@article{(Open Science Index):https://publications.waset.org/pdf/13879, title = {Generating Normally Distributed Clusters by Means of a Self-organizing Growing Neural Network– An Application to Market Segmentation –}, author = {Reinhold Decker and Christian Holsing and Sascha Lerke}, country = {}, institution = {}, abstract = {This paper presents a new growing neural network for cluster analysis and market segmentation, which optimizes the size and structure of clusters by iteratively checking them for multivariate normality. We combine the recently published SGNN approach [8] with the basic principle underlying the Gaussian-means algorithm [13] and the Mardia test for multivariate normality [18, 19]. The new approach distinguishes from existing ones by its holistic design and its great autonomy regarding the clustering process as a whole. Its performance is demonstrated by means of synthetic 2D data and by real lifestyle survey data usable for market segmentation.}, journal = {International Journal of Economics and Management Engineering}, volume = {2}, number = {2}, year = {2008}, pages = {137 - 143}, ee = {https://publications.waset.org/pdf/13879}, url = {https://publications.waset.org/vol/14}, bibsource = {https://publications.waset.org/}, issn = {eISSN: 1307-6892}, publisher = {World Academy of Science, Engineering and Technology}, index = {Open Science Index 14, 2008}, }