Zeitschrift für Informatik und Systembiologie

An Advanced Clustering Algorithm (ACA) for Clustering Large Data Set to Achieve High Dimensionality

Abstract

Amanpreet Kaur Toor, Amarpreet Singh and Amarpreet Singh

Cluster analysis method is one of the main analytical methods in data mining; this method of clustering algorithm will influence the clustering results directly. This paper proposes an Advanced Clustering Algorithm in order to solve the question of high dimensionality and large data set. The Advanced Clustering Algorithm method avoids computing the distance of each data object to the cluster centers again and again and save the running time. ACA requires a simple data structure to store information in every iteration, which is to be used in the next iteration. Experimental results show that the Advanced Clustering Algorithm method can effectively improve the speed of clustering and accuracy, reducing the computational complexity of the traditional algorithms (K-Means, SOM and HAC). This paper includes Advanced Clustering Algorithm (ACA) and its experimental results through experimenting with academic data sets.