Class LibLinearClassificationModel

All Implemented Interfaces:<ModelProvenance>, Serializable, ONNXExportable

public class LibLinearClassificationModel extends LibLinearModel<Label> implements ONNXExportable
A Model which wraps a LibLinear-java classification model.

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


 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:
  • Method Details

    • predict

      public Prediction<Label> predict(Example<Label> 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<Label>
      example - the example to predict.
      the result of the prediction.
    • getTopFeatures

      public Map<String,List<<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<Label>
      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.
      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 LibLinearClassificationModel 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<Label>
      newName - The new name.
      newProvenance - The new provenance.
      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<Label>
      The feature weights.
    • innerGetExcuse

      protected Excuse<Label> innerGetExcuse(Example<Label> 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<Label>
      e - The example.
      allFeatureWeights - The feature weights.
      An excuse for this example.
    • exportONNXModel

      public OnnxMl.ModelProto exportONNXModel(String domain, long modelVersion)
      Description copied from interface: ONNXExportable
      Exports this Model as an ONNX protobuf.
      Specified by:
      exportONNXModel in interface ONNXExportable
      domain - A reverse-DNS name to namespace the model (e.g., org.tribuo.classification.sgd.linear).
      modelVersion - A version number for this model.
      The ONNX ModelProto representing this Tribuo Model.
    • writeONNXGraph

      public ONNXNode writeONNXGraph(ONNXRef<?> input)
      Description copied from interface: ONNXExportable
      Writes this Model into OnnxMl.GraphProto.Builder inside the input's ONNXContext.
      Specified by:
      writeONNXGraph in interface ONNXExportable
      input - The input to the model graph.
      the output node of the model graph.