A metaclassifier that selecting a mid-point threshold on the probability output by a Classifier
The midpoint threshold is set so that a given performance measure is optimized.Currently this is the F-measure.
Performance is measured either on the training data, a hold-out set or using cross-validation.In addition, the probabilities returned by the base learner can have their range expanded so that the output probabilities will reside between 0 and 1 (this is useful if the scheme normally produces probabilities in a very narrow range).
(based on WEKA 3.7)
For further options, click the 'More' - button in the dialog.
All weka dialogs have a panel where you can specify classifier-specific parameters.
- Type: Data Training data
- Type: Weka 3.7 Classifier Trained model