Package org.tribuo.regression.libsvm

Class LibSVMRegressionModel

java.lang.Object
org.tribuo.Model<T>
org.tribuo.common.libsvm.LibSVMModel<Regressor>
org.tribuo.regression.libsvm.LibSVMRegressionModel
All Implemented Interfaces:
com.oracle.labs.mlrg.olcut.provenance.Provenancable<ModelProvenance>, Serializable, ONNXExportable
public class LibSVMRegressionModel extends LibSVMModel<Regressor> implements ONNXExportable
A regression model that uses an underlying libSVM model to make the predictions. Contains an independent model for each output dimension.

See: 

 Chang CC, Lin CJ.
 "LIBSVM: a library for Support Vector Machines"
 ACM transactions on intelligent systems and technology (TIST), 2011.
for the nu-svr algorithm: 
 Schölkopf B, Smola A, Williamson R, Bartlett P L.
 "New support vector algorithms"
 Neural Computation, 2000, 1207-1245.
and for the original algorithm: 
 Cortes C, Vapnik V.
 "Support-Vector Networks"
 Machine Learning, 1995.
See Also:

  • Method Details

    • getNumberOfSupportVectors

      public Map<String,Integer> getNumberOfSupportVectors()
      Returns the support vectors used for each dimension.
      Returns:
      The support vectors.

    • 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.

    • getMeans

      protected double[] getMeans()
      Accessor used in the tests. May be considered to be made public.
      Returns:
      The means used for standardization.

    • getVariances

      protected double[] getVariances()
      Accessor used in the tests. May be considered to be made public.
      Returns:
      The variances used for standardization.

    • copy

      protected LibSVMRegressionModel 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.

    • 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
      Parameters:
      domain - A reverse-DNS name to namespace the model (e.g., org.tribuo.classification.sgd.linear).
      modelVersion - A version number for this model.
      Returns:
      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
      Parameters:
      input - The input to the model graph.
      Returns:
      the output node of the model graph.