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A Method of Bank Telemarketing Customer Prediction based on Hybrid Sampling and Stacked Deep Networks

혼성 표본 추출과 적층 딥 네트워크에 기반한 은행 텔레마케팅 고객 예측 방법

  • 이현진 (숭실사이버대학교 ICT공학과)
  • Received : 2019.08.02
  • Accepted : 2019.09.03
  • Published : 2019.09.30

Abstract

Telemarketing has been used in finance due to the reduction of offline channels. In order to select telemarketing target customers, various machine learning techniques have emerged to maximize the effect of minimum cost. However, there are problems that the class imbalance, which the number of marketing success customers is smaller than the number of failed customers, and the recall rate is lower than accuracy. In this paper, we propose a method that solve the imbalanced class problem and increase the recall rate to improve the efficiency. The hybrid sampling method is applied to balance the data in the class, and the stacked deep network is applied to improve the recall and precision as well as the accuracy. The proposed method is applied to actual bank telemarketing data. As a result of the comparison experiment, the accuracy, the recall, and the precision is improved higher than that of the conventional methods.

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