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Pattern Recognition with Fuzzy Objective Function Algorithms
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Citations
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Journal ArticleDOI
Application of fuzzy sets in soil science: fuzzy logic, fuzzy measurements and fuzzy decisions
TL;DR: Fuzzy systems, including fuzzy set theory and fuzzy logic, provide a rich and meaningful improvement, or extension of conventional logic, in soil science, and may be seen as a generalisation of classic set theory.
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.
Journal ArticleDOI
Computer-aided diagnosis of diabetic retinopathy: A review
Muthu Rama Krishnan Mookiah,U. Rajendra Acharya,U. Rajendra Acharya,Chua Kuang Chua,Choo Min Lim,Edwin Ng,Augustinus Laude +6 more
TL;DR: This review discusses the available methods of various retinal feature extractions and automated analysis for diagnosis of diabetic retinopathy.
Journal ArticleDOI
Noise-robust soft clustering of gene expression time-course data
TL;DR: To overcome the limitations of hard clustering, this work applied soft clustering which offers several advantages for researchers, including more noise robust and a priori pre-filtering of genes can be avoided.
Journal ArticleDOI
A neuro-fuzzy method to learn fuzzy classification rules from data
Detlef Nauck,Rudolf Kruse +1 more
TL;DR: A learning method for fuzzy classification rules is discussed, based on NEFCLASS, a neuro-fuzzy model for pattern classification that is able to derive fuzzy rules from a set of training data very quickly, and tunes them by modifying parameters of membership functions.
References
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Journal ArticleDOI
Nearest neighbor pattern classification
Thomas M. Cover,Peter E. Hart +1 more
TL;DR: The nearest neighbor decision rule assigns to an unclassified sample point the classification of the nearest of a set of previously classified points, so it may be said that half the classification information in an infinite sample set is contained in the nearest neighbor.
Book
Introduction to Statistical Pattern Recognition
TL;DR: This completely revised second edition presents an introduction to statistical pattern recognition, which is appropriate as a text for introductory courses in pattern recognition and as a reference book for workers in the field.
A fuzzy relative of the isodata process and its use in detecting compact well-separated clusters
TL;DR: In this paper, 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, and 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 LSE criterion function.