Predicting credit card customer churn using support vector machine based on Bayesian optimization

Kamil Demirberk ÜNLÜ

doi:https://doi.org/10.31801/cfsuasmas.899206

Makale detayları

Predicting credit card customer churn using support vector machine based on Bayesian optimization

Yazarlar:

Kamil Demirberk ÜNLÜ

Yayıncı:

Ankara University

Ana Başlıklar:

Olasılıklar ve uygulamalı matematik

Dergi:

Communications Faculty of Sciences University of Ankara Series A1 Mathematics and Statistics 2021 Vol.70 Issue 2, pp.827-836

Belge Tipi:

Makale

Yayın Tarihi:

12/2021

Belge Dili:

İngilizce

Document ID (Org No.):

2000908901

Sıklık:

Üç Aylık

eISSN:

2618-6470

pISSN:

1303-5991

DOI:

https://doi.org/10.31801/cfsuasmas.899206

Özet:

 

In this study, we have employed a hybrid machine learning algorithm to predict customer credit card churn. The proposed model is Support Vector Machine (SVM) with Bayesian Optimization (BO). BO is used to optimize the hyper-parameters of the SVM. Four different kernels are utilized. The hyper-parameters of the utilized kernels are calculated by the BO. The prediction power of the proposed models are compared by four different evaluation metrics. Used metrics are accuracy, precision, recall and F1-score. According to each metrics linear kernel has the highest performance. It has accuracy of %91. The worst performance achieved by sigmoid kernel which has accuracy
of %84.

Makale detayları

Predicting credit card customer churn using support vector machine based on Bayesian optimization

Yazarlar: Kamil Demirberk ÜNLÜ

Yayıncı: Ankara University

Ana Başlıklar: Olasılıklar ve uygulamalı matematik

Dergi: Communications Faculty of Sciences University of Ankara Series A1 Mathematics and Statistics 2021 Vol.70 Issue 2, pp.827-836

Belge Tipi: Makale

Yayın Tarihi: 12/2021

Belge Dili: İngilizce

Document ID (Org No.): 2000908901

Sıklık: Üç Aylık

eISSN: 2618-6470

pISSN: 1303-5991

DOI: https://doi.org/10.31801/cfsuasmas.899206

Sayı

Yazarlar:

Kamil Demirberk ÜNLÜ

Yayıncı:

Ankara University

Ana Başlıklar:

Olasılıklar ve uygulamalı matematik

Dergi:

Communications Faculty of Sciences University of Ankara Series A1 Mathematics and Statistics 2021 Vol.70 Issue 2, pp.827-836

Belge Tipi:

Makale

Yayın Tarihi:

12/2021

Belge Dili:

İngilizce

Document ID (Org No.):

2000908901

Sıklık:

Üç Aylık

eISSN:

2618-6470

pISSN:

1303-5991

DOI:

https://doi.org/10.31801/cfsuasmas.899206