Class PerceptronModel

java.lang.Object
opennlp.tools.ml.model.AbstractModel
opennlp.tools.ml.perceptron.PerceptronModel
All Implemented Interfaces:
MaxentModel

public class PerceptronModel extends AbstractModel
A model implementation based one the perceptron algorithm.

Each outcome is represented as a binary perceptron classifier. This supports standard (integer) weighting as well average weighting as described in: Discriminative Training Methods for Hidden Markov Models: Theory and Experiments with the Perceptron Algorithm. Michael Collins, EMNLP 2002.

  • Constructor Details

    • PerceptronModel

      public PerceptronModel(Context[] params, String[] predLabels, String[] outcomeNames)
      Initializes a PerceptronModel.
      Parameters:
      params - The parameters to set.
      predLabels - The predicted labels.
      outcomeNames - The names of the outcomes.
  • Method Details

    • eval

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

      public double[] eval(String[] context, float[] values)
      Evaluates a context with the specified context values.
      Parameters:
      context - An array 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 double[] eval(String[] context, double[] probs)
      Evaluates a context.
      Parameters:
      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.
      Returns:
      An array of the probabilities for each of the different outcomes, all of which sum to 1.
    • eval

      public double[] eval(String[] context, float[] values, double[] outsums)
    • eval

      public static double[] eval(int[] context, double[] prior, EvalParameters model)
      Evaluates a PerceptronModel.
      Parameters:
      context - The context parameters as int[].
      prior - The data prior to the evaluation as double[].
      model - The EvalParameters used for evaluation.
      Returns:
      The resulting evaluation data as double[].
    • hashCode

      public int hashCode()
      Overrides:
      hashCode in class AbstractModel
    • equals

      public boolean equals(Object obj)
      Overrides:
      equals in class AbstractModel