Class DummyClassifierModel

java.lang.Object
org.tribuo.Model<Label>
org.tribuo.classification.baseline.DummyClassifierModel
All Implemented Interfaces:
com.oracle.labs.mlrg.olcut.provenance.Provenancable<ModelProvenance>, Serializable, ProtoSerializable<org.tribuo.protos.core.ModelProto>

public class DummyClassifierModel extends Model<Label>
A model which performs dummy classifications (e.g., constant output, uniform sampled labels, stratified sampled labels).
See Also:
  • Field Details

    • CURRENT_VERSION

      public static final int CURRENT_VERSION
      Protobuf serialization version.
      See Also:
  • Method Details

    • deserializeFromProto

      public static DummyClassifierModel 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<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>
      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<Label>
      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
    • getExcuse

      public Optional<Excuse<Label>> getExcuse(Example<Label> example)
      Description copied from class: Model
      Generates an excuse for an example.

      This attempts to explain a classification result. Generating an excuse may be quite an expensive operation.

      This excuse either contains per class information or an entry with key Model.ALL_OUTPUTS.

      The optional is empty if the model does not provide excuses.

      Specified by:
      getExcuse in class Model<Label>
      Parameters:
      example - The input example.
      Returns:
      An optional excuse object. The optional is empty if this model does not provide excuses.
    • 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<Label>
      Returns:
      The protobuf.
    • copy

      protected DummyClassifierModel 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>
      Parameters:
      newName - The new name.
      newProvenance - The new provenance.
      Returns:
      A copy of the model.