Journal ArticleDOI
Pattern classification problems and fuzzy sets
TLDR
A unified presentation of classical clustering algorithms is proposed both for the hard and fuzzy pattern classification problems, and two coefficients that measure the “degree of non-fuzziness” of the partition are proposed.About:
This article is published in Fuzzy Sets and Systems.The article was published on 1978-10-01. It has received 209 citations till now. The article focuses on the topics: Fuzzy classification & Fuzzy clustering.read more
Citations
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Ignorance and Uncertainty: Emerging Paradigms
TL;DR: In this article, a variety of approaches to the problem of indeterminacies in human thought and behavior are discussed, including cognitive psychology, social psychology, organizational studies, sociology, and social anthroplogy.
Journal ArticleDOI
A survey of fuzzy clustering
TL;DR: A survey of fuzzy set theory applied in cluster analysis in three categories: the fuzzy clustering based on fuzzy relation, the fuzzy generalized k-nearest neighbor rule, and an overview of a nonparametric classifier.
Journal ArticleDOI
A cluster validity index for fuzzy clustering
Kuo-Lung Wu,Miin-Shen Yang +1 more
TL;DR: The results of comparative study show that the proposed PCAES index has high ability in producing a good cluster number estimate and in addition, it provides a new point of view for cluster validity in a noisy environment.
Journal ArticleDOI
Low-complexity fuzzy relational clustering algorithms for Web mining
TL;DR: A comparison of FCMdd with the well-known relational fuzzy c-means algorithm (RFCM) shows thatFCMdd is more efficient, and several applications of these algorithms to Web mining, including Web document clustering, snippet clusters, and Web access log analysis are presented.
References
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Some methods for classification and analysis of multivariate observations
TL;DR: The k-means algorithm as mentioned in this paper partitions an N-dimensional population into k sets on the basis of a sample, which is a generalization of the ordinary sample mean, and it is shown to give partitions which are reasonably efficient in the sense of within-class variance.
Journal ArticleDOI
Pattern Classification and Scene Analysis.
Book
Pattern classification and scene analysis
Richard O. Duda,Peter E. Hart +1 more
TL;DR: In this article, a unified, comprehensive and up-to-date treatment of both statistical and descriptive methods for pattern recognition is provided, including Bayesian decision theory, supervised and unsupervised learning, nonparametric techniques, discriminant analysis, clustering, preprosessing of pictorial data, spatial filtering, shape description techniques, perspective transformations, projective invariants, linguistic procedures, and artificial intelligence techniques for scene analysis.
Journal ArticleDOI
A Fuzzy Relative of the ISODATA Process and Its Use in Detecting Compact Well-Separated Clusters
TL;DR: Two fuzzy versions of the k-means optimal, least squared error partitioning problem are formulated for finite subsets X of a general inner product space; in both cases, the extremizing solutions are shown to be fixed points of a certain operator T on the class of fuzzy, k-partitions of X, and simple iteration of T provides an algorithm which has the descent property relative to the least squarederror criterion function.