Feature Selection Package - Algorithms - Fast Correlation-Based Filter
FCBF is a fast correlation-based filter algorithm designed for high-dimensional data and has been shown effective in removing both irrelevant features and redundant features.
Method Signature:
[out] = fsFCBF(X,Y)

    out: A struct containing the field 'fList', the list of features relevant for further processing.

    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 ...
Code Example
% Using the wine.dat data set, which can be found at
% [fspackage_location]/classifiers/knn/wine.mat
Keyword in Evaluator Framework
BibTex entry for:

Feature Selection for High-Dimensional Data: A Fast Correlation-Based Filter Solution by L. Yu and H. Liu.

Discretization: An Enabling Technique H. Liu, F. Hussain, C.L. Tan, and M. Dash.
   author = {Liu, H. and Yu, L.},
   title = {Feature Selection for High-Dimensional Data: A Fast Correlation-Based Filter Solution},
   booktitle = {Correlation-Based Filter Solution". In Proceedings of The Twentieth International Conference on Machine Leaning (ICML-03)},
   year = {2003},
   pages = {856--863},
   address = {Washington, D.C.},
   publisher = {ICM}

@inproceedings{ author = {Liu,
   H., Hussain, F., Tan, C.L., and Dash, Manoranjan} title = {Discretization: An Enabling Technique},
   booktitle = {Data Mining and Knowledge Discovery},
   year = {2002},
   pages = {393--423},
   address = {Netherlands} publisher = {Springer Netherland}