Using neural networks for marketing research data classification

Authors:
Jiri Stastny;Pavel Turcinek;Arnost Motycka
Affiliations:
Department of Informatics, Mendel University in Brno, Brno, Czech Republic;Department of Informatics, Mendel University in Brno, Brno, Czech Republic;Department of Informatics, Mendel University in Brno, Brno, Czech Republic
Venue:
MACMESE'11 Proceedings of the 13th WSEAS international conference on Mathematical and computational methods in science and engineering
Year:
2011

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Machine learning, neural and statistical classification

Machine learning, neural and statistical classification
Self-Organizing Maps

Self-Organizing Maps

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Abstract

This paper deals with problems of marketing research data classification by means of artificial Neural Networks algorithms. Two basic methods are described, classification with the aid of Multi-layer Perceptron neural network with Back-propagation algorithm and classification with the aid of Self-organizing (Kohonen's) maps. Finally, applicability of these algorithms is compared. These algorithms are applied over the data from a survey about consumer behavior in the food market in the Czech Republic. The limits of this approach are considered and possibilities of more complex structural recognition methods and semi-supervised learning utilization are suggested.