Wrapper classifier that addresses incompatible training and test data by building a mapping between the training data that a classifier has been built with and the incoming test instances' structure
Model attributes that are not found in the incoming instances receive missing values, so do incoming nominal attribute values that the classifier has not seen before.A new classifier can be trained or an existing one loaded from a file.
(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.