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Abd El-Aziz, Rasha M.
- Speedy Algorithm for Clustering Imbalanced Data
Abstract Views :177 |
PDF Views:2
Authors
Affiliations
1 Department of Computer Science, Assiut University, EG
1 Department of Computer Science, Assiut University, EG
Source
Data Mining and Knowledge Engineering, Vol 7, No 2 (2015), Pagination: 82-88Abstract
Fast Balanced K-means (FBK-means) clustering approach is one of the most important consideration when one want to solve clustering problem of balanced data. Mostly, numerical experiments show that FBK-means is faster and more accurate than the K-means algorithm, Genetic Algorithm, and Bee algorithm. FBK-means Algorithm needs few distance calculations and fewer computational time while keeping the same clustering results. However, the FBK-means algorithm doesn't give good results with imbalanced data. To resolve this shortage, a more efficient clustering algorithm, namely Fast K-means (FK-means), developed in this paper. This algorithm not only give the best results as in the FBK-means approach but also needs lower computational time in case of imbalance data.Keywords
Clustering, K-Means Algorithm, Bee Algorithm, Genetic Algorithm, FBK-Means Algorithm, FK-Means Algorithm.- Data Classification Based on GEPSVM Using Backtracking Search Algorithm
Abstract Views :175 |
PDF Views:2
Authors
Affiliations
1 Computer Science Department, Assiut University, EG
1 Computer Science Department, Assiut University, EG