A Self-Adaptive Fuzzy c-Means Algorithm for Determining the Optimal Number of Clusters
المؤلفون المشاركون
Ren, Min
Liu, Peiyu
Wang, Zhihao
Yi, Jing
المصدر
Computational Intelligence and Neuroscience
العدد
المجلد 2016، العدد 2016 (31 ديسمبر/كانون الأول 2015)، ص ص. 1-12، 12ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2016-11-29
دولة النشر
مصر
عدد الصفحات
12
التخصصات الرئيسية
الملخص EN
For the shortcoming of fuzzy c-means algorithm (FCM) needing to know the number of clusters in advance, this paper proposed a new self-adaptive method to determine the optimal number of clusters.
Firstly, a density-based algorithm was put forward.
The algorithm, according to the characteristics of the dataset, automatically determined the possible maximum number of clusters instead of using the empirical rule n and obtained the optimal initial cluster centroids, improving the limitation of FCM that randomly selected cluster centroids lead the convergence result to the local minimum.
Secondly, this paper, by introducing a penalty function, proposed a new fuzzy clustering validity index based on fuzzy compactness and separation, which ensured that when the number of clusters verged on that of objects in the dataset, the value of clustering validity index did not monotonically decrease and was close to zero, so that the optimal number of clusters lost robustness and decision function.
Then, based on these studies, a self-adaptive FCM algorithm was put forward to estimate the optimal number of clusters by the iterative trial-and-error process.
At last, experiments were done on the UCI, KDD Cup 1999, and synthetic datasets, which showed that the method not only effectively determined the optimal number of clusters, but also reduced the iteration of FCM with the stable clustering result.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Ren, Min& Liu, Peiyu& Wang, Zhihao& Yi, Jing. 2016. A Self-Adaptive Fuzzy c-Means Algorithm for Determining the Optimal Number of Clusters. Computational Intelligence and Neuroscience،Vol. 2016, no. 2016, pp.1-12.
https://search.emarefa.net/detail/BIM-1099605
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Ren, Min…[et al.]. A Self-Adaptive Fuzzy c-Means Algorithm for Determining the Optimal Number of Clusters. Computational Intelligence and Neuroscience Vol. 2016, no. 2016 (2015), pp.1-12.
https://search.emarefa.net/detail/BIM-1099605
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Ren, Min& Liu, Peiyu& Wang, Zhihao& Yi, Jing. A Self-Adaptive Fuzzy c-Means Algorithm for Determining the Optimal Number of Clusters. Computational Intelligence and Neuroscience. 2016. Vol. 2016, no. 2016, pp.1-12.
https://search.emarefa.net/detail/BIM-1099605
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1099605
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر