- Author
- Owczarczuk Marcin (Szkoła Główna Handlowa w Warszawie)
- Title
- Segmentation Model with Respect to the Difference in Means
- Source
- Roczniki Kolegium Analiz Ekonomicznych / Szkoła Główna Handlowa, 2007, nr 17, s. 285-296, rys., bibliogr. 6 poz.
- Issue title
- Discovering patterns in economic data
- Keyword
- Segmentacja
Segmentation - Note
- summ.
- Abstract
- The aim of the paper is to formulate and solve the following segmentation problem. Given is a population described by independent variables: Xl,..., Xn, (both continuous and categorical), the continuous dependent variable Y and the two-level categorical variable a with levels a = 1 and a = 0. Ya=1 and Ya=0 are the means of Y for observations at levels a = 1 and a = 0 , respectively. The goal is to create the segments of the population, described by the independent variables, that the difference in means Ya=1 - Ya=0 is the feature that distinguishes the segments. I. e. the means should be as different as possible between segments and should be similar within the segment. The solution is based on regression trees approach. (original abstract)
- Accessibility
- The Main Library of the Cracow University of Economics
The Library of Warsaw School of Economics
The Library of University of Economics in Katowice
The Main Library of Poznań University of Economics and Business
The Main Library of the Wroclaw University of Economics - Bibliography
-
- Breiman L., Friedman J.H., Olshen R.A., Stone C.J., Classification and regresion trees, Wadsworth, Belmont CA, 1984.
- Ćwik J., Koronacki J., Statystyczne systemy uczące się, WNT, Warszawa 2005.
- Faraway J., Practical Regerssion and Anova using R, 2002, http//cran.r-project.org/doc/contrib/Faraway-PRA.pgf
- Koronacki J., Mielniczuk J., Statystyka dla studentów kierunków technicznych i przyrodniczych, WNT, Warsaw 2001.
- Nong Ye.(red.), The handbook of data mining, Lawrance Erlbaum Associates Mahwah 2003.
- Wang Y., Witten I.H., Induction of model trees for predicting continuous classes, Proc European Conference on Machine Learning Poster Papers, pp.128-137, Prague 1997.
- Cited by
- ISSN
- 1232-4671
- Language
- eng
