org.tribuo.regression.baseline

Class DummyRegressionTrainer

java.lang.Object

org.tribuo.regression.baseline.DummyRegressionTrainer

All Implemented Interfaces:

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

public final class DummyRegressionTrainer
extends Object
implements Trainer<Regressor>

A trainer for simple baseline regressors. Use this only for comparison purposes, if you can't beat these baselines, your ML system doesn't work.

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	DummyRegressionTrainer.DummyRegressionTrainerProvenance Deprecated.
static class	DummyRegressionTrainer.DummyType Types of dummy regression model.

Field Summary

Fields inherited from interface org.tribuo.Trainer

DEFAULT_SEED

Method Summary

Modifier and Type	Method and Description
static DummyRegressionTrainer	createConstantTrainer(double value) Creates a trainer which create models which return a fixed value.
static DummyRegressionTrainer	createGaussianTrainer(long seed) Creates a trainer which create models which sample the output from a gaussian distribution fit to the training data.
static DummyRegressionTrainer	createMeanTrainer() Creates a trainer which create models which return the mean of the training data.
static DummyRegressionTrainer	createMedianTrainer() Creates a trainer which create models which return the median of the training data.
static DummyRegressionTrainer	createQuartileTrainer(double value) Creates a trainer which create models which return the value at the specified fraction of the sorted training data.
int	getInvocationCount() The number of times this trainer instance has had it's train method invoked.
TrainerProvenance	getProvenance()
void	postConfig() Used by the OLCUT configuration system, and should not be called by external code.
String	toString()
DummyRegressionModel	train(Dataset<Regressor> examples, Map<String,com.oracle.labs.mlrg.olcut.provenance.Provenance> instanceProvenance) Trains a predictive model using the examples in the given data set.

Methods inherited from class java.lang.Object

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

Methods inherited from interface org.tribuo.Trainer

train

Method Detail

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

train

public DummyRegressionModel train(Dataset<Regressor> examples,
                                  Map<String,com.oracle.labs.mlrg.olcut.provenance.Provenance> instanceProvenance)

Description copied from interface: Trainer

Trains a predictive model using the examples in the given data set.

Specified by:

train in interface Trainer<Regressor>

Parameters:

examples - the data set containing the examples.

instanceProvenance - Training run specific provenance (e.g., fold number).

Returns:

a predictive model that can be used to generate predictions for new examples.

toString

public String toString()

Overrides:

toString in class Object

getInvocationCount

public int getInvocationCount()

Description copied from interface: Trainer

The number of times this trainer instance has had it's train method invoked.

This is used to determine how many times the trainer's RNG has been accessed to ensure replicability in the random number stream.

Specified by:

getInvocationCount in interface Trainer<Regressor>

Returns:

The number of train invocations.

getProvenance

public TrainerProvenance getProvenance()

Specified by:

getProvenance in interface com.oracle.labs.mlrg.olcut.provenance.Provenancable<TrainerProvenance>

createConstantTrainer

public static DummyRegressionTrainer createConstantTrainer(double value)

Creates a trainer which create models which return a fixed value.

Parameters:

value - The value to return

Returns:

A regression trainer.

createGaussianTrainer

public static DummyRegressionTrainer createGaussianTrainer(long seed)

Creates a trainer which create models which sample the output from a gaussian distribution fit to the training data.

Parameters:

seed - The RNG seed.

Returns:

A regression trainer.

createMeanTrainer

public static DummyRegressionTrainer createMeanTrainer()

Creates a trainer which create models which return the mean of the training data.

Returns:

A regression trainer.

createMedianTrainer

public static DummyRegressionTrainer createMedianTrainer()

Creates a trainer which create models which return the median of the training data.

Returns:

A regression trainer.

createQuartileTrainer

public static DummyRegressionTrainer createQuartileTrainer(double value)

Creates a trainer which create models which return the value at the specified fraction of the sorted training data.

Parameters:

value - The quartile value.

Returns:

A regression trainer.