public class LinearSGDModel extends AbstractLinearSGDModel<MultiLabel>
See:
Bottou L. "Large-Scale Machine Learning with Stochastic Gradient Descent" Proceedings of COMPSTAT, 2010.
AbstractSGDModel.PredAndActive
addBias, modelParameters
ALL_OUTPUTS, BIAS_FEATURE, featureIDMap, generatesProbabilities, name, outputIDInfo, provenance, provenanceOutput
Modifier and Type | Method and Description |
---|---|
protected LinearSGDModel |
copy(String newName,
ModelProvenance newProvenance)
Copies a model, replacing it's provenance and name with the supplied values.
|
protected String |
getDimensionName(int index)
Gets the name of the indexed output dimension.
|
Prediction<MultiLabel> |
predict(Example<MultiLabel> example)
Uses the model to predict the output for a single example.
|
getExcuse, getTopFeatures, getWeightsCopy
getModelParameters, predictSingle
copy, generatesProbabilities, getExcuses, getFeatureIDMap, getName, getOutputIDInfo, getProvenance, innerPredict, predict, predict, setName, toString, validate
public Prediction<MultiLabel> predict(Example<MultiLabel> example)
Model
predict does not mutate the example.
Throws IllegalArgumentException
if the example has no features
or no feature overlap with the model.
predict
in class Model<MultiLabel>
example
- the example to predict.protected String getDimensionName(int index)
AbstractLinearSGDModel
getDimensionName
in class AbstractLinearSGDModel<MultiLabel>
index
- The output dimension index.protected LinearSGDModel copy(String newName, ModelProvenance newProvenance)
Model
Used to provide the provenance removal functionality.
copy
in class Model<MultiLabel>
newName
- The new name.newProvenance
- The new provenance.Copyright © 2015–2021 Oracle and/or its affiliates. All rights reserved.