edu.cmu.minorthird.classify.relational
Class StackedGraphicalLearner

java.lang.Object
  edu.cmu.minorthird.classify.relational.StackedBatchClassifierLearner
      edu.cmu.minorthird.classify.relational.StackedGraphicalLearner

All Implemented Interfaces:

ClassifierLearner, java.lang.Cloneable

public class StackedGraphicalLearner
extends StackedBatchClassifierLearner

Stacked Graphical Learning based on a BatchClassifier learner

Author:

Zhenzhen Kou

Nested Class Summary

class	StackedGraphicalLearner.StackedGraphicalClassifier
static class	StackedGraphicalLearner.StackingParams Bundle of parameters for the StackedGraphicalLearner.

Field Summary

Fields inherited from class edu.cmu.minorthird.classify.relational.StackedBatchClassifierLearner

classifier, dataset

Constructor Summary

StackedGraphicalLearner()

StackedGraphicalLearner(BatchClassifierLearner baseLearner)

StackedGraphicalLearner(BatchClassifierLearner baseLearner, int depth)

StackedGraphicalLearner(int depth)

Method Summary

Classifier	batchTrain(RealRelationalDataset dataset) subclasses should use this method to implement a batch supervised learning algorithm.
StackedGraphicalLearner.StackingParams	getParams()
ExampleSchema	getSchema() Returns the ExampleSchema - constraints on what the Examples will be.
void	setSchema(ExampleSchema schema) Accept an ExampleSchema - constraints on what the Examples will be.
RealRelationalDataset	stackDataset(RealRelationalDataset dataset) Create a new dataset in which each instance has been augmented with the features constructed from the *predicted* labels of neighbor examples, where the prediction is made using cross-validation.

Methods inherited from class edu.cmu.minorthird.classify.relational.StackedBatchClassifierLearner

addExample, completeTraining, copy, getClassifier, hasNextQuery, nextQuery, reset, setInstancePool

Methods inherited from class java.lang.Object

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

Constructor Detail

StackedGraphicalLearner

public StackedGraphicalLearner()

StackedGraphicalLearner

public StackedGraphicalLearner(BatchClassifierLearner baseLearner)

StackedGraphicalLearner

public StackedGraphicalLearner(BatchClassifierLearner baseLearner,
                               int depth)

StackedGraphicalLearner

public StackedGraphicalLearner(int depth)

Method Detail

getParams

public StackedGraphicalLearner.StackingParams getParams()

setSchema

public final void setSchema(ExampleSchema schema)

Description copied from interface: ClassifierLearner

Accept an ExampleSchema - constraints on what the Examples will be.

getSchema

public final ExampleSchema getSchema()

Description copied from interface: ClassifierLearner

Returns the ExampleSchema - constraints on what the Examples will be.

batchTrain

public Classifier batchTrain(RealRelationalDataset dataset)

Description copied from class: StackedBatchClassifierLearner

subclasses should use this method to implement a batch supervised learning algorithm.

Specified by:

batchTrain in class StackedBatchClassifierLearner

stackDataset

public RealRelationalDataset stackDataset(RealRelationalDataset dataset)

Create a new dataset in which each instance has been augmented with the features constructed from the *predicted* labels of neighbor examples, where the prediction is made using cross-validation.