Class LinearSGDModel

java.lang.Object

org.tribuo.Model<Regressor>

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

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

org.tribuo.regression.sgd.linear.LinearSGDModel

All Implemented Interfaces:

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

public class LinearSGDModel
extends AbstractLinearSGDModel<Regressor>
implements ONNXExportable

The inference time version of a linear model trained using SGD. The output dimensions are independent, unless they are tied together by the optimiser.

See:

 Bottou L.
 "Large-Scale Machine Learning with Stochastic Gradient Descent"
 Proceedings of COMPSTAT, 2010.
 

See Also:

• Serialized Form

Nested Class Summary

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

AbstractSGDModel.PredAndActive

Field Summary

Fields

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

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

Fields inherited from interface org.tribuo.ONNXExportable

PROVENANCE_METADATA_FIELD, SERIALIZER

Fields inherited from interface org.tribuo.protos.ProtoSerializable

DESERIALIZATION_METHOD_NAME, PROVENANCE_SERIALIZER

Method Summary

Modifier and Type	Method	Description
protected LinearSGDModel	copy(String newName, ModelProvenance newProvenance)	Copies a model, replacing its provenance and name with the supplied values.
static LinearSGDModel	deserializeFromProto(int version, String className, com.google.protobuf.Any message)	Deserialization factory.
protected String	getDimensionName(int index)	Gets the name of the indexed output dimension.
protected String	onnxModelName()
protected ONNXNode	onnxOutput(ONNXNode input)	Takes the unnormalized ONNX output of this model and applies an appropriate normalizer from the concrete class.
Prediction<Regressor>	predict(Example<Regressor> example)	Uses the model to predict the output for a single example.
org.tribuo.protos.core.ModelProto	serialize()	Serializes this object to a protobuf.

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

exportONNXModel, getExcuse, getTopFeatures, getWeightsCopy, writeONNXGraph

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

getModelParameters, predictSingle

Methods inherited from class org.tribuo.Model

castModel, copy, createDataCarrier, deserialize, deserializeFromFile, deserializeFromStream, generatesProbabilities, getExcuses, getFeatureIDMap, getName, getOutputIDInfo, getProvenance, innerPredict, predict, predict, serializeToFile, serializeToStream, setName, toString, validate

Methods inherited from class java.lang.Object

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

Methods inherited from interface org.tribuo.ONNXExportable

exportONNXModel, saveONNXModel, serializeProvenance, writeONNXGraph

Field Details

CURRENT_VERSION

public static final int CURRENT_VERSION

Protobuf serialization version.

See Also:

• Constant Field Values

Method Details

deserializeFromProto

public static LinearSGDModel 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 Prediction<Regressor> predict(Example<Regressor> example)

Description copied from class: Model

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

predict does not mutate the example.

Throws IllegalArgumentException if the example has no features or no feature overlap with the model.

Specified by:

predict in class Model<Regressor>

Parameters:

example - the example to predict.

Returns:

the result of the prediction.

serialize

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

Description copied from interface: ProtoSerializable

Serializes this object to a protobuf.

Specified by:

serialize in interface ProtoSerializable<org.tribuo.protos.core.ModelProto>

Overrides:

serialize in class Model<Regressor>

Returns:

The protobuf.

copy

protected LinearSGDModel copy(String newName,
 ModelProvenance newProvenance)

Description copied from class: Model

Copies a model, replacing its provenance and name with the supplied values.

Used to provide the provenance removal functionality.

Specified by:

copy in class Model<Regressor>

Parameters:

newName - The new name.

newProvenance - The new provenance.

Returns:

A copy of the model.

getDimensionName

protected String getDimensionName(int index)

Description copied from class: AbstractLinearSGDModel

Gets the name of the indexed output dimension.

Specified by:

getDimensionName in class AbstractLinearSGDModel<Regressor>

Parameters:

index - The output dimension index.

Returns:

The name of the requested output dimension.

onnxOutput

protected ONNXNode onnxOutput(ONNXNode input)

Description copied from class: AbstractLinearSGDModel

Takes the unnormalized ONNX output of this model and applies an appropriate normalizer from the concrete class.

Specified by:

onnxOutput in class AbstractLinearSGDModel<Regressor>

Parameters:

input - Unnormalized ONNX leaf node.

Returns:

Normalized ONNX leaf node.

onnxModelName

protected String onnxModelName()

Specified by:

onnxModelName in class AbstractLinearSGDModel<Regressor>

Returns:

Name to write into the ONNX Model.