Collection of Matlab modules for calculating unsupervised and supervised mutlivariate models (download from the Milano Chemometrics and QSAR Research Group):

• Classification toolbox (for Matlab): 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), Backpropagation Neural Networks (BPNN)..
• PCA toolbox (for Matlab): unsupervised multivariate models for data structure analysis: Principal Component Analysis (PCA), Multidimensional Scaling (MDS) and Cluster Analysis.
• N3-BNN toolbox (for Matlab): N3 (N-Nearest Neighbours), BNN (Binned Nearest Neighbours) and kNN (k Nearest Neighbours) local classification methods.
• Kohonen and CPANN toolbox (for Matlab): Kohonen Maps and Counterpropagation Artificial Neural networs (CPANNs), Supervised Kohonen networks and XY-fused networks.
• Regression toolbox (for Matlab): collection of MATLAB modules for calculating regression multivariate models: Ordinary Least Squares (OLS), Partial Least Squares (PLS), Principal Component Regression (PCR), Ridge regression, local regression based on K Nearest Neighbours (KNN) and Binned Nearest Neighbours (BNN) approaches, and variable selection approaches (All Subset Models, Forward selection, Genetic Algorithms and Reshaped Sequential Replacement).