Predicting Good Probabilities With Supervised Learning

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predicting well-calibrated probabilities prior to calibration, but after calibration the best methods are boosted trees, ran-dom forests and SVMs. 2. Calibration Methods In this section we describe the two methods for mapping model predictions to posterior probabilities: Platt Calibra-tion and Isotonic Regression. Unfortunately, these methods

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