Class IndependentSequenceModel<T extends Output<T>>

java.lang.Object

org.tribuo.sequence.SequenceModel<T>

org.tribuo.sequence.IndependentSequenceModel<T>

Type Parameters:

T - The output type.

All Implemented Interfaces:

com.oracle.labs.mlrg.olcut.provenance.Provenancable<ModelProvenance>, Serializable, ProtoSerializable<org.tribuo.protos.core.SequenceModelProto>

public class IndependentSequenceModel<T extends Output<T>>
extends SequenceModel<T>

A SequenceModel which independently predicts each element of the sequence.

See Also:

• Serialized Form

Field Summary

Fields

Modifier and Type	Field	Description
static final int	CURRENT_VERSION	Protobuf serialization version.

Fields inherited from class org.tribuo.sequence.SequenceModel

featureIDMap, name, outputIDMap, provenanceOutput

Fields inherited from interface org.tribuo.protos.ProtoSerializable

DESERIALIZATION_METHOD_NAME, PROVENANCE_SERIALIZER

Method Summary

Modifier and Type	Method	Description
static IndependentSequenceModel<?>	deserializeFromProto(int version, String className, com.google.protobuf.Any message)	Deserialization factory.
Map<String, List<com.oracle.labs.mlrg.olcut.util.Pair<String,Double>>>	getTopFeatures(int n)	Gets the top n features associated with this model.
List<Prediction<T>>	predict(SequenceExample<T> example)	Uses the model to predict the output for a single example.
org.tribuo.protos.core.SequenceModelProto	serialize()	Serializes this object to a protobuf.

Methods inherited from class org.tribuo.sequence.SequenceModel

castModel, createDataCarrier, deserialize, deserializeFromFile, deserializeFromStream, getFeatureIDMap, getName, getOutputIDInfo, getProvenance, predict, predict, serializeToFile, serializeToStream, setName, toMaxLabels, toString, validate

Methods inherited from class java.lang.Object

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

Field Details

CURRENT_VERSION

public static final int CURRENT_VERSION

Protobuf serialization version.

See Also:

• Constant Field Values

Method Details

deserializeFromProto

public static IndependentSequenceModel<?> deserializeFromProto(int version,
 String className,
 com.google.protobuf.Any message)
                                                        throws com.google.protobuf.InvalidProtocolBufferException

Deserialization factory.

Parameters:

version - The serialized object version.

className - The class name.

message - The serialized data.

Returns:

The deserialized object.

Throws:

com.google.protobuf.InvalidProtocolBufferException - If the protobuf could not be parsed from the message.

predict

public List<Prediction<T>> predict(SequenceExample<T> example)

Description copied from class: SequenceModel

Uses the model to predict the output for a single example.

Specified by:

predict in class SequenceModel<T extends Output<T>>

Parameters:

example - the example to predict.

Returns:

the result of the prediction.

serialize

public org.tribuo.protos.core.SequenceModelProto serialize()

Description copied from interface: ProtoSerializable

Serializes this object to a protobuf.

Specified by:

serialize in interface ProtoSerializable<T extends Output<T>>

Overrides:

serialize in class SequenceModel<T extends Output<T>>

Returns:

The protobuf.

getTopFeatures

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

Description copied from class: SequenceModel

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 SequenceModel<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 its 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