FD-CABOSFV High Dimensional Data Clustering for Interval-scaled Variables
Huimin Huang · 2011
FD-CABOSFV,an improved algorithm of CABOSFV based on fuzzy discretizaton,is proposed for highdim ensional data clustering of interval-scaled variables.It discretizes the data of each attribute portfolio by using the idea of fuzzy C means clustering,and determines each object's discretized attribute category byλcut turning the attribute value into binary variables,and then uses CABOSFV algorithm to complete clustering.Three UCI benchmark data sets were used to compare FD-CABOSFV with famous K-means clustering algorithm.The empirical tests show that FDCABOSFV is more effective.