Classification toolbox for MATLAB



What Classification toolbox for MATLAB is?

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), class modeling 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).

This is the version 7.0 of the Classification toolbox for MATLAB.

Classification toolbox for MATLAB has been released by Milano Chemometrics and QSAR research Group.

[-> top]


Installing the toolbox

MATLAB should be installed, while the Statistics Toolbox is needed to compute some of the classification methods (Discriminant Analysis, Support Vector Machines, CART, Random Forest and some functions for SIMCA and UNEQ). In order to install the Classification toolbox for MATLAB, simply copy the files to a folder (e.g. "Classification toolbox for MATLAB"). Then, in order to use it, select the same folder as MATLAB current directory.

[-> top]


Help structure

This html help provides some underlying information on classification methods (see Theory section). If you wish to use the graphical interface, please read the corresponding section. A complete list of all the used MATLAB routines is given. An example of analysis is shown. Please, read also the license and write us if you find bugs or have comments.

[-> top]