Variable Reduction Testbench is a MATLAB module that allows the application of several methods for variable reduction based on correlation analysis:

- These methods rank the variables, starting from the most correlated ones (i.e. the most redundant variables, thus they can be easily removed from the dataset without significant information loss) and ending with the variables with lowest correlation. Most of the methods suggest also how many variables could be removed from the dataset without information loss;
- Datasets are required in the form of matrices of n x p elements, where n are the samples (rows) and p the variables (columns);
- Each method also provides the value of standardized Shannon entropy (H) for all the variables, since it is a very useful index of the quantity of information contained in each variable;
- The module is entirely based on a graphic interface; the ranking output is given in several forms (plain text file, MATLAB file and a plot) thus allowing an easy understanding of the results. Furthermore, outputs of the correlation analysis are additionally provided;