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Modeling Data Mining Applications for Prediction of Prepaid Churn in Telecommunication Services

Goran Kraljević ; HT Mostar, Mostar, Bosna i Hercegovina
Sven Gotovac orcid id orcid.org/0000-0002-5014-5000 ; Fakultet elektrotehnike, strojarstva i brodogradnje Sveučilišta u Splitu, Split, Hrvatska


Puni tekst: hrvatski pdf 1.415 Kb

str. 275-283

preuzimanja: 6.768

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Sažetak

This paper defines an advanced methodology for modeling applications based on Data Mining methods that represents a logical framework for development of Data Mining applications. Methodology suggested here for Data Mining modeling process has been applied and tested through Data Mining applications for predicting Prepaid users churn in the telecom industry. The main emphasis of this paper is defining of a successful model for prediction of potential Prepaid churners, in which the most important part is to identify the very set of input variables that are high enough to make the prediction model precise and reliable. Several models have been created and compared on the basis of different Data Mining methods and algorithms (neural networks, decision trees, logistic regression). For the modeling examples we used WEKA analysis tool.

Ključne riječi

Data Mining applications; Prepaid churn model; Neural networks; Decision trees; Logistic regression

Hrčak ID:

61550

URI

https://hrcak.srce.hr/61550

Datum izdavanja:

30.9.2010.

Podaci na drugim jezicima: hrvatski

Posjeta: 8.205 *