jsat.classifiers.boosting

Class LogitBoostPL

java.lang.Object

jsat.classifiers.boosting.LogitBoost

jsat.classifiers.boosting.LogitBoostPL

All Implemented Interfaces:

java.io.Serializable, java.lang.Cloneable, Classifier, Parameterized

public class LogitBoostPL
extends LogitBoost

An extension to the original LogitBoost algorithm for parallel training. This comes at an increase in classification time.
Note: LogitBoost is a semi unstable algorithm, and this method does in fact increase the instability. In most cases, similar classification results will be obtained, however - under some circumstances the performance may be significantly degraded. Especially if there is insufficient data to distribute for parallel computation. The results for LogitBoost seem to be over stated in the original paper.
See: Scalable and Parallel Boosting with MapReduce, Indranil Palit and Chandan K. Reddy, IEEE Transactions on Knowledge and Data Engineering

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
LogitBoostPL(int M)
LogitBoostPL(Regressor baseLearner, int M)

Method Summary

Modifier and Type	Method and Description
LogitBoostPL	clone()
void	train(ClassificationDataSet dataSet, boolean parallel) Trains the classifier and constructs a model for classification using the given data set.

Methods inherited from class jsat.classifiers.boosting.LogitBoost

classify, getMaxIterations, getModels, getzMax, setMaxIterations, setzMax, supportsWeightedData

Methods inherited from class java.lang.Object

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

Methods inherited from interface jsat.classifiers.Classifier

train

Methods inherited from interface jsat.parameters.Parameterized

getParameter, getParameters

Constructor Detail

LogitBoostPL

public LogitBoostPL(Regressor baseLearner,
                    int M)

LogitBoostPL

public LogitBoostPL(int M)

Method Detail

train

public void train(ClassificationDataSet dataSet,
                  boolean parallel)

Description copied from interface: Classifier

Trains the classifier and constructs a model for classification using the given data set. If the training method knows how, it will used the threadPool to conduct training in parallel. This method will block until the training has completed.

Specified by:

train in interface Classifier

Overrides:

train in class LogitBoost

Parameters:

dataSet - the data set to train on

parallel - true if multiple threads should be used to train the model. false if it should be done in a single threaded manner.

clone

public LogitBoostPL clone()

Specified by:

clone in interface Classifier

Overrides:

clone in class LogitBoost