The novel hierarchical clustering approach using self-organizing map with optimum dimension selection.

It is found that SOM is superior to or on par with other clustering approaches, like, k-means or the other, and could be used successfully to cluster all types of data sets. Ten benchmark data sets from diverse domains like medical, biological, and chemical are tested in this work, including the synthetic data sets.