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Fuzzy clustering: Determining the number of clusters
2012 Fourth International Conference on Computational Aspects of Social Networks (CASoN), 2012In this study we analyze behavior of two types of coefficients for determining the suitable number of clusters obtained when fuzzy cluster analysis is applied. First one is Dunn's coefficient which contains membership degrees in its computational formula; second one is the average silhouette width, used primarily for evaluating hard clustering.
Hana Rezanková, Dusan Húsek
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1978
When one is lecturing in a centre for interdisciplinary research, it is, I imagine, appropriate to start by emphasizing the interdisciplinary character of the topic one is going to discuss. In my case this does not present any difficulty. Clustering is a pictorial term for positive correlations in an ensemble of randomly distributed bodies or events ...
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When one is lecturing in a centre for interdisciplinary research, it is, I imagine, appropriate to start by emphasizing the interdisciplinary character of the topic one is going to discuss. In my case this does not present any difficulty. Clustering is a pictorial term for positive correlations in an ensemble of randomly distributed bodies or events ...
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Cluster headache and cluster variants
Current Treatment Options in Neurology, 2003Patients must be cognizant of the time course of the cluster headache periods to optimally tailor their therapy. Steroids provide the fastest onset of prophylactic effect. Once steroids are initiated, it remains difficult to wean patients off of them, and that is why it is always recommended to associate another prophylactic agent from the onset with ...
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On the Number of Clusters in Cluster Analysis
1998Clustering is a fundamental tool for analyzing the structure of feature spaces. It has been applied to various fields such as pattern recognition, information retrieval and so on. Many studies have been done on this problem and various kinds of clustering methods have been proposed and compared (e.g., [1]).
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Joint Cluster Based Co-clustering for Clustering Ensembles
2006This paper introduces a new method for solving clustering ensembles, that is, combining multiple clusterings over a common dataset into a final better one. The ensemble is reduced to a graph that simultaneously models as vertices the original clusters in the ensemble and the joint clusters derived from them.
Tianming Hu +3 more
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CLUSTERS AND CLUSTERS OF CLUSTERS IN COLLISIONS
Photonic, Electronic and Atomic Collisions, 2006B. MANIL +18 more
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Data clustering: application and trends
Artificial Intelligence Review, 2022Gbeminiyi John Oyewole, George Thopil
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To Cluster or not to Cluster: A VRU Clustering Based on V2X Communication
2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC), 2023Silas C. Lobo +2 more
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From clustering to clustering ensemble selection: A review
Engineering Applications of Artificial Intelligence, 2021Keyvan Golalipour +2 more
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