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Pattern Recognition with Fuzzy Objective Function Algorithms
  • J. Bezdek
  • Computer Science
  • Advanced Applications in Pattern Recognition
  • 31 July 1981
New updated! The latest book from a very famous author finally comes out. Book of pattern recognition with fuzzy objective function algorithms, as an amazing reference becomes what you need to get.Expand
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FCM: The fuzzy c-means clustering algorithm
This paper transmits a FORTRAN-IV coding of the fuzzy c -means (FCM) clustering program. Expand
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On cluster validity for the fuzzy c-means model
  • N. Pal, J. Bezdek
  • Mathematics, Computer Science
  • IEEE Trans. Fuzzy Syst.
  • 1 August 1995
We examine the role a subtle but important parameter-the weighting exponent m of the FCM model-plays in determining the validity of FCM partitions. Expand
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A possibilistic fuzzy c-means clustering algorithm
We propose a new model called possibilistic-fuzzy c-means (PFCM) that solves the noise sensitivity defect of FCM, overcomes the coincident clusters problem of PCM and eliminates the row sum constraints of FPCM. Expand
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Fuzzy Models and Algorithms for Pattern Recognition and Image Processing
Pattern Recognition.- Cluster Analysis for Object Data and Relational Data. Expand
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Cluster Validity with Fuzzy Sets
Abstract Given a finite, unlabelled set of real vectors X, one often presumes the existence of (c) subsets (clusters) in X, the members of which somehow bear more similarity to each other than toExpand
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Some new indexes of cluster validity
  • J. Bezdek, N. Pal
  • Mathematics, Medicine
  • IEEE Trans. Syst. Man Cybern. Part B
  • 1 June 1998
We review two clustering algorithms (hard c-means and single linkage) and three indexes of crisp cluster validity (Hubert's statistics, the Davies-Bouldin index, and Dunn's index) and propose several generalizations of them that are not as brittle to outliers in the clusters. Expand
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Decision templates for multiple classifier fusion: an experimental comparison
We compare 11 versions of our model with 14 other techniques for classi"er fusion on both data sets. Expand
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A Convergence Theorem for the Fuzzy ISODATA Clustering Algorithms
  • J. Bezdek
  • Mathematics, Computer Science
  • IEEE Transactions on Pattern Analysis and Machine…
  • 1980
In this paper the convergence of a class of clustering procedures, popularly known as the fuzzy ISODATA algorithms, is established. Expand
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Fuzzy mathematics in pattern classification
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