[Updated on Apr. 18] Integration of CiNii Articles into CiNii Research

Do the AUC and log-loss evaluate CTR prediction models properly?

DOI

Bibliographic Information

Other Title
  • CTR 予測モデルの評価に AUC や log-loss は適切か?

Abstract

<p>Click-through rate (CTR) prediction is one of the most important task for web advertising platform companies. However, CTR prediction is a non-standard machine learning task, so conventional metrics, for example, area under the Receiver Operating Characteristic curve (AUC), and log-loss, a.k.a. cross-entropy, and so on, can be improper. Our target is develop a new metrices for CTR prediction. In this article, we state the drawbacks of such conventional metrics and perspective of a metric based on the calibration plot approach.</p>

Journal

Citations (0)*help

See more

References(0)*help

See more

Related Articles

See more

Related Data

See more

Related Books

See more

Related Dissertations

See more

Related Projects

See more

Related Products

See more

Details

Report a problem

Back to top