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PCFA : mining of projected clusters in high dimensional data using modified FCM algorithm
المؤلفون المشاركون
Murugappan, Ilango
Vasudev, Mohan
المصدر
The International Arab Journal of Information Technology
العدد
المجلد 11، العدد 2 (31 مارس/آذار 2014)9ص.
الناشر
تاريخ النشر
2014-03-31
دولة النشر
الأردن
عدد الصفحات
9
التخصصات الرئيسية
تكنولوجيا المعلومات وعلم الحاسوب
الملخص EN
Data deals with the specific problem of partitioning a group of objects into a fixed number of subsets, so that the similarity of the objects in each subset is increased and the similarity across subsets is reduced.
Several algorithms have been proposed in the literature for clustering, where k-means clustering and Fuzzy C-Means (FCM) clustering are the two popular algorithms for partitioning the numerical data into groups.
But, due to the drawbacks of both categories of algorithms, recent researches have paid more attention on modifying the clustering algorithms.
In this paper, we have made an extensive analysis on modifying the FCM clustering algorithm to overcome the difficulties possessed by the K-means and FCM algorithms over high dimensional data.
According to, we have proposed an algorithm, called Projected Clustering based on FCM Algorithm (PCFA).
Here, we have utilized the standard FCM clustering algorithm for sub-clustering high dimensional data into reference centroids.
The matrix containing the reference values is then fed as an input to the modified FCM algorithm.
Finally, experimentation is carried out on the very large dimensional datasets obtained from the benchmarks data repositories and the performance of the PCFA algorithm is evaluated with the help of clustering accuracy, memory usage and the computation time.
The evaluation results showed that, the PCFA algorithm shows approximately 20 % improvement in the execution time and 50 % improvement in memory usage over the PCKA algorithm.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Murugappan, Ilango& Vasudev, Mohan. 2014. PCFA : mining of projected clusters in high dimensional data using modified FCM algorithm. The International Arab Journal of Information Technology،Vol. 11, no. 2.
https://search.emarefa.net/detail/BIM-334224
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Murugappan, Ilango& Vasudev, Mohan. PCFA : mining of projected clusters in high dimensional data using modified FCM algorithm. The International Arab Journal of Information Technology Vol. 11, no. 2 (Mar. 2014).
https://search.emarefa.net/detail/BIM-334224
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Murugappan, Ilango& Vasudev, Mohan. PCFA : mining of projected clusters in high dimensional data using modified FCM algorithm. The International Arab Journal of Information Technology. 2014. Vol. 11, no. 2.
https://search.emarefa.net/detail/BIM-334224
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-334224
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
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