Classification Toolbox
The Classification toolbox for MATLAB is a collection of MATLAB modules for calculating classification (supervised pattern recognition) multivariate models: Discriminant Analysis, Partial Least Square Discriminant Analysis (PLSDA), Classification trees (CART), K-Nearest Neighbors (kNN), Potential Functions (Kernel Density Estimators), Support Vector Machines (SVM) and Soft Independent Modeling of Class Analogy (SIMCA). A graphical user interface (GUI), which allows an easy model calculation and analysis of results, is also provided with the toolbox.
 Help files
HTML files are provided toghter with the MATLAB files in order to help the user. The full help is also available on line. The HTML help provides some underlying information on multivariate classification (see Theory section); it also explains how to prepare your data, how to handle the model settings and how to calculate the classification models. An example of analysis is shown.
 Conditions and warranty
The toolbox is freeware and may be used (but not modified) if proper reference is given to the authors. Preferably refer to the followign papers:

Ballabio D, Consonni V, (2013) Classification tools in chemistry. Part 1: Linear models. PLS-DA. Analytical Methods, 5, 3790-3798

In short, no guarantees, whatsoever, are given for the quality of this toolbox or for the consequences of its use. It is inevitable that there will be some bugs, but we have tried to test the algorithms thoroughly.


You can freely download the MATLAB modules:

download Classification Toolbox