Optimal Clustering Method Based on Genetic Algorithm

  • Satish Gajawada
  • Durga Toshniwal
  • Nagamma Patil
  • Kumkum Garg
Conference paper
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 131)

Abstract

Clustering methods divide the dataset into groups called clusters such that the objects in the same cluster are more similar and objects in the different clusters are dissimilar. Clustering algorithms can be hierarchical or partitional. Partitional clustering methods decompose the dataset into set of disjoint clusters. Most partitional approaches assume that the number of clusters are known a priori. Moreover, they are sensitive to initialization. Hierarchical clustering methods produce a complete sequence of clustering solutions, either from singleton clusters to a cluster including all individuals or vice versa. Hierarchical clustering can be represented by help of a dendrogram that can be cut at different levels to obtain different number of clusters of corresponding granularities. If dataset has large multilevel hierarchies then it becomes difficult to determine optimal clustering by cutting the dendrogram at every level and validating clusters obtained for each level. Genetic Algorithms (GAs) have proven to be a promising technique for solving complex optimization problems. In this paper, we propose an Optimal Clustering Genetic Algorithm (OCGA) to find optimal number of clusters. The proposed method has been applied on some artificially generated datasets. It has been observed that it took less number of iterations of cluster validation to arrive at optimal number of clusters.

Keywords

Genetic algorithm hierarchical clustering optimal clusters dendrogram 

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Copyright information

© Springer India Pvt. Ltd. 2012

Authors and Affiliations

  • Satish Gajawada
    • 1
  • Durga Toshniwal
    • 1
  • Nagamma Patil
    • 1
  • Kumkum Garg
    • 2
  1. 1.Department of Electronics and Computer EngineeringIndian Institute of Technology RoorkeeRoorkeeIndia
  2. 2.Department of Computer Science and EngineeringManipal Institute of TechnologyManipalIndia

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