Hybrid Hierarchical Clustering (KH): Cluster Assessment via Rand index.
Publish place: 5th International Conference on knowledge based research in Computer engineering and Information Technology
Publish Year: 1396
نوع سند: مقاله کنفرانسی
زبان: English
View: 371
This Paper With 6 Page And PDF and WORD Format Ready To Download
- Certificate
- من نویسنده این مقاله هستم
استخراج به نرم افزارهای پژوهشی:
شناسه ملی سند علمی:
COMCO04_131
تاریخ نمایه سازی: 17 آبان 1396
Abstract:
This paper introduces a hybrid hierarchical clustering method, this method has several computational advantages over agglomerative hierarchical clustering approach for it uses centroids rather than raw data points. It reduces the sample space for building the hierarchy and hence requires fewer resources. In order to evaluate the hybrid algorithm, it is compared with the standard algorithm in terms of time and accuracy on generating data with different distributions (i.e., uniform and normal) and Chess data sets from the UCI repository for single hierarchical and average hierarchical with Euclidean and Manhattan distances.in this paper, we Determine the number of clusters by using ratio from 0.1 to 0.9 from the total number of original data. And also, we used the external (Rand index) criteria with the purposes to evaluate the results obtained from hybrid hierarchical clustering and standard hierarchical clustering.
Authors
Zahraa Radhi Waad
Faculty of Mathematics and Computer Science, Amirkabir University of Technology, Tehran,Iran
M E.SHIRI
Faculty of Mathematics and Computer Science, Amirkabir University of Technology, Tehran,Iran.
A Mohammadpour
Faculty of Mathematics and Computer Science, Amirkabir University of Technology, Tehran,Iran