org.tribuo.anomaly.liblinear

Class LibLinearAnomalyModel

java.lang.Object

org.tribuo.Model<T>

org.tribuo.common.liblinear.LibLinearModel<Event>

org.tribuo.anomaly.liblinear.LibLinearAnomalyModel

All Implemented Interfaces:

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

public class LibLinearAnomalyModel
extends LibLinearModel<Event>

A Model which wraps a LibLinear-java anomaly detection model.

It disables the LibLinear debug output as it's very chatty.

See:

 Fan RE, Chang KW, Hsieh CJ, Wang XR, Lin CJ.
 "LIBLINEAR: A library for Large Linear Classification"
 Journal of Machine Learning Research, 2008.
 

and for the original algorithm:

 Cortes C, Vapnik V.
 "Support-Vector Networks"
 Machine Learning, 1995.
 

See Also:

Serialized Form

Field Summary

Fields inherited from class org.tribuo.common.liblinear.LibLinearModel

models

Fields inherited from class org.tribuo.Model

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

Method Summary

Modifier and Type	Method and Description
protected LibLinearAnomalyModel	copy(String newName, ModelProvenance newProvenance) Copies a model, replacing it's provenance and name with the supplied values.
protected double[][]	getFeatureWeights() Extracts the feature weights from the models.
Map<String,List<com.oracle.labs.mlrg.olcut.util.Pair<String,Double>>>	getTopFeatures(int n) Gets the top n features associated with this model.
protected Excuse<Event>	innerGetExcuse(Example<Event> e, double[][] allFeatureWeights) The call to model.getFeatureWeights in the public methods copies the weights array so this inner method exists to save the copy in getExcuses.
Prediction<Event>	predict(Example<Event> example) Uses the model to predict the output for a single example.

Methods inherited from class org.tribuo.common.liblinear.LibLinearModel

copyModel, getExcuse, getExcuses, getInnerModels

Methods inherited from class org.tribuo.Model

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

Methods inherited from class java.lang.Object

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

Method Detail

predict

public Prediction<Event> predict(Example<Event> 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<Event>

Parameters:

example - the example to predict.

Returns:

the result of the prediction.

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<Event>

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

copy

protected LibLinearAnomalyModel copy(String newName,
                                     ModelProvenance newProvenance)

Description copied from class: Model

Copies a model, replacing it's provenance and name with the supplied values.

Used to provide the provenance removal functionality.

Specified by:

copy in class Model<Event>

Parameters:

newName - The new name.

newProvenance - The new provenance.

Returns:

A copy of the model.

getFeatureWeights

protected double[][] getFeatureWeights()

Description copied from class: LibLinearModel

Extracts the feature weights from the models. The first dimension corresponds to the model index.

Specified by:

getFeatureWeights in class LibLinearModel<Event>

Returns:

The feature weights.

innerGetExcuse

protected Excuse<Event> innerGetExcuse(Example<Event> e,
                                       double[][] allFeatureWeights)

The call to model.getFeatureWeights in the public methods copies the weights array so this inner method exists to save the copy in getExcuses.

If it becomes a problem then we could cache the feature weights in the model.

Specified by:

innerGetExcuse in class LibLinearModel<Event>

Parameters:

e - The example.

allFeatureWeights - The feature weights.

Returns:

An excuse for this example.