Package autoweka.instancegenerators

Class Summary
CrossValidation Splits the training data up into CV folds with a given seed.
Default The most lame of InstanceGenerators, does nothing
MultiLevel Experimental InstanceGenerator that takes as input a child classifier, and creates multiple levels of training data.
RandomSubSampling Experimental InstanceGenerator that splits the data up into random folds, with a fixed percentage used for training instanceGeneratorArguments: A property string with the following startingseed - the initial seed of the splits numsamples - the number of folds to gererate percent - the percentage of data to use in the training set bias - the bias towards a uniform partition instance string format: seed - the seed used to split up data percent - the percentage of data to use in the training set bias - the bias towards a uniform partition
TerminationHoldout Experimental InstanceGenerator that takes as input a child classifier, and holds back a bunch of data as a 'Termination' set from the SMBO methods.