Research Article Open Access

Adaptive Classification Method Based on Data Decomposition

Ayman E. Khedr1, Amira M. Idrees2 and Ahmed I. El Seddawy3
  • 1 Helwan University, Egypt
  • 2 Fayoum University, Egypt
  • 3 Arab Academy for Science Technology and Maritime Transport (AASTMT), Egypt
Journal of Computer Science
Volume 12 No. 1, 2016, 31-38

DOI: https://doi.org/10.3844/jcssp.2016.31.38

Submitted On: 30 November 2015 Published On: 20 February 2016

How to Cite: Khedr, A. E., Idrees, A. M. & El Seddawy, A. I. (2016). Adaptive Classification Method Based on Data Decomposition. Journal of Computer Science, 12(1), 31-38. https://doi.org/10.3844/jcssp.2016.31.38

Abstract

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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Keywords

  • Data Mining
  • Supervised Learning
  • Classification
  • ID3