PREDICTIVE MODELING OF CLICK-THROUGH RATES: A REGRESSION ANALYSIS APPROACH

Authors

  • Suleyman Suleymanzade Institute of Information Technology, Baku, Azerbaijan Author

DOI:

https://doi.org/10.32010/26166127.2023.6.2.199.202

Keywords:

Data Splitting, XGBoost, CTR-related, CTR Prediction

Abstract

This research uses advanced regression techniques to develop a robust predictive model for Click-Through Rates (CTR) in online advertising. The study leverages a diverse dataset encompassing various advertising campaigns and user interactions to uncover patterns and relationships influencing click-through behavior. The goal is to provide advertisers with a tool for accurate CTR prediction, enabling them to optimize campaigns and allocate resources effectively.

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References

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Published

2023-12-31

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