Algorithms for clustering data
Algorithms for clustering data
Pattern Recognition with Fuzzy Objective Function Algorithms
Pattern Recognition with Fuzzy Objective Function Algorithms
Fuzzy Models and Algorithms for Pattern Recognition and Image Processing
Fuzzy Models and Algorithms for Pattern Recognition and Image Processing
Cluster validity methods: part I
ACM SIGMOD Record
Clustering validity checking methods: part II
ACM SIGMOD Record
Document clustering based on non-negative matrix factorization
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Cluster Analysis for Gene Expression Data: A Survey
IEEE Transactions on Knowledge and Data Engineering
Document Clustering Using Locality Preserving Indexing
IEEE Transactions on Knowledge and Data Engineering
Pattern Recognition, Third Edition
Pattern Recognition, Third Edition
Pattern Recognition Letters
On fuzzy cluster validity indices
Fuzzy Sets and Systems
Advances in Fuzzy Clustering and its Applications
Advances in Fuzzy Clustering and its Applications
Clustering
Extending the rand, adjusted rand and jaccard indices to fuzzy partitions
Journal of Intelligent Information Systems
Nonparametric genetic clustering: comparison of validity indices
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Similarity measure for anomaly detection and comparing human behaviors
International Journal of Intelligent Systems
Automatic aspect discrimination in data clustering
Pattern Recognition
Comparing partitions by means of fuzzy data mining tools
SUM'12 Proceedings of the 6th international conference on Scalable Uncertainty Management
Refining discretizations of continuous-valued attributes
MDAI'12 Proceedings of the 9th international conference on Modeling Decisions for Artificial Intelligence
A new index based on sparsity measures for comparing fuzzy partitions
SSPR'12/SPR'12 Proceedings of the 2012 Joint IAPR international conference on Structural, Syntactic, and Statistical Pattern Recognition
Fuzzy clustering of human activity patterns
Fuzzy Sets and Systems
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When clustering produces more than one candidate to partition a finite set of objects O, there are two approaches to validation (i.e., selection of a "best" partition, and implicitly, a best value for c, which is the number of clusters in O). First, we may use an internal index, which evaluates each partition separately. Second, we may compare pairs of candidates with each other, or with a reference partition that purports to represent the "true" cluster structure in the objects. This paper generalizes many of the classical indices that have been used with outputs of crisp clustering algorithms so that they are applicable for candidate partitions of any type (i.e., crisp or soft, with soft comprising the fuzzy, probabilistic, and possibilistic cases). Space prevents inclusion of all of the possible generalizations that can be realized this way. Here, we concentrate on the Rand index and its modifications. We compare our fuzzy-Rand index with those of Campello, Hullermeier and Rifqi, and Brouwer, and show that our extension of the Rand index is O(n), while the other three are all O(n2). Numerical examples are given to illustrate various facets of the new indices. In particular, we show that our indices can be used, even when the partitions are probabilistic or possibilistic, and that our method of generalization is valid for any index that depends only on the entries of the classical (i.e., four-pair types) contingency table for this problem.