Self-Organizing Maps
Clustering with Swarm Algorithms Compared to Emergent SOM
WSOM '09 Proceedings of the 7th International Workshop on Advances in Self-Organizing Maps
WSOM '09 Proceedings of the 7th International Workshop on Advances in Self-Organizing Maps
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A new classification method is proposed with which a multidimensional data set was visualized. The phase distance on the spherical surface for the labeled data was computed and a dendrogram constructed using this distance. Then, the data can be easily classified. To this end, the color-coded clusters on the spherical surface were represented based on the distance between each node and the labels on the sphere. Thus, each cluster can have a separate color. This method can be applied to a variety of data. As a first-example, we considered the iris benchmark data set. A boundary between the clusters was clearly visualizible with this coloring method. As a second example, the velocity (first derivative) mode of a Plethysmogram pulse-wave data set was analyzed using the distance measure on the spherical surface.