Package opennlp.tools.ml.model

Schnittstelle MaxentModel

Alle bekannten Implementierungsklassen:
AbstractModel, GISModel, NaiveBayesModel, PerceptronModel, QNModel
public interface MaxentModel
Interface for maximum entropy models.

  • Methodenübersicht

    Modifizierer und Typ
    Methode
    Beschreibung
    double[]
    eval(String[] context)
    Evaluates a context.
    double[]
    eval(String[] context, double[] probs)
    Evaluates a context.
    double[]
    eval(String[] context, float[] values)
    Evaluates a context with the specified context values.
    String
    getAllOutcomes(double[] outcomes)
    Retrieves a string matching all the outcome names with all the probabilities produced by the eval(String[]) method.
    String
    getBestOutcome(double[] outcomes)
    Retrieves the outcome associated with the index containing the highest probability in the double[].
    int
    getIndex(String outcome)
    Retrieves the index associated with the String name of the given outcome.
    int
    getNumOutcomes()
     
    String
    getOutcome(int i)
    Retrieves the String name of the outcome associated with the index i.

  • Methodendetails

    • eval

      double[] eval(String[] context)
      Evaluates a context.
      Parameter:
      context - An array of String names of the contextual predicates which are to be evaluated together.
      Gibt zurück:
      An array of the probabilities for each of the different outcomes, all of which sum to 1.

    • eval

      double[] eval(String[] context, double[] probs)
      Evaluates a context.
      Parameter:
      context - An array of String names of the contextual predicates which are to be evaluated together.
      probs - An array which is populated with the probabilities for each of the different outcomes, all of which sum to 1.
      Gibt zurück:
      An array of the probabilities for each of the different outcomes, all of which sum to 1.

    • eval

      double[] eval(String[] context, float[] values)
      Evaluates a context with the specified context values.
      Parameter:
      context - An array of String names of the contextual predicates which are to be evaluated together.
      values - The values associated with each context.
      Gibt zurück:
      An array of the probabilities for each of the different outcomes, all of which sum to 1.

    • getBestOutcome

      String getBestOutcome(double[] outcomes)
      Retrieves the outcome associated with the index containing the highest probability in the double[].
      Parameter:
      outcomes - A double[] as returned by the eval(String[]) method.
      Gibt zurück:
      The String name of the best outcome.

    • getAllOutcomes

      String getAllOutcomes(double[] outcomes)
      Retrieves a string matching all the outcome names with all the probabilities produced by the eval(String[]) method.
      Parameter:
      outcomes - A double[] as returned by the eval(String[]) method.
      Gibt zurück:
      String containing outcome names paired with the normalized probability (contained in the double[] ocs) for each one.

    • getOutcome

      String getOutcome(int i)
      Retrieves the String name of the outcome associated with the index i.
      Parameter:
      i - The index for which the name of the associated outcome is desired.
      Gibt zurück:
      The String name of the outcome

    • getIndex

      int getIndex(String outcome)
      Retrieves the index associated with the String name of the given outcome.
      Parameter:
      outcome - The String name of the outcome for which the index is desired,
      Gibt zurück:
      The index if the given outcome label exists for this model, -1 if it does not.

    • getNumOutcomes

      int getNumOutcomes()
      Gibt zurück:
      Retrieves the number of outcomes for this model.