Uses of Class
ace.datatypes.TrainedModel

Packages that use TrainedModel
ace   
ace.datatypes   
 

Uses of TrainedModel in ace
 

Methods in ace that return TrainedModel
 TrainedModel Coordinator.train(double max_class_membership_spread, double max_class_membership_count, boolean order_randomly, java.lang.String feature_selector, java.lang.String classifier_type, java.io.OutputStream out, int max_attribute, boolean verbose)
          Trains a Weka Classifier based on a set of sample Instances.
 

Methods in ace with parameters of type TrainedModel
 SegmentedClassification[] Coordinator.classify(java.lang.String results_file, TrainedModel trained)
          Classifies a set of instances with the given trained classifier.
static SegmentedClassification[] InstanceClassifier.classify(TrainedModel trained, DataBoard data_board, weka.core.Instances instances, java.lang.String results_file, boolean save_intermediate_arffs)
          Classify a set of instances using a trained Weka Classifier.
static weka.core.Instances InstanceClassifier.classifyInstances(TrainedModel trained, weka.core.Instances instances, boolean save_intermediate_arffs)
          Classifies a set of Weka Instances.
 java.lang.String CrossValidator.crossValidate(TrainedModel trained, CrossValidationResults[] cvres, weka.core.Instances instances, java.io.OutputStream out, java.lang.StringBuffer cv_results, java.lang.String file_name, java.lang.String feature_selector, boolean save_intermediate_arffs, boolean verbose, int i)
          Cross validates a set of Weka Instances.
 java.lang.String Coordinator.performDimensionalityReduction(TrainedModel trained, java.lang.String feature_selector, int max_attribute, java.io.OutputStream out, boolean verbose)
          Performs dimensionality reduction on a set of Weka Instances.
static void Experimenter.resetClassifier(TrainedModel trained)
          Instantiates a new instance of the Weka Classifier contained in the given TrainedModel.
static void Trainer.train(weka.core.Instances instances, TrainedModel trained)
          Trains the Weka Classifier contained in the given TrainedModel object based on the given traning Instances.
 

Uses of TrainedModel in ace.datatypes
 

Fields in ace.datatypes declared as TrainedModel
 TrainedModel CrossValidationResults.trained
          The serializable object containing reference to the Weka objects that were use for classification in this cross validation.
 

Methods in ace.datatypes with parameters of type TrainedModel
 SegmentedClassification[] DataBoard.getClassifiedResults(weka.core.Instances instances, boolean save_intermediate_arffs, TrainedModel trained, boolean use_top_level_features, boolean use_sub_section_features)
          Classify the given set of Instances using the given AttributeSelection and the given Classifier.