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MATAB toolbox for Multivariate Data Analysis
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README.md

Multivariate Data Analysis toolbox for MATLAB

Description

mdatools is a free open source toolbox for analysis of multivariate experimental data based on methods widespread in Chemometrics. The toolbox can work with conventional two-way datasets (where rows are objects or measurements and columns are variables) as well as with colour and hyperspectral images. Currently only command line tools are available, old GUI version has been removed from the project and new is now under developing.

All documentation is available at GitBook. It is recommended to start learning the toolbox with a quick start guide, which gives a brief overview of basic methods with a lot of examples. It allows you to start working with the toolbox after 30 minutes learning. Then just continue with the user guide to get acquainted with all available features and details.

The last version of the toolbox was tested using MATLAB 2018b but should also work in earlier varsion. For the basic functionality you do not need any additional toolboxes installed. All methods were tested using well-known datasets, but there still could be some bugs, in this case please report to svkucheryavski@gmail.com.

Installation

The current version is 0.1.7 (from 31.10.2018).

Installation is easy and the procedure is similar to most of the others 3rd party MATLAB Toolboxes. Download zip archive for the latest release and unzip it to the folder you use to keep you MATLAB code, for example to Documents/MATLAB or Documents/MATLAB/Toolboxes. Open the folder in MATLAB environment and run install.m script, which will do the rest.

If you upgrade from previous version, run uninstall on the old version first (it will clear the path list and remove folder with toolbox), then unzip the new version and follow the instructions above.

Bug reports and suggestions

If you find a bug, please, send a message to svkucheryavski@gmail.com with detailed description or use a form on GitHub. Any comments and suggestions will also be highly appreciated.

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