Results 21 to 30 of about 375,352 (295)
Median evidential c-means algorithm and its application to community detection [PDF]
, 2015 Median clustering is of great value for partitioning relational data. In this paper, a new prototype-based clustering method, called Median Evidential C-Means (MECM), which is an extension of median c-means and median fuzzy c-means on the theoretical ...
Liu, Zhun-Ga +3 more
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Benchmarking parameterized fuzzy c-Means classifier
2009 IEEE International Conference on Fuzzy Systems, 2009 This paper reports on the performance of the fuzzy c-means based classifier (FCMC). Test set performances optimized by way of several CV procedures and three sets of hyperparameters are throughly compared. UCI benchmark datasets are used to evaluate the performance.
Hidetomo ICHIHASHI +3 more
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Performance comparison of fuzzy and non-fuzzy classification methods
Egyptian Informatics Journal, 2016 In data clustering, partition based clustering algorithms are widely used clustering algorithms. Among various partition algorithms, fuzzy algorithms, Fuzzy c-Means (FCM), Gustafson–Kessel (GK) and non-fuzzy algorithm, k-means (KM) are most popular ...
B. Simhachalam, G. Ganesan
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A Federated Fuzzy c-means Clustering Algorithm
Proceedings of WILF 2021, the 13th International Workshop on Fuzzy Logic and Applications (WILF 2021), 2021 Traditional clustering algorithms require data to be centralized on a single machine or in a datacenter. Due to privacy issues and traffic limitations, in several real applications data cannot be transferred, thus hampering the effectiveness of traditional clustering algorithms, which can operate only on locally stored data.
B��rcena, Jos�� Luis Corcuera +4 more
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An improved fuzzy clustering image segmentation algorithm combining spatial information
Xi'an Gongcheng Daxue xuebao, 2021 In order to improve the ability of fuzzy C-means (FCM) clustering algorithm to suppress noise, an improved fuzzy clustering image segmentation algorithm was proposed.
Xudong LIU +4 more
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Probabilistic clustering algorithms for fuzzy rules decomposition [PDF]
, 2007 The fuzzy c-means (FCM) clustering algorithm is the best known and used method in fuzzy clustering and is generally applied to well defined set of data. In this paper a generalized Probabilistic fuzzy c-means (FCM) algorithm is proposed and applied to
Igrejas, Getúlio, Salgado, Paulo
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International Journal of Intelligent Systems, 2023 The problem of ordered clustering in the context of decision‐making with multiple criteria has garnered significant interest from researchers in the field of management science and operational research. In real‐world scenarios, the datasets often exhibit imprecision or uncertainty, which can lead to suboptimal ordered‐clustering outcomes.
Muhammad Adnan Bashir +2 more
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IEEE Access, 2020 Due to the rapid development of information technology and network technology, there is a lot of data, but the phenomenon of lack of knowledge is becoming more and more serious.
Yuan Huang +4 more
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Barekeng, 2023 Indonesia is a country that has a population density that is increasing every year, with the increase in population density, the crime rate in Indonesia is increasing. Criminal acts arise because they are supported by factors that cause crime. To improve
Bella Destia, Mujiati Dwi Kartikasari
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BarekengCluster analysis involves the methodical categorization of data based on the degree of similarity within each group to group data with similar characteristics. This study focuses on classifying poverty data across Indonesian provinces.
Dian Kurniasari +4 more
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