Results 61 to 70 of about 867,994 (193)
Extended Fuzzy Clustering Algorithms [PDF]
Fuzzy clustering is a widely applied method for obtaining fuzzy models from data. Ithas been applied successfully in various fields including finance and marketing.
Kaymak, U., Setnes, M.
core
Fuzzy clustering with Minkowski distance [PDF]
Distances in the well known fuzzy c-means algorithm of Bezdek (1973) are measured by the squared Euclidean distance.Other distances have been used as well in fuzzy clustering.
Groenen, P.J.F. +2 more
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A robust multi-view knowledge transfer-based rough fuzzy C-means clustering algorithm
Complex & Intelligent SystemsRough fuzzy clustering algorithms have received extensive attention due to the excellent ability to handle overlapping and uncertainty of data. However, existing rough fuzzy clustering algorithms generally consider single view clustering, which neglects ...
Feng Zhao +3 more
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Fuzzy Clustering Models for Gene Expression Data Analysis [PDF]
With the advent of microarray technology, it is possible to monitor gene expression of tens of thousands of genes in parallel. In order to gain useful biological knowledge, it is necessary to study the data and identify the underlying patterns, which ...
Wang, Yu
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Single-Valued Neutrosophic Clustering Algorithm Based on Tsallis Entropy Maximization
Axioms, 2018 Data clustering is an important field in pattern recognition and machine learning. Fuzzy c-means is considered as a useful tool in data clustering. The neutrosophic set, which is an extension of the fuzzy set, has received extensive attention in solving ...
Qiaoyan Li +3 more
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Cluster validity for fuzzy criterion clustering
1995 IEEE International Conference on Systems, Man and Cybernetics. Intelligent Systems for the 21st Century, 1999 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Esogbue, A.O., Liu, Baoding
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Comparison Of Incomplete Data Handling Techniques For Neuro-Fuzzy System
Computer Science, 2014 Real-life data sets sometimes miss some values. The incomplete data needs specialized algorithms or preprocessing that allows the use of the algorithms for complete data.
Marcin Sikora, Krzysztof Simiński
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Document clustering using sample weighting [PDF]
, 2007 Clustering algorithm based on Sample weighting has been noticed recently. In this paper, a novel sample weighting clustering algorithm is presented based on K-Means and fuzzy C-Means algorithm.
Su, Xinning +2 more
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A COMPARISON OF TWO FUZZY CLUSTERING TECHNIQUES [PDF]
Journal of Process Management and New Technologies, 2013 - In fuzzy clustering, unlike hard clustering, depending on the membership value, a single object may belong exactly to one cluster or partially to more than one cluster.
Samarjit Das, Hemanta K. Baruah
doaj
A Definition for Hesitant fuzzy Partitions
International Journal of Computational Intelligence Systems, 2016 In this paper, we define hesitant fuzzy partitions (H-fuzzy partitions) to consider the results of standard fuzzy clustering family (e.g. fuzzy c-means and intuitionistic fuzzy c-means).
Laya Aliahmadipour +3 more
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