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Unconstrained Fuzzy C-Means Algorithm
IEEE Transactions on Pattern Analysis and Machine IntelligenceFuzzy C-Means algorithm (FCM) is one of the most commonly used fuzzy clustering algorithm, which uses the alternating optimization algorithm to update the membership matrix and the cluster center matrix. FCM achieves effective results in clustering tasks.
Feiping Nie 0001 +3 more
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Local convergence of the fuzzy c-Means algorithms
Pattern Recognition, 1986In this paper we prove a local convergence property, that is, a property pertaining to iteration sequences started near a solution. Specifically, a simple result is proved which shows that whenever an FCM algorithm is started sufficiently near a minimizer of the corresponding objective function, then the iteration sequence must converge to that ...
Richard J. Hathaway, James C. Bezdek
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NAFIPS 2008 - 2008 Annual Meeting of the North American Fuzzy Information Processing Society, 2008
Clustering streaming data presents the problem of not having all the data available at one time. Further, the total size of the data may be larger than will fit in the available memory of a typical computer. If the data is very large, it is a challenge to apply fuzzy clustering algorithms to get a partition in a timely manner. In this paper, we present
P. Hore +3 more
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Clustering streaming data presents the problem of not having all the data available at one time. Further, the total size of the data may be larger than will fit in the available memory of a typical computer. If the data is very large, it is a challenge to apply fuzzy clustering algorithms to get a partition in a timely manner. In this paper, we present
P. Hore +3 more
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Fuzzy C-Means and Fuzzy TLBO for Fuzzy Clustering
2015The choice of initial center plays a great role in achieving optimal clustering results in all partitional clustering approaches. Fuzzy C-means is a widely used approach but it also gets trapped in local optima values due to sensitiveness to initial cluster centers.
P. Gopala Krishna, D. Lalitha Bhaskari
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2019 5th Conference on Knowledge Based Engineering and Innovation (KBEI), 2019
Fuzzy c-means (FCM) is one of the most popular fuzzy clustering methods and it is used in various applications in computer science. Most clustering methods including FCM, suffer from bad initialization problem. If initial cluster centers (membership degree initialization in FCM) are not selected appropriately, it may yield poor results.
Yoosof Mashayekhi +3 more
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Fuzzy c-means (FCM) is one of the most popular fuzzy clustering methods and it is used in various applications in computer science. Most clustering methods including FCM, suffer from bad initialization problem. If initial cluster centers (membership degree initialization in FCM) are not selected appropriately, it may yield poor results.
Yoosof Mashayekhi +3 more
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Optimality tests for the fuzzy c-means algorithm
Pattern Recognition, 1994zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Wen Wei, Jerry M. Mendel
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A fuzzy c-means variant for the generation of fuzzy term sets
Fuzzy Sets and Systems, 2003zbMATH Open Web Interface contents unavailable due to conflicting licenses.
T. Warren Liao +2 more
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On efficiency of optimization in fuzzy \(c\)-means
Neural Parallel Sci. Comput., 2002Summary: The efficiency of optimization in fuzzy \(c\)-means clustering is investigated. Numerous, powerful, general-purpose simultaneous optimization methods, and hybrid methods combining these and the most widely used Alternating Optimization (AO) method, are extensively tested for speed comparison.
Yingkang Hu, Richard J. Hathaway
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Analysis of parameter selections for fuzzy c-means
Pattern Recognition, 2012zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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A fuzzy microaggregation algorithm using fuzzy c-means
2015Masking methods are used in data privacy to avoid the disclosure of sensitive information. Microaggregation is a perturbative masking method that has been proven effective. Data masked using microaggregation can be attacked when the intruder has information of the masking method and the parameters used.
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