Class LinearSGDTrainer

java.lang.Object

org.tribuo.common.sgd.AbstractSGDTrainer<Label, Integer, LinearSGDModel, LinearParameters>

org.tribuo.common.sgd.AbstractLinearSGDTrainer<Label, Integer, LinearSGDModel>

org.tribuo.classification.sgd.linear.LinearSGDTrainer

All Implemented Interfaces:

com.oracle.labs.mlrg.olcut.config.Configurable, com.oracle.labs.mlrg.olcut.provenance.Provenancable<org.tribuo.provenance.TrainerProvenance>, org.tribuo.Trainer<Label>, org.tribuo.WeightedExamples

Direct Known Subclasses:

LogisticRegressionTrainer

public class LinearSGDTrainer
extends AbstractLinearSGDTrainer<Label, Integer, LinearSGDModel>

A trainer for a linear classifier using SGD.

See:

 Bottou L.
 "Large-Scale Machine Learning with Stochastic Gradient Descent"
 Proceedings of COMPSTAT, 2010.
 

Field Summary

Fields inherited from class org.tribuo.common.sgd.AbstractSGDTrainer

addBias, epochs, loggingInterval, minibatchSize, optimiser, rng, seed, shuffle

Fields inherited from interface org.tribuo.Trainer

DEFAULT_SEED, INCREMENT_INVOCATION_COUNT

Constructor Summary

Constructors

Constructor	Description
LinearSGDTrainer(LabelObjective objective, StochasticGradientOptimiser optimiser, int epochs, int loggingInterval, int minibatchSize, long seed)	Constructs an SGD trainer for a linear model.
LinearSGDTrainer(LabelObjective objective, StochasticGradientOptimiser optimiser, int epochs, int loggingInterval, long seed)	Constructs an SGD trainer for a linear model.
LinearSGDTrainer(LabelObjective objective, StochasticGradientOptimiser optimiser, int epochs, long seed)	Constructs an SGD trainer for a linear model.

Method Summary

Modifier and Type	Method	Description
protected LinearSGDModel	createModel(String name, org.tribuo.provenance.ModelProvenance provenance, org.tribuo.ImmutableFeatureMap featureMap, org.tribuo.ImmutableOutputInfo<Label> outputInfo, LinearParameters parameters)
protected String	getModelClassName()
protected SGDObjective<Integer>	getObjective()
protected Integer	getTarget(org.tribuo.ImmutableOutputInfo<Label> outputInfo, Label output)
String	toString()

Methods inherited from class org.tribuo.common.sgd.AbstractLinearSGDTrainer

createParameters, getName

Methods inherited from class org.tribuo.common.sgd.AbstractSGDTrainer

getInvocationCount, getProvenance, postConfig, setInvocationCount, setShuffle, shuffleInPlace, train, train, train

Methods inherited from class java.lang.Object

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

Constructor Details

LinearSGDTrainer

public LinearSGDTrainer(LabelObjective objective,
 StochasticGradientOptimiser optimiser,
 int epochs,
 int loggingInterval,
 int minibatchSize,
 long seed)

Constructs an SGD trainer for a linear model.

Parameters:

objective - The objective function to optimise.

optimiser - The gradient optimiser to use.

epochs - The number of epochs (complete passes through the training data).

loggingInterval - Log the loss after this many iterations. If -1 don't log anything.

minibatchSize - The size of any minibatches.

seed - A seed for the random number generator, used to shuffle the examples before each epoch.

LinearSGDTrainer

public LinearSGDTrainer(LabelObjective objective,
 StochasticGradientOptimiser optimiser,
 int epochs,
 int loggingInterval,
 long seed)

Constructs an SGD trainer for a linear model.

Sets the minibatch size to 1.

Parameters:

objective - The objective function to optimise.

optimiser - The gradient optimiser to use.

epochs - The number of epochs (complete passes through the training data).

loggingInterval - Log the loss after this many iterations. If -1 don't log anything.

seed - A seed for the random number generator, used to shuffle the examples before each epoch.

LinearSGDTrainer

public LinearSGDTrainer(LabelObjective objective,
 StochasticGradientOptimiser optimiser,
 int epochs,
 long seed)

Constructs an SGD trainer for a linear model.

Sets the minibatch size to 1 and the logging interval to 1000.

Parameters:

objective - The objective function to optimise.

optimiser - The gradient optimiser to use.

epochs - The number of epochs (complete passes through the training data).

seed - A seed for the random number generator, used to shuffle the examples before each epoch.

Method Details

getTarget

protected Integer getTarget(org.tribuo.ImmutableOutputInfo<Label> outputInfo,
 Label output)

Specified by:

getTarget in class AbstractSGDTrainer<Label, Integer, LinearSGDModel, LinearParameters>

getObjective

protected SGDObjective<Integer> getObjective()

Specified by:

getObjective in class AbstractSGDTrainer<Label, Integer, LinearSGDModel, LinearParameters>

createModel

protected LinearSGDModel createModel(String name,
 org.tribuo.provenance.ModelProvenance provenance,
 org.tribuo.ImmutableFeatureMap featureMap,
 org.tribuo.ImmutableOutputInfo<Label> outputInfo,
 LinearParameters parameters)

Specified by:

createModel in class AbstractSGDTrainer<Label, Integer, LinearSGDModel, LinearParameters>

getModelClassName

protected String getModelClassName()

Specified by:

getModelClassName in class AbstractSGDTrainer<Label, Integer, LinearSGDModel, LinearParameters>

toString

public String toString()

Overrides:

toString in class Object