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Journals / Balkan Journal of Electrical and Computer Engineering / 2015 / Cilt: 3

Establishing the Potential Clients Using Artificial Neural Networks

Ziynet PAMUK
Yüksel YURTAY
Oğuz YAVUZYILMAZ
Pages
219–224
Publication Date
2015-12-30
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Feed forward neural network yielded the best result with an accuracy rate of 95.74%.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Today, technologies retrieving forward-looking information from the existing data are available.
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Key Findings & Data:The data set collected from 4.512 subjects consists of 16 input attributes (job, age, balance, etc.) and 1 output attribute (yes/no).
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Conclusion & Impact:Feed forward neural network yielded the best result with an accuracy rate of 95.74%.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Bank data · deposit · artificial neural network

Abstract

Today, technologies retrieving forward-looking information from the existing data are available. In this study, whether the clients would open a deposit account was estimated using the data in the marketing campaign of a bank in Portugal for its clients. The purpose of the study was to create a decision support system to determine the potential clients in future. The data set collected from 4.512 subjects consists of 16 input attributes (job, age, balance, etc.) and 1 output attribute (yes/no). In the study, the 6-fold cross validation method was used. The data obtained from 3.760 people were used for the training process and the data obtained from 752 people were used for the testing process. As classifiers; Feed Forward Neural Networks (FFNN), Probabilistic Neural Network (PNN) and k Nearest Neighbor (kNN) were used. At the end of the study, success ratios of different algorithms were compared by Receiver Operating Characteristics (ROC) analysis method. Feed forward neural network yielded the best result with an accuracy rate of 95.74%.

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Cite This Article

PAMUK, Z., YURTAY, Y., YAVUZYILMAZ, O. (2015). Establishing the Potential Clients Using Artificial Neural Networks. Balkan Journal of Electrical and Computer Engineering, Cilt: 3, 219–224. https://ajindex.com/articles/473265

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