Classification toolbox (for MATLAB)

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) , Unequal class models (UNEQ) 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 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.

Download
Fill in the following form. Your personal data will be used only for notification via email of new releases of the toolbox and will not be communicated to external third parties. Once the form has been submitted, download the rar file containing the toolbox on a local folder, unzip the rar file and extract all the Matlab modules in a unique folder. Before starting calculations, please read the HELP files provided in HTML format. A complete guide on how to calculate models is provided.