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Student
Title
Supervisor
Faculty
Educational Programme
Final Grade
Year of Graduation
Sogdiana Gafurova
Determining Individual Credit Limits for Mobile Telecommunication Subscribers
2019
The development of methods of data recording and storage has led to a rapid growth in the volume of collected and analyzed information. Over the years, telecommunications companies have collected impressive amounts of data about their customers, which allows them to use them to build various forecasting models. One of the tasks that can now be solved more efficiently thanks to the availability of data is the provision of a trust payment.

The purpose of this study is to develop an effective model for predicting the return of the trust payment by subscribers, by analyzing their profile.

As a result of the study on the basis of the collected data, it was possible to build an effective model for predicting the return of the trust payment. A new quality metric has been introduced that takes into account the economic benefits of the correct classification of objects. The use of the new reward ratio metric on cross-validation made it possible to optimize the hyperparameters of the algorithms in such a way that the expected economic effect from the application of such a model was maximized.

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