盈利能力指数
朴素贝叶斯分类器
决策树
电话
计算机科学
直接营销
机器学习
期限(时间)
人工智能
营销
数据挖掘
支持向量机
业务
财务
哲学
物理
量子力学
语言学
出处
期刊:BCP business & management
[Boya Century Publishing]
日期:2023-01-13
卷期号:36: 285-290
标识
DOI:10.54691/bcpbm.v36i.3444
摘要
The research on machine leaning method for bank marketing has become a widely discussed topic. To obtain precise performances for bank marketing, KNN algorithm is utilized in this paper to forecast the success rate of telemarketing that focuses on whether a prospect will agree to a term deposit if a phone call is placed. The comparison experiments with three other machine learning models (Decision Tree, Random Forrest, and Naive Bayes) by using real data from a Portuguese banking institution revealed that KNN achieved the highest Accuracy (89.45 percent) and Precision (61.76 percent), thus proving the effectiveness of KNN. The proposed prediction method can also be adapted to operate within many other situations, creating a template when faced with the issue of direct marketing such as the increasing of the efficiency and profitability of telemarketing.
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