com.datumbox.framework.core.machinelearning.classification

Class MaximumEntropy

java.lang.Object

com.datumbox.framework.core.machinelearning.common.abstracts.AbstractTrainer<MP,TP>

com.datumbox.framework.core.machinelearning.common.abstracts.modelers.AbstractModeler<MP,TP>

com.datumbox.framework.core.machinelearning.common.abstracts.modelers.AbstractClassifier<MaximumEntropy.ModelParameters,MaximumEntropy.TrainingParameters>

com.datumbox.framework.core.machinelearning.classification.MaximumEntropy

All Implemented Interfaces:

Savable, Parallelizable, PredictParallelizable, Trainable<MaximumEntropy.ModelParameters,MaximumEntropy.TrainingParameters>, TrainParallelizable, java.lang.AutoCloseable

public class MaximumEntropy
extends AbstractClassifier<MaximumEntropy.ModelParameters,MaximumEntropy.TrainingParameters>
implements PredictParallelizable, TrainParallelizable

The MaximumEntropy implements the Max Ent classifier which is an alternative implementation of Multinomial Logistic Regression model. References: http://blog.datumbox.com/machine-learning-tutorial-the-max-entropy-text-classifier/ http://www.cs.cmu.edu/afs/cs/user/aberger/www/html/tutorial/node3.html https://web.archive.org/web/20121021173335/http://acl.ldc.upenn.edu/P/P02/P02-1002.pdf

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	MaximumEntropy.ModelParameters Base class for every ModelParameter class in the framework.
static class	MaximumEntropy.TrainingParameters The AbstractTrainingParameters class stores the parameters that can be changed before training the algorithm.

Nested classes/interfaces inherited from class com.datumbox.framework.core.machinelearning.common.abstracts.modelers.AbstractClassifier

AbstractClassifier.AbstractModelParameters

Nested classes/interfaces inherited from class com.datumbox.framework.core.machinelearning.common.abstracts.AbstractTrainer

AbstractTrainer.AbstractTrainingParameters

Nested classes/interfaces inherited from interface com.datumbox.framework.core.machinelearning.common.interfaces.PredictParallelizable

PredictParallelizable.Prediction

Method Summary

Modifier and Type	Method and Description
PredictParallelizable.Prediction	_predictRecord(Record r) Takes a single record, makes a prediction using the model and returns the result wrapped in the Prediction tuple.
boolean	isParallelized() Getter for the parallelized parameter.
void	setParallelized(boolean parallelized) Setter for the parallelized parameter.

Methods inherited from class com.datumbox.framework.core.machinelearning.common.abstracts.modelers.AbstractModeler

predict

Methods inherited from class com.datumbox.framework.core.machinelearning.common.abstracts.AbstractTrainer

close, delete, fit, getModelParameters, getTrainingParameters, save

Methods inherited from class java.lang.Object

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

Methods inherited from interface com.datumbox.framework.core.machinelearning.common.interfaces.PredictParallelizable

_predictDatasetParallel, _predictDatasetParallel

Method Detail

isParallelized

public boolean isParallelized()

Getter for the parallelized parameter.

Specified by:

isParallelized in interface Parallelizable

Returns:

setParallelized

public void setParallelized(boolean parallelized)

Setter for the parallelized parameter.

Specified by:

setParallelized in interface Parallelizable

_predictRecord

public PredictParallelizable.Prediction _predictRecord(Record r)

Takes a single record, makes a prediction using the model and returns the result wrapped in the Prediction tuple. The method assumes that the KnowledgeBase is be loaded.

Specified by:

_predictRecord in interface PredictParallelizable

Returns: