Learning Metrics for Self-Organizing Maps

Reference:

Samuel Kaski, Janne Sinkkonen, and Jaakko Peltonen. Learning metrics for self-organizing maps. In Proceedings of IJCNN'01, International Joint Conference on Neural Networks, pages 914–919, Piscataway, NJ, 2001. IEEE. Preprint postscript at http://www.cis.hut.fi/projects/mi/papers/ijcnn01.ps.gz.

Abstract:

We introduce methods that adapt the metric of the data space to reflect relevance, as indicated by auxiliary data associated with the primary data samples. The derived metric is especially useful in descriptive data analysis by unsupervised methods such as the Self-Organizing Maps. In this work we use the new metric to refine SOM-based analyses of the factors affecting the bankruptcy risk of companies.

Suggested BibTeX entry:

@inproceedings{Kaski01ijcnn,
    address = {Piscataway, NJ},
    author = {Samuel Kaski and Janne Sinkkonen and Jaakko Peltonen},
    booktitle = {Proceedings of IJCNN'01, International Joint Conference on Neural Networks},
    note = {Preprint postscript at \url{http://www.cis.hut.fi/projects/mi/papers/ijcnn01.ps.gz}},
    pages = {914-919},
    publisher = {IEEE},
    title = {Learning Metrics for Self-Organizing Maps},
    year = {2001},
}