Package org.tribuo

Class SparseModel<T extends Output<T>>

java.lang.Object

org.tribuo.Model<T>

org.tribuo.SparseModel<T>

All Implemented Interfaces:

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

Direct Known Subclasses:

SkeletalIndependentRegressionSparseModel, TreeModel

public abstract class SparseModel<T extends Output<T>>
extends Model<T>

A model which uses a subset of the features it knows about to make predictions.

See Also:

• Serialized Form

Field Summary

Fields inherited from class org.tribuo.Model

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

Constructor Summary

Constructors

Constructor	Description
SparseModel(String name, ModelProvenance provenance, ImmutableFeatureMap featureIDMap, ImmutableOutputInfo<T> outputIDInfo, boolean generatesProbabilities, Map<String,List<String>> activeFeatures)	Constructs a sparse model from the supplied arguments.

Method Summary

Modifier and Type	Method	Description
SparseModel<T>	copy()	Copies a model, returning a deep copy of any mutable state, and a shallow copy otherwise.
Map<String,List<String>>	getActiveFeatures()	Return an immutable view on the active features for each dimension.

Methods inherited from class org.tribuo.Model

castModel, copy, generatesProbabilities, getExcuse, getExcuses, getFeatureIDMap, getName, getOutputIDInfo, getProvenance, getTopFeatures, 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

SparseModel

public SparseModel(String name,
 ModelProvenance provenance,
 ImmutableFeatureMap featureIDMap,
 ImmutableOutputInfo<T> outputIDInfo,
 boolean generatesProbabilities,
 Map<String,List<String>> activeFeatures)

Constructs a sparse model from the supplied arguments.

Parameters:

name - The model name.

provenance - The model provenance.

featureIDMap - The features the model knows.

outputIDInfo - The outputs the model can produce.

generatesProbabilities - Does this model generate probabilistic outputs.

activeFeatures - The active features in this model.

Method Details

getActiveFeatures

public Map<String,List<String>> getActiveFeatures()

Return an immutable view on the active features for each dimension.

Sorted lexicographically.

Returns:

The active features.

copy

public SparseModel<T> copy()

Description copied from class: Model

Copies a model, returning a deep copy of any mutable state, and a shallow copy otherwise.

Overrides:

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

Returns:

A copy of the model.