Jagdish Prasad* and Rahul Rajawat Pages 166 - 173 ( 8 )
Background: Cluster analysis is a data reduction technique in rows of the data matrix. This technique is widely used in engineering, biology, society, pattern recognition, and image processing.
Objective: In this paper, self organized map (SOM) using the artificial neural network and different statistical techniques of cluster analysis are used on Population data of 33 districts of Rajasthan with 9 variables for comparison purpose.
Methods: The goal of this work is to identify the most suitable technique for clustering the data by using the artificial neural network and different statistical clustering techniques. We received all patents regarding artificial neural network and k-means cluster method.
Results: In some situation, artificial neural network (ANN) self-organized map cluster analysis runs on software MATLAB 8.2.0 is more or less same with K-means Statistical cluster analysis using SPSS 7.0.
Conclusion: The k-means cluster analysis is found as good as Neural Network cluster analysis, whereas Hierarchical cluster analysis and two steps cluster analysis provide some variation from the neural network cluster analysis.
SOM, adaptive resonance theory, MATLAB, SPSS, cluster, artificial neural network.
Amity School of Applied Sciences, Amity University Rajasthan, Jaipur, Department of Statistics, University of Rajasthan, Jaipur