Class AbstractLinearSGDModel<T extends Output<T>>

java.lang.Object

org.tribuo.Model<T>

org.tribuo.common.sgd.AbstractSGDModel<T>

org.tribuo.common.sgd.AbstractLinearSGDModel<T>

All Implemented Interfaces:

com.oracle.labs.mlrg.olcut.provenance.Provenancable<ModelProvenance>, Serializable

Direct Known Subclasses:

LinearSGDModel, LinearSGDModel, LinearSGDModel

public abstract class AbstractLinearSGDModel<T extends Output<T>>
extends AbstractSGDModel<T>

See Also:

• Serialized Form

Nested Class Summary

Nested classes/interfaces inherited from class org.tribuo.common.sgd.AbstractSGDModel

AbstractSGDModel.PredAndActive

Field Summary

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

addBias, modelParameters

Fields inherited from class org.tribuo.Model

ALL_OUTPUTS, BIAS_FEATURE, featureIDMap, generatesProbabilities, name, outputIDInfo, provenance, provenanceOutput

Constructor Summary

Constructors

Modifier	Constructor	Description
protected	AbstractLinearSGDModel(String name, ModelProvenance provenance, ImmutableFeatureMap featureIDMap, ImmutableOutputInfo<T> outputIDInfo, LinearParameters parameters, boolean generatesProbabilities)	Constructs a linear model trained via SGD.

Method Summary

Modifier and Type	Method	Description
protected abstract String	getDimensionName(int index)	Gets the name of the indexed output dimension.
Optional<Excuse<T>>	getExcuse(Example<T> example)	Generates an excuse for an example.
Map<String, List<com.oracle.labs.mlrg.olcut.util.Pair<String,Double>>>	getTopFeatures(int n)	Gets the top n features associated with this model.
DenseMatrix	getWeightsCopy()	Returns a copy of the weights.

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

getModelParameters, predictSingle

Methods inherited from class org.tribuo.Model

copy, copy, generatesProbabilities, getExcuses, getFeatureIDMap, getName, getOutputIDInfo, getProvenance, innerPredict, predict, predict, predict, setName, toString, validate

Methods inherited from class java.lang.Object

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

Constructor Details

AbstractLinearSGDModel

protected AbstractLinearSGDModel(String name,
 ModelProvenance provenance,
 ImmutableFeatureMap featureIDMap,
 ImmutableOutputInfo<T> outputIDInfo,
 LinearParameters parameters,
 boolean generatesProbabilities)

Constructs a linear model trained via SGD.

Parameters:

name - The model name.

provenance - The model provenance.

featureIDMap - The feature domain.

outputIDInfo - The output domain.

parameters - The model parameters.

generatesProbabilities - Does this model generate probabilities?

Method Details

getTopFeatures

public Map<String, List<com.oracle.labs.mlrg.olcut.util.Pair<String,Double>>> getTopFeatures(int n)

Description copied from class: Model

Gets the top n features associated with this model.

If the model does not produce per output feature lists, it returns a map with a single element with key Model.ALL_OUTPUTS.

If the model cannot describe it's top features then it returns Collections.emptyMap().

Specified by:

getTopFeatures in class Model<T extends Output<T>>

Parameters:

n - the number of features to return. If this value is less than 0, all features should be returned for each class, unless the model cannot score it's features.

Returns:

a map from string outputs to an ordered list of pairs of feature names and weights associated with that feature in the model

getExcuse

public Optional<Excuse<T>> getExcuse(Example<T> example)

Description copied from class: Model

Generates an excuse for an example.

This attempts to explain a classification result. Generating an excuse may be quite an expensive operation.

This excuse either contains per class information or an entry with key Model.ALL_OUTPUTS.

The optional is empty if the model does not provide excuses.

Specified by:

getExcuse in class Model<T extends Output<T>>

Parameters:

example - The input example.

Returns:

An optional excuse object. The optional is empty if this model does not provide excuses.

getDimensionName

protected abstract String getDimensionName(int index)

Gets the name of the indexed output dimension.

Parameters:

index - The output dimension index.

Returns:

The name of the requested output dimension.

getWeightsCopy

public DenseMatrix getWeightsCopy()

Returns a copy of the weights.

Returns:

A copy of the weights.