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Journal of Applied Sciences
  Year: 2014 | Volume: 14 | Issue: 5 | Page No.: 426-435
DOI: 10.3923/jas.2014.426.435
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Swap Mechanism for Medical Clustering Problems

Anmar Abuhamdah, Rawnaq Kittaneh, Jawad Alkhatib and Mohd Zakree Ahmad Nazri

Clustering problem is an important area of data mining. The goal of the clustering is to partitioning N objects into K clusters with similar characteristics for one cluster and dissimilar to other clusters by using any algorithm to generate the initial clusters partition. This initial clusters quality will be measured based on a certain distance (or object) function. The initial partitioning can be improve by iteratively explores its neighbor solutions looking for a better one by any algorithm. The neighbor’s solutions are achieved by reallocating some patters (objects) by using any neighborhoods structures. However, the way of employing the neighborhoods structures will affects the solution quality. Therefore, in this work, a swap mechanism is proposed to increase the diversification for the neighborhood structure. The proposed mechanism tested on two algorithms previously implemented over six medical clustering problem (that are available in UCI Machine Learning Repository) by using two way of the distance calculation. This work, also present a third distance calculation to minimize the distances between the clusters. Experimental results show that, using the swap mechanism and the third distance function on the algorithms is able to produce significantly better quality solutions than not using it on all datasets.
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How to cite this article:

Anmar Abuhamdah, Rawnaq Kittaneh, Jawad Alkhatib and Mohd Zakree Ahmad Nazri, 2014. Swap Mechanism for Medical Clustering Problems. Journal of Applied Sciences, 14: 426-435.

DOI: 10.3923/jas.2014.426.435






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