it.uniroma2.sag.kelp.predictionfunction

Interface PredictionFunction

All Known Subinterfaces:

Classifier, RegressionFunction

All Known Implementing Classes:

BinaryClassifier, BinaryKernelMachineClassifier, BinaryLinearClassifier, MultiLabelClassifier, OneVsAllClassifier, OneVsOneClassifier, SequencePredictionFunction, UnivariateKernelMachineRegressionFunction, UnivariateLinearRegressionFunction, UnivariateRegressionFunction

public interface PredictionFunction

It is a generic prediction function that can be learned with a machine learning algorithm

Author:

Simone Filice

Method Summary

Methods

Modifier and Type	Method and Description
List<Label>	getLabels() Returns the labels representing the concept to be predicted.
Model	getModel() Returns the model
Prediction	predict(Example example)
void	reset() Resets all the predictor parameters to the default state.
void	setLabels(List<Label> labels) Sets the labels representing the concept to be predicted.
void	setModel(Model model) Sets the model

Method Detail

predict

Prediction predict(Example example)

reset

void reset()

Resets all the predictor parameters to the default state. All the learned process is forgotten

setLabels

void setLabels(List<Label> labels)

Sets the labels representing the concept to be predicted.

Parameters:

labels - the labels representing the concept to be predicted

getLabels

List<Label> getLabels()

Returns the labels representing the concept to be predicted.

Returns:

the labels representing the concept to be predicted

getModel

Model getModel()

Returns the model

Returns:

model the model

setModel

void setModel(Model model)

Sets the model

Parameters:

model - the model to set