@article {10.3844/jcssp.2016.31.38,
article_type = {journal},
title = {Adaptive Classification Method Based on Data Decomposition},
author = {Khedr, Ayman E. and Idrees, Amira M. and El Seddawy, Ahmed I.},
volume = {12},
number = {1},
year = {2016},
month = {Feb},
pages = {31-38},
doi = {10.3844/jcssp.2016.31.38},
url = {https://thescipub.com/abstract/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.},
journal = {Journal of Computer Science},
publisher = {Science Publications}
}