Titlebook: Rough Sets, Fuzzy Sets, Data Mining and Granular Computing; 11th International C Aijun An,Jerzy Stefanowski,Guoyin Wang Conference proceedi

CAGE

Data Clustering Algorithms for Information Systemso supervised classification in pattern recognition; in the latter case classification rules should be derived from the classes of given points in a feature space. We also notice that methods of unsupervised classification (in other words, data clustering) in pattern recognition are closely related t

掃興

實(shí)施生效

Licentious

REIGN

FAZE

Information-Theoretic Measure of Uncertainty in Generalized Fuzzy Rough Setsrement of uncertainty in generalized fuzzy rough sets determined by a triangular norm. Based on information theory, the entropy of a generalized fuzzy approximation space is introduced, which is similar to Shannon’s entropy. To measure uncertainty in generalized fuzzy rough sets, a notion of fuzzine

女上癮

Madrigal

薄膜

Vaguely Quantified Rough Setstive way. As a result, the hybrid theory inherits their respective strengths, but also exhibits some weaknesses. In particular, although they allow for gradual membership, fuzzy rough sets are still abrupt in a sense that adding or omitting a single element may drastically alter the outcome of the a

CLAN