Supplementary material concerning repeatability of
Multivariate Maximal Correlation Analysis

by Nguyen H. V., Müller E., Vreeken J., and Böhm K.

published in Proc. International Conference on Machine Learning (ICML 2014), Beijing, China (2014)

This page provides additional information about our experiments and assist in reproducing the results with our MAC algorithm. We provide this in addition to our publication [download full text PDF] published at  ICML 2014 conference.
 

Computation of MAC Results


In order to enable repeatability of our results we provide the MAC algorithm and all data sets used in our experiments. In order to execute MAC you can use the following command line structure:

Parameter Meaning
-FILE_INPUT name of input file
-FILE_CP_OUTPUT name of output file for cut points
-FILE_RUNTIME_OUTPUT name of output runtime file
-FILE_DATA_OUTPUT name of output file for discretized data
-NUM_ROWS number of data points
-NUM_MEASURE_COLS number of dimensions
-FIELD_DELIMITER delimiter used in the input file
-ALPHA is actually (1 - epsilon)
-CLUMPS is actually c
 

Download


If you publish results based on our material, then please include a reference to our paper. This will help others to obtain the same data sets, algorithms, parameter settings and evaluation measures and replicate your experiments.

All benchmark data sets can be found in the following file: data.zip. Our data collection contains the used benchmark data from the UCI Machine Learning Repository.

In order to reproduce our results for MAC we provide the executables of our method: MAC.jar