Classification in Marketing Research by Means of LEM2-generated Rules

Decker R, Kroll F (2007)
In: Advances in Data Analysis. Decker R, Lenz H-J (Eds); Berlin: Springer: 425-432.

Download
Es wurde kein Volltext hochgeladen. Nur Publikationsnachweis!
Konferenzbeitrag | Veröffentlicht | Englisch
Herausgeber
;
Abstract / Bemerkung
The vagueness and uncertainty of data is a frequent problem in marketing research. Since rough sets have already proven their usefulness in dealing with such data in other domains like medicine (Ohrn 1999) and image processing (Pawlak et al. 1995), the question arises, whether they are a useful alternative to the more popular fuzzy sets for marketing research as well. In the present (more technical) paper we discuss the pros and cons of the LEM2 (Learning from Examples Module Version 2) algorithm in this respect. Beyond that its efficiency will be demonstrated by solving two marketing-related classification problems. The main objective is to show that the LEM2 algorithm is an adequate tool for marketing research which deserves much more attention as it is the case so far. Therefore, we also investigate the reasons for the obvious ignoring of rough sets in the marketing literature to date. The implementation of the LEM2 algorithm, which we use in the empirical part of our paper, is part of the data mining system LERS (Learning from Examples based on Rough Sets) which was introduced in the early nineties by Grzymala-Busse (1992) and modified in 1997 by the same author. It generates the smallest set of minimal rules of a decision class by means of rough sets. Therefore, as we will show, the LEM2 algorithm is suited to efficiently generate classification rules for decision making in (new) customer selection for instance.
Erscheinungsjahr
Titel des Konferenzbandes
Advances in Data Analysis
Seite
425-432
ISSN
PUB-ID

Zitieren

Decker R, Kroll F. Classification in Marketing Research by Means of LEM2-generated Rules. In: Decker R, Lenz H-J, eds. Advances in Data Analysis. Berlin: Springer; 2007: 425-432.
Decker, R., & Kroll, F. (2007). Classification in Marketing Research by Means of LEM2-generated Rules. In R. Decker & H. - J. Lenz (Eds.), Advances in Data Analysis (pp. 425-432). Berlin: Springer. doi:10.1007/978-3-540-70981-7_48
Decker, R., and Kroll, F. (2007). “Classification in Marketing Research by Means of LEM2-generated Rules” in Advances in Data Analysis, Decker, R., and Lenz, H. - J. eds. (Berlin: Springer), 425-432.
Decker, R., & Kroll, F., 2007. Classification in Marketing Research by Means of LEM2-generated Rules. In R. Decker & H. - J. Lenz, eds. Advances in Data Analysis. Berlin: Springer, pp. 425-432.
R. Decker and F. Kroll, “Classification in Marketing Research by Means of LEM2-generated Rules”, Advances in Data Analysis, R. Decker and H.-J. Lenz, eds., Berlin: Springer, 2007, pp.425-432.
Decker, R., Kroll, F.: Classification in Marketing Research by Means of LEM2-generated Rules. In: Decker, R. and Lenz, H.-J. (eds.) Advances in Data Analysis. p. 425-432. Springer, Berlin (2007).
Decker, Reinhold, and Kroll, Frank. “Classification in Marketing Research by Means of LEM2-generated Rules”. Advances in Data Analysis. Ed. R. Decker and H.-J. Lenz. Berlin: Springer, 2007. 425-432.

Export

Markieren/ Markierung löschen
Markierte Publikationen

Open Data PUB

Suchen in

Google Scholar