Class LibSVMRegressionTrainer

java.lang.Object

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

org.tribuo.regression.libsvm.LibSVMRegressionTrainer

All Implemented Interfaces:

com.oracle.labs.mlrg.olcut.config.Configurable, com.oracle.labs.mlrg.olcut.provenance.Provenancable<TrainerProvenance>, Trainer<Regressor>

public class LibSVMRegressionTrainer
extends LibSVMTrainer<Regressor>

A trainer for regression models that uses LibSVM. Trains 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.
 

Field Summary

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

parameters, svmType

Fields inherited from interface org.tribuo.Trainer

DEFAULT_SEED

Constructor Summary

Constructors

Modifier	Constructor	Description
protected	LibSVMRegressionTrainer()	For olcut.
	LibSVMRegressionTrainer(SVMParameters<Regressor> parameters)

Method Summary

Modifier and Type	Method	Description
protected LibSVMModel<Regressor>	createModel(ModelProvenance provenance, ImmutableFeatureMap featureIDMap, ImmutableOutputInfo<Regressor> outputIDInfo, List<libsvm.svm_model> models)	Construct the appropriate subtype of LibSVMModel for the prediction task.
protected com.oracle.labs.mlrg.olcut.util.Pair<libsvm.svm_node[][], double[][]>	extractData(Dataset<Regressor> data, ImmutableOutputInfo<Regressor> outputInfo, ImmutableFeatureMap featureMap)	Extracts the features and Outputs in LibLinear's format.
void	postConfig()	Used by the OLCUT configuration system, and should not be called by external code.
protected List<libsvm.svm_model>	trainModels(libsvm.svm_parameter curParams, int numFeatures, libsvm.svm_node[][] features, double[][] outputs)	Train all the liblinear instances necessary for this dataset.

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

exampleToNodes, getInvocationCount, getProvenance, setupParameters, toString, train, train

Methods inherited from class java.lang.Object

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

Constructor Details

LibSVMRegressionTrainer

protected LibSVMRegressionTrainer()

For olcut.

LibSVMRegressionTrainer

public LibSVMRegressionTrainer(SVMParameters<Regressor> parameters)

Method Details

postConfig

public void postConfig()

Used by the OLCUT configuration system, and should not be called by external code.

Specified by:

postConfig in interface com.oracle.labs.mlrg.olcut.config.Configurable

Overrides:

postConfig in class LibSVMTrainer<Regressor>

createModel

protected LibSVMModel<Regressor> createModel(ModelProvenance provenance,
 ImmutableFeatureMap featureIDMap,
 ImmutableOutputInfo<Regressor> outputIDInfo,
 List<libsvm.svm_model> models)

Description copied from class: LibSVMTrainer

Construct the appropriate subtype of LibSVMModel for the prediction task.

Specified by:

createModel in class LibSVMTrainer<Regressor>

Parameters:

provenance - The model provenance.

featureIDMap - The feature id map.

outputIDInfo - The output id info.

models - The svm models.

Returns:

An implementation of LibSVMModel.

trainModels

protected List<libsvm.svm_model> trainModels(libsvm.svm_parameter curParams,
 int numFeatures,
 libsvm.svm_node[][] features,
 double[][] outputs)

Description copied from class: LibSVMTrainer

Train all the liblinear instances necessary for this dataset.

Specified by:

trainModels in class LibSVMTrainer<Regressor>

Parameters:

curParams - The LibLinear parameters.

numFeatures - The number of features in this dataset.

features - The features themselves.

outputs - The outputs.

Returns:

A list of liblinear models.

extractData

protected com.oracle.labs.mlrg.olcut.util.Pair<libsvm.svm_node[][], double[][]> extractData(Dataset<Regressor> data,
 ImmutableOutputInfo<Regressor> outputInfo,
 ImmutableFeatureMap featureMap)

Description copied from class: LibSVMTrainer

Extracts the features and Outputs in LibLinear's format.

Specified by:

extractData in class LibSVMTrainer<Regressor>

Parameters:

data - The input data.

outputInfo - The output info.

featureMap - The feature info.

Returns:

The features and outputs.