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Using independent component analysis for feature extraction and multivariate data projection

Weingessel, Andreas and Natter, Martin and Hornik, Kurt (1998) Using independent component analysis for feature extraction and multivariate data projection. Working Papers SFB "Adaptive Information Systems and Modelling in Economics and Management Science", 16. SFB Adaptive Information Systems and Modelling in Economics and Management Science, WU Vienna University of Economics and Business, Vienna.

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Abstract

Deriving low-dimensional perceptual spaces from data consisting of many variables is of crucial interest in strategic market planning. A frequently used method in this context is Principal Components Analysis, which finds uncorrelated directions in the data. This methodology which supports the identification of competitive structures can gainfully be utilized for product (re)positioning or optimal product (re)design. In our paper, we investigate the usefulness of a novel technique, Independent Component Analysis, to discover market structures. Independent Component Analysis is an extension of Principal Components Analysis in the sense that it looks for directions in the data that are not only uncorrelated but also independent. Comparing the two approaches on the basis of an empirical data set, we find that Independent Component Analysis leads to clearer and sharper structures than Principal Components Analysis. Furthermore, the results of Independent Component Analysis have a reasonable marketing interpretation.

Item Type: Paper
Keywords: Faktorenanalyse / Multivariate Daten / Projektionsverfahren
Divisions: Departments > Finance, Accounting and Statistics > Statistics and Mathematics
Departments > Informationsverarbeitung u Prozessmanag. > Informationswirtschaft
Departments > Informationsverarbeitung u Prozessmanag. > Produktionsmanagement > Taudes
Departments > Marketing > Service Marketing und Tourismus
Depositing User: Repository Administrator
Date Deposited: 07 Mar 2002 17:26
Last Modified: 27 Feb 2017 11:24
URI: http://epub.wu.ac.at/id/eprint/1424

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