org.tribuo.classification.baseline

Class DummyClassifierTrainer

java.lang.Object

org.tribuo.classification.baseline.DummyClassifierTrainer

All Implemented Interfaces:

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

public final class DummyClassifierTrainer
extends Object
implements Trainer<Label>

A trainer for simple baseline classifiers. 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	DummyClassifierTrainer.DummyType Types of dummy classifier.

Field Summary

Fields inherited from interface org.tribuo.Trainer

DEFAULT_SEED

Method Summary

Modifier and Type	Method and Description
static DummyClassifierTrainer	createConstantTrainer(String constantLabel) Creates a trainer which creates models which return a fixed label.
static DummyClassifierTrainer	createMostFrequentTrainer() Creates a trainer which creates models which return a fixed label, the one which was most frequent in the training data.
static DummyClassifierTrainer	createStratifiedTrainer(long seed) Creates a trainer which creates models which return random labels sampled from the training label distribution.
static DummyClassifierTrainer	createUniformTrainer(long seed) Creates a trainer which creates models which return random labels sampled uniformly from the labels seen at training time.
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()
Model<Label>	train(Dataset<Label> 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 Model<Label> train(Dataset<Label> 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<Label>

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.

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<Label>

Returns:

The number of train invocations.

toString

public String toString()

Overrides:

toString in class Object

getProvenance

public TrainerProvenance getProvenance()

Specified by:

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

createStratifiedTrainer

public static DummyClassifierTrainer createStratifiedTrainer(long seed)

Creates a trainer which creates models which return random labels sampled from the training label distribution.

Parameters:

seed - The RNG seed to use.

Returns:

A classification trainer.

createConstantTrainer

public static DummyClassifierTrainer createConstantTrainer(String constantLabel)

Creates a trainer which creates models which return a fixed label.

Parameters:

constantLabel - The label to return.

Returns:

A classification trainer.

createUniformTrainer

public static DummyClassifierTrainer createUniformTrainer(long seed)

Creates a trainer which creates models which return random labels sampled uniformly from the labels seen at training time.

Parameters:

seed - The RNG seed to use.

Returns:

A classification trainer.

createMostFrequentTrainer

public static DummyClassifierTrainer createMostFrequentTrainer()

Creates a trainer which creates models which return a fixed label, the one which was most frequent in the training data.

Returns:

A classification trainer.