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Analysis of data mining techniques f...

Kadambi, Rupasri R.

Analysis of data mining techniques for customer segmentation and predictive modeling: A case study.

紀錄類型:	書目-電子資源 : 單行本
正題名/作者:	Analysis of data mining techniques for customer segmentation and predictive modeling: A case study./
作者:	Kadambi, Rupasri R.
面頁冊數:	143 p.
附註:	Source: Masters Abstracts International, Volume: 44-04, page: 1953.
Contained By:	Masters Abstracts International44-04.
標題:	Engineering, Industrial. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1432085
ISBN:	9780542499807

Analysis of data mining techniques for customer segmentation and predictive modeling: A case study.
Kadambi, Rupasri R.

Analysis of data mining techniques for customer segmentation and predictive modeling: A case study. - 143 p.

Source: Masters Abstracts International, Volume: 44-04, page: 1953.

Thesis (M.S.)--State University of New York at Binghamton, 2005.

The objective of this research is to build a predictive model that can predict customer behavior, based on other attributes of the customer. The data used for this research belongs to Company ABC, a financial services company. Based on the behavior predicted, customers would then be segmented into different groups. Each group would then be approached with a customized marketing strategy, to increase business. Several statistical techniques like correlation and principal component analysis were employed to first analyze the data, reduce the data set and build predictive models. A comparison was carried out between Clustering and Neural network models, to determine the most suitable model for the current scenario. It was observed that in spite of high percentage error, clustering is more favorable than neural network, due to its approach in segmenting data into various groups. (Abstract shortened by UMI.)

ISBN: 9780542499807Subjects--Topical Terms:

170926
Engineering, Industrial.

Analysis of data mining techniques for customer segmentation and predictive modeling: A case study.
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