine.mat

fsTtest(X,Y);

% [fspackage_location]/classifiers/knn/wine.mat

fsTtest(X,Y);

Keyword in Evaluator Framework

ttest