@inproceedings{
    Kaski01ijcnn,
    author = "Kaski, Samuel and Sinkkonen, Janne and Peltonen, Jaakko",
    publisher = "IEEE",
    title = "Learning Metrics for Self-Organizing Maps",
    url = "http://dx.doi.org/10.1109/IJCNN.2001.939481",
    booktitle = "Proceedings of IJCNN01, International Joint Conference on Neural Networks",
    address = "Piscataway, NJ",
    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.",
    note = "Preprint postscript at \url{http://www.cis.hut.fi/projects/mi/papers/ijcnn01.ps.gz}",
    flags = "AIRC copy",
    year = "2001",
    impactfactor = "D3",
    pages = "914-919"
}