Abstract
Mobile call drop is a big concern for all telecommunications operators. In telecommunications, a cell phone call drop is a condition where calls have been cut off before the speakers have ended their conversation tone and before one of them has hung up. Therefore, the goal of this research is to design a predictive model that can estimate the mobile call drop data set of the mobile network. In order to address the disadvantage of simple statistical approaches, we have proposed and used data mining techniques, methods and methodologies in this study. In this paper, we propose a decision tree based on the mobile call drop data classification and prediction method. Experimental research is also being performed to test the proposed technique.
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