Uses of Interface
weka.classifiers.evaluation.Prediction

Packages that use Prediction

Package	Description
weka.classifiers
weka.classifiers.evaluation
weka.classifiers.evaluation.output.prediction
weka.gui.visualize.plugins

Uses of Prediction in weka.classifiers

Methods in weka.classifiers that return types with arguments of type Prediction

Modifier and Type	Method	Description
ArrayList<Prediction>	Evaluation.predictions()	Returns the predictions that have been collected.

Uses of Prediction in weka.classifiers.evaluation

Classes in weka.classifiers.evaluation that implement Prediction

Modifier and Type	Class	Description
class	NominalPrediction	Encapsulates an evaluatable nominal prediction: the predicted probability distribution plus the actual class value.
class	NumericPrediction	Encapsulates an evaluatable numeric prediction: the predicted class value plus the actual class value.

Methods in weka.classifiers.evaluation that return Prediction

Modifier and Type	Method	Description
Prediction	EvaluationUtils.getPrediction(Classifier classifier, Instance test)	Generate a single prediction for a test instance given the pre-trained classifier.

Methods in weka.classifiers.evaluation that return types with arguments of type Prediction

Modifier and Type	Method	Description
ArrayList<Prediction>	EvaluationUtils.getCVPredictions(Classifier classifier, Instances data, int numFolds)	Generate a bunch of predictions ready for processing, by performing a cross-validation on the supplied dataset.
ArrayList<Prediction>	EvaluationUtils.getTestPredictions(Classifier classifier, Instances test)	Generate a bunch of predictions ready for processing, by performing a evaluation on a test set assuming the classifier is already trained.
ArrayList<Prediction>	EvaluationUtils.getTrainTestPredictions(Classifier classifier, Instances train, Instances test)	Generate a bunch of predictions ready for processing, by performing a evaluation on a test set after training on the given training set.
ArrayList<Prediction>	Evaluation.predictions()	Returns the predictions that have been collected.

Method parameters in weka.classifiers.evaluation with type arguments of type Prediction

Modifier and Type	Method	Description
void	ConfusionMatrix.addPredictions(ArrayList<Prediction> predictions)	Includes a whole bunch of predictions in the confusion matrix.
Instances	CostCurve.getCurve(ArrayList<Prediction> predictions)	Calculates the performance stats for the default class and return results as a set of Instances.
Instances	CostCurve.getCurve(ArrayList<Prediction> predictions, int classIndex)	Calculates the performance stats for the desired class and return results as a set of Instances.
Instances	MarginCurve.getCurve(ArrayList<Prediction> predictions)	Calculates the cumulative margin distribution for the set of predictions, returning the result as a set of Instances.
Instances	ThresholdCurve.getCurve(ArrayList<Prediction> predictions)	Calculates the performance stats for the default class and return results as a set of Instances.
Instances	ThresholdCurve.getCurve(ArrayList<Prediction> predictions, int classIndex)	Calculates the performance stats for the desired class and return results as a set of Instances.

Uses of Prediction in weka.classifiers.evaluation.output.prediction

Fields in weka.classifiers.evaluation.output.prediction declared as Prediction

Modifier and Type	Field	Description
Prediction	InMemory.PredictionContainer.prediction	the prediction.

Uses of Prediction in weka.gui.visualize.plugins

Method parameters in weka.gui.visualize.plugins with type arguments of type Prediction

Modifier and Type	Method	Description
JMenuItem	VisualizePlugin.getVisualizeMenuItem(ArrayList<Prediction> preds, Attribute classAtt)	Get a JMenu or JMenuItem which contain action listeners that perform the visualization, using some but not necessarily all of the data.