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), Soft Independent Modeling of Class Analogy (SIMCA), Random Forest (RF) and Backpropagation Neural Networks (BPNN). 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 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
The Classification toolbox for MATLAB is distributed with an Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence:
You are free to share – copy and redistribute the material in any medium or format. The licensor cannot revoke these freedoms as long as you follow the following license terms:
Attribution – You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
NonCommercial – You may not use the material for commercial purposes.
NoDerivatives – If you remix, transform, or build upon the material, you may not distribute the modified material.

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. If you experience any problem to downlaod the toolbox, write to