Package opennlp.tools.ml.maxent

Class GISModel

java.lang.Object
opennlp.tools.ml.model.AbstractModel
opennlp.tools.ml.maxent.GISModel
All Implemented Interfaces:
MaxentModel
public final class GISModel extends AbstractModel
A maximum entropy model which has been trained using the Generalized Iterative Scaling procedure (implemented in GIS.java).

  • Nested Class Summary

    Nested classes/interfaces inherited from class opennlp.tools.ml.model.AbstractModel

    AbstractModel.ModelType

  • Constructor Summary

    Constructors
    Constructor
    Description
    GISModel(Context[] params, String[] predLabels, String[] outcomeNames)
    Creates a new model with the specified parameters, outcome names, and predicate/feature labels.
    GISModel(Context[] params, String[] predLabels, String[] outcomeNames, Prior prior)
    Creates a new model with the specified parameters, outcome names, and predicate/feature labels.

  • Method Summary

    Modifier and Type
    Method
    Description
    static double[]
    eval(int[] context, double[] prior, EvalParameters model)
    Use this model to evaluate a context and return an array of the likelihood of each outcome given the specified context and the specified parameters.
    final double[]
    eval(String[] context)
    Use this model to evaluate a context and return an array of the likelihood of each outcome given that context.
    final double[]
    eval(String[] context, double[] outsums)
    Evaluates a context.
    final double[]
    eval(String[] context, float[] values)
    Evaluates a contexts with the specified context values.
    final double[]
    eval(String[] context, float[] values, double[] outsums)
    Use this model to evaluate a context and return an array of the likelihood of each outcome given that context.

    Methods inherited from class opennlp.tools.ml.model.AbstractModel

    equals, getAllOutcomes, getBestOutcome, getDataStructures, getIndex, getModelType, getNumOutcomes, getOutcome, hashCode

    Methods inherited from class java.lang.Object

    getClass, notify, notifyAll, toString, wait, wait, wait

  • Constructor Details

    • GISModel

      public GISModel(Context[] params, String[] predLabels, String[] outcomeNames)
      Creates a new model with the specified parameters, outcome names, and predicate/feature labels.
      Parameters:
      params - The parameters of the model.
      predLabels - The names of the predicates used in this model.
      outcomeNames - The names of the outcomes this model predicts.

    • GISModel

      public GISModel(Context[] params, String[] predLabels, String[] outcomeNames, Prior prior)
      Creates a new model with the specified parameters, outcome names, and predicate/feature labels.
      Parameters:
      params - The parameters of the model.
      predLabels - The names of the predicates used in this model.
      outcomeNames - The names of the outcomes this model predicts.
      prior - The prior to be used with this model.

  • Method Details

    • eval

      public final double[] eval(String[] context)
      Use this model to evaluate a context and return an array of the likelihood of each outcome given that context.
      Parameters:
      context - The names of the predicates which have been observed at the present decision point.
      Returns:
      The normalized probabilities for the outcomes given the context. The indexes of the double[] are the outcome ids, and the actual string representation of the outcomes can be obtained from the method getOutcome(int i).

    • eval

      public final double[] eval(String[] context, float[] values)
      Description copied from interface: MaxentModel
      Evaluates a contexts with the specified context values.
      Parameters:
      context - A list of String names of the contextual predicates which are to be evaluated together.
      values - The values associated with each context.
      Returns:
      an array of the probabilities for each of the different outcomes, all of which sum to 1.

    • eval

      public final double[] eval(String[] context, double[] outsums)
      Description copied from interface: MaxentModel
      Evaluates a context.
      Parameters:
      context - A list of String names of the contextual predicates which are to be evaluated together.
      outsums - An array which is populated with the probabilities for each of the different outcomes, all of which sum to 1.
      Returns:
      an array of the probabilities for each of the different outcomes, all of which sum to 1.

    • eval

      public final double[] eval(String[] context, float[] values, double[] outsums)
      Use this model to evaluate a context and return an array of the likelihood of each outcome given that context.
      Parameters:
      context - The names of the predicates which have been observed at the present decision point.
      outsums - This is where the distribution is stored.
      Returns:
      The normalized probabilities for the outcomes given the context. The indexes of the double[] are the outcome ids, and the actual string representation of the outcomes can be obtained from the method getOutcome(int i).

    • eval

      public static double[] eval(int[] context, double[] prior, EvalParameters model)
      Use this model to evaluate a context and return an array of the likelihood of each outcome given the specified context and the specified parameters.
      Parameters:
      context - The integer values of the predicates which have been observed at the present decision point.
      prior - The prior distribution for the specified context.
      model - The set of parametes used in this computation.
      Returns:
      The normalized probabilities for the outcomes given the context. The indexes of the double[] are the outcome ids, and the actual string representation of the outcomes can be obtained from the method getOutcome(int i).