Synopsis
Turns confidence scores of boolean classifiers into probability estimates.
Description
A scaling operator, applying the original algorithm by Platt (1999) to turn confidence scores of boolean classifiers into probability estimates. Unlike the original version this operator assumes that the confidence scores are already in the interval of [0,1], as e.g. given for the RapidMiner boosting operators. The crude estimates are then transformed into log odds, and scaled by the original transformation of Platt. The operator assumes a model and an example set for scaling. It outputs a PlattScalingModel, that contains both, the supplied model and the scaling step. If the example set contains a weight attribute, then this operator is able to fit a model to the weighted examples.
Input
- example set: expects: ExampleSet
- prediction model: expects: Model
Output
- example set:
- model: