Adaptive Classification Method Based on Data Decomposition
- 1 Helwan University, Egypt
- 2 Fayoum University, Egypt
- 3 Arab Academy for Science Technology and Maritime Transport (AASTMT), Egypt
Copyright: © 2020 Ayman E. Khedr, Amira M. Idrees and Ahmed I. El Seddawy. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Knowledge discovery is one of the vital fields which strongly supports decision making by applying different techniques based on the targeted field and the required information. Focusing on clustering and classification techniques, this paper presents an approach for adapting one of the classification algorithms for supporting decision making procedure in radiology data analysis field. The proposed adaptation is based on dividing the analysis problem by data partitioning and individually examining against each cluster, with applying the classification algorithm in a parallel approach. The proposed approach has proved to produce higher results accuracy with minimization of time when compared with the traditional ID3.
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- Data Mining
- Supervised Learning