Independent Variable Group Analysis

The Independent Variable Group Analysis (IVGA) research is about methods and software that search for a grouping or structure for the variables in data, effectively grouping dependent variables together.

Current work is mostly based on utilizing variational Bayesian learning and combinatorial optimization mechanisms. This framework allows searching for the most compact, most probable, model for the whole data, so that the variables in the same group are modeled in the same model.

Group members

Krista Lagus (senior researcher)
Antti Honkela (post-doc researcher)
Paul Wagner (research assistant)
Jeremias Seppä (research assistant)

External collaborators

Esa Alhoniemi (post-doc researcher, UTU/IT)
Harri Valpola (post-doc researcher, TKK/LCE)

Publications

Honkela, A., Seppä, J., Alhoniemi, E. (2008): Agglomerative Independent Variable Group Analysis. Neurocomputing 71(7-9), pp. 1311-1320.
Appeared in Special Issue for the 15th European Symposium on Artificial Neural Networks (ESANN 2007).
doi:10.1016/j.neucom.2007.11.024
Alhoniemi, E., Honkela, A., Lagus, K., Seppä, J., Wagner, P., and Valpola, H. (2007): Compact Modeling of Data Using Independent Variable Group Analysis. IEEE Transactions on Neural Networks, 18(6), pp. 1762 - 1776.
doi:10.1109/TNN.2007.900809
Honkela, A., Seppä, J., Alhoniemi, E. (2007): Agglomerative Independent Variable Group Analysis. In Proceedings of the 15th European Symposium on Artificial Neural Networks (ESANN 2007), Bruges, Belgium. Pp. 55-60.
Lagus, K., Alhoniemi, E.,Seppä, J., Honkela, A.,Wagner P. (2005): Independent Variable Group Analysis in Learning Compact Representations for Data. In Honkela T. et al., eds., Proceedings of International and Interdisciplinary Conference on Adaptive Knowledge Representation and Reasoning - AKRR'05, Espoo, Finland. Pp. 49-56.
Lagus, K., Alhoniemi, E., Valpola, H (2001): Independent Variable Group Analysis. In Dorffner et al, eds, Proceedings of International Conference on Artificial Neural Networks - ICANN 2001, Vienna, Austria. Pp. 203-210. Springer.

Downloads

IVGA Toolbox

The latest version of the Independent Variable Group Analysis Toolbox for MATLAB can be downloaded from the following links. See the README.txt file in the package for install and usage instructions. The package is available under the GNU General Public License. (older versions are available here)

ivga-1.14.8.zip

ivga-1.14.8.tar.gz

The MATLAB scripts for running the ionosphere data experiments and the synthetic data experiment reported in article "Compact Modeling of Data Using Independent Variable Group Analysis" are available here:

ivga_experiment_codes.zip

AIVGA Toolbox

The latest version of the Agglomerative Independent Variable Group Analysis Toolbox for MATLAB can be downloaded from the following links. See the README file in the package for install and usage instructions. The package is available under the GNU General Public License.

aivga-1.0.zip

aivga-1.0.tar.gz