Field-aware Calibration: A Simple and Empirically Strong Method for Reliable Probabilistic Predictions

WWW '20: The Web Conference 2020 Taipei Taiwan April, 2020, pp.729-739, (2020)

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Abstract:

It is often observed that the probabilistic predictions given by a machine learning model can disagree with averaged actual outcomes on specific subsets of data, which is also known as the issue of miscalibration. It is responsible for the unreliability of practical machine learning systems. For example, in online advertising, an ad can r...More

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