NDLI: Predicting the characteristics of people living in the South USA using logistic regression and decision tree

Content Provider	IEEE Xplore Digital Library
Author	Serban, R. Kupraszewicz, A. Gongzhu Hu
Copyright Year	2011
Description	Author affiliation: Department of Computer Science, Central Michigan University (Serban, R.; Kupraszewicz, A.; Gongzhu Hu)
Abstract	Analysis of social data is at the core of social studies and an important application area of data mining and knowledge discovery. One aspect of such social data analysis is based on demographic and/or economic data. In this paper, we apply data mining techniques to find the characteristics of people living in the south of USA. The data used in our study is the WAGE2 data set with 935 observations that has been used in some previous social study research. The software tool SAS Enterprise Miner was used to analyze the data, particularly the regression and decision tree models. The results of our analysis show that the decision tree model produced a better variable selection than the logistic regression model did to predict if a person is likely to live in the south than the logistic regression model, at least from the given data set.
Starting Page	688
Ending Page	693
File Size	556751
Page Count	6
File Format	PDF
ISBN	9781457704352
e-ISBN	9781457704345
e-ISBN	9781457704338
DOI	10.1109/INDIN.2011.6034974
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-07-26
Publisher Place	Portugal
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Economics Analytical models decision tree Biological system modeling demographic and economic data analysis Data models Social informatics logistic regression Regression tree analysis Logistics
Content Type	Text
Resource Type	Article

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