PCA toolbox for matlab
Updated 21 Dec 2021
The PCA toolbox for MATLAB is a collection of MATLAB modules for calculating unsupervised multivariate models for data structure analysis: Principal Component Analysis (PCA), Multidimensional Scaling (MDS) and Cluster Analysis.
This is the version 1.5 of the PCA toolbox for MATLAB
PCA toolbox for MATLAB has been released by Milano Chemometrics and QSAR research Group. Visit our website at www.michem.unimib.it
MATLAB should be installed, while the Statistics Toolbox is needed to compute Cluster Analysis and Multidimensional Scaling. In order to install the toolbox, simply copy the files to a folder (e.g. "PCA toolbox for MATLAB"). Then, in order to use it, select the same folder as MATLAB current directory.
Before starting calculations, please read the HELP files provided in HTML format. A complete guide on how to calculate models is provided.
Help files are provided in HTML format. Open the help.htm file in your favourite browser and read it!
The toolbox is freeware and may be used if proper reference is given to the authors. Preferably refer to the following paper: D. Ballabio (2015), A MATLAB toolbox for Principal Component Analysis and unsupervised exploration of data structure Chemometrics and Intelligent Laboratory Systems, 149 Part B, 1-9
The PCA toolbox for MATLAB is distributed with an Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence: https://creativecommons.org/licenses/by-nc-nd/4.0/ 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.
D. Ballabio (2015), A MATLAB toolbox for Principal Component Analysis and unsupervised exploration of data structure, Chemometrics and Intelligent Laboratory Systems, 149 Part B, 1-9
MATLAB Release Compatibility
Platform CompatibilityWindows macOS Linux
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