org.tribuo.regression.libsvm

Class LibSVMRegressionModel

java.lang.Object

org.tribuo.Model<T>

org.tribuo.common.libsvm.LibSVMModel<Regressor>

org.tribuo.regression.libsvm.LibSVMRegressionModel

All Implemented Interfaces:

com.oracle.labs.mlrg.olcut.provenance.Provenancable<ModelProvenance>, Serializable

public class LibSVMRegressionModel
extends LibSVMModel<Regressor>

A regression model that uses an underlying libSVM model to make the predictions. Contains an independent model for each output dimension.

See:

 Chang CC, Lin CJ.
 "LIBSVM: a library for Support Vector Machines"
 ACM transactions on intelligent systems and technology (TIST), 2011.
 

for the nu-svr algorithm:

 Schölkopf B, Smola A, Williamson R, Bartlett P L.
 "New support vector algorithms"
 Neural Computation, 2000, 1207-1245.
 

and for the original algorithm:

 Cortes C, Vapnik V.
 "Support-Vector Networks"
 Machine Learning, 1995.
 

See Also:

Serialized Form

Field Summary

Fields inherited from class org.tribuo.common.libsvm.LibSVMModel

models

Fields inherited from class org.tribuo.Model

ALL_OUTPUTS, BIAS_FEATURE, featureIDMap, generatesProbabilities, name, outputIDInfo, provenance, provenanceOutput

Method Summary

Modifier and Type	Method and Description
protected LibSVMRegressionModel	copy(String newName, ModelProvenance newProvenance) Copies a model, replacing it's provenance and name with the supplied values.
protected double[]	getMeans() Accessor used in the tests.
Map<String,Integer>	getNumberOfSupportVectors() Returns the support vectors used for each dimension.
protected double[]	getVariances() Accessor used in the tests.
Prediction<Regressor>	predict(Example<Regressor> example) Uses the model to predict the output for a single example.

Methods inherited from class org.tribuo.common.libsvm.LibSVMModel

copyModel, getExcuse, getInnerModels, getModel, getTopFeatures

Methods inherited from class org.tribuo.Model

copy, generatesProbabilities, getExcuses, getFeatureIDMap, getName, getOutputIDInfo, getProvenance, innerPredict, predict, predict, setName, toString, validate

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

Method Detail

getNumberOfSupportVectors

public Map<String,Integer> getNumberOfSupportVectors()

Returns the support vectors used for each dimension.

Returns:

The support vectors.

predict

public Prediction<Regressor> predict(Example<Regressor> example)

Description copied from class: Model

Uses the model to predict the output for a single example.

predict does not mutate the example.

Throws IllegalArgumentException if the example has no features or no feature overlap with the model.

Specified by:

predict in class Model<Regressor>

Parameters:

example - the example to predict.

Returns:

the result of the prediction.

getMeans

protected double[] getMeans()

Accessor used in the tests. May be considered to be made public.

Returns:

The means used for standardization.

getVariances

protected double[] getVariances()

Accessor used in the tests. May be considered to be made public.

Returns:

The variances used for standardization.

copy

protected LibSVMRegressionModel copy(String newName,
                                     ModelProvenance newProvenance)

Description copied from class: Model

Copies a model, replacing it's provenance and name with the supplied values.

Used to provide the provenance removal functionality.

Specified by:

copy in class Model<Regressor>

Parameters:

newName - The new name.

newProvenance - The new provenance.

Returns:

A copy of the model.