k近傍の最大距離に基づくノイズにロバストな自己組織化マップに基づくクラスタリング手法

抄録

Clustering methods, which are based on Self-Organaizing Map, can not precisely classify data when noise data is included. We describe a clustering method that can precisely classify data even when noise data are included.