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FPT University|e-Resources > Đồ án tốt nghiệp (Dissertations) > Khoa học máy tính >
Please use this identifier to cite or link to this item: /handle/123456789/3324

Title: Potential Customers Prediction in Bank Telemarketing
Authors: Le, Dinh Huynh
Phung, Thai Duong
Khuat, Duy Bach
Keywords: Computer Science
Data Mining
Bank Telemarketing
Response Coding
K-Nearest-Neighbor classifier
Issue Date: 2022
Publisher: FPTU Ha Noi
Abstract: Data mining plays a vital role in the success of direct marketing campaigns by predicting which leads subscribe to a term deposit. This thesis is accomplished to illustrate with practical mining methods that the data is related to a Portuguese banking institution's direct marketing campaigns (phone calls). The algorithms are used: K-Nearest Neighbor, Logistic Regression, Linear Supported Vector Machines, and Extreme Gradient Boosting to classify potential customers for long-term deposits finance products. Response coding is used to vectorize categorical data while solving a machine learning classification problem. Accuracy and AUC scores are key metrics to evaluate performance. We inherited selecting important features from previous research. Our thesis employed a better method by combining response coding techniques with practical algorithms in an unbalanced dataset. The best prediction model achieved 91.07% and 0.9324 of accuracy and AUC score, significantly higher than the prior of 79% and 0.8 respectively
URI: /handle/123456789/3324
Appears in Collections:Khoa học máy tính

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