RFCM: A Hybrid Clustering Algorithm Using Rough and Fuzzy Sets

摘要: A hybrid unsupervised learning algorithm, termed as rough-fuzzy c-means, is proposed in this paper. It comprises a judicious integration of the principles rough sets and fuzzy sets. While concept lower upper approximations deals with uncertainty, vagueness, incompleteness class definition, membership function enables efficient handling overlapping partitions. The crisp bound boundary class, introduced selection cluster prototypes. Several quantitative indices are based on for evaluating performance c-means algorithm. effectiveness along comparison other algorithms, has been demonstrated set real life data