Abstract

Clustering technique is used to put similar data items in a same group. K-mean clustering is a commonly used approach in clustering technique which is based on initial centroids selected randomly. However, the existing method does not consider the data preprocessing which is an important task before executing the clustering among the different database. This study proposes a new approach of k-mean clustering algorithm. Experimental analysis shows that the proposed method performs well on infectious disease data set when compare with the conventional k-means clustering method.

Keywords:

Infectious diseases , k-means clustering, principal component analysis, principal components, standardization,

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Competing interests

The authors have no competing interests.

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The authors have no competing interests.