Optimize Threshold (Subprocess)
Synopsis
This operator evaluates different thresholds and delivers a model with the best threshold attached.
Description
When solving a classification task one derives confidences for each class. By default, RapidMiner assigns the prediction to the class with the highest confidence. Therefore, in a binominal classification the prediction is set to the class which has a confidence larger than 0.5. This operator automatically applies thresholds between 0 and 1.0 to receive the threshold which results in the highest performance. The performance measure is calculated using the inner process.
Input
exa
The ExampleSet you want the thresholds to be optimized on.
mod
The model for scoring. It is not mandatory to provide a model, but recommended to get a GroupedModel as result. If you do not provide a model the ExampleSet at the exa input port needs to be scored already (have a prediction attribute).
Output
exa
The scored example set with the best thresholds applied.
mod
If you provide a model as an input, you will receive a GroupedModel with the original Model and the Threshold Model combined. You can use this to score new data and apply the threshold at the same time. If you do not provide a model you will only get the threshold model. This threshold model can be applied using Apply Model.
per
The performance of the best threshold.