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

DOI10.31801/cfsuasmas.899206zbMath1489.62378OpenAlexW3205303611MaRDI QIDQ5083788

Kamil Demirberk Ünlü

Publication date: 21 June 2022

Published in: Communications Faculty Of Science University of Ankara Series A1Mathematics and Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.31801/cfsuasmas.899206

zbMATH Keywords

machine learningsupport vector machinechurn analysishyper-parameter optimization

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Learning and adaptive systems in artificial intelligence (68T05)

Uses Software

• Spearmint

Cites Work

• Unnamed Item
• Support-vector networks
• Forecasting stock market movement direction with support vector machine
• A two-step machine learning approach to predict S&P 500 bubbles

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