Class MCMaxEntTrainer

    • Constructor Detail

      • MCMaxEntTrainer

        public MCMaxEntTrainer​(MCMaxEnt initialClassifier)
      • MCMaxEntTrainer

        public MCMaxEntTrainer()
      • MCMaxEntTrainer

        public MCMaxEntTrainer​(boolean useHyperbolicPrior)
      • MCMaxEntTrainer

        public MCMaxEntTrainer​(double gaussianPriorVariance)
        Constructs a trainer with a parameter to avoid overtraining. 1.0 is usually a reasonable default value.
      • MCMaxEntTrainer

        public MCMaxEntTrainer​(double gaussianPriorVariance,
                               boolean useMultiConditionalTraining)
      • MCMaxEntTrainer

        public MCMaxEntTrainer​(double hyperbolicPriorSlope,
                               double hyperbolicPriorSharpness)
    • Method Detail

      • setNumIterations

        public MCMaxEntTrainer setNumIterations​(int i)
        Specifies the maximum number of iterations to run during a single call to train or trainWithFeatureInduction. Not currently functional.
        This trainer
      • setUseHyperbolicPrior

        public MCMaxEntTrainer setUseHyperbolicPrior​(boolean useHyperbolicPrior)
      • setGaussianPriorVariance

        public MCMaxEntTrainer setGaussianPriorVariance​(double gaussianPriorVariance)
        Sets a parameter to prevent overtraining. A smaller variance for the prior means that feature weights are expected to hover closer to 0, so extra evidence is required to set a higher weight.
        This trainer
      • setHyperbolicPriorSlope

        public MCMaxEntTrainer setHyperbolicPriorSlope​(double hyperbolicPriorSlope)
      • setHyperbolicPriorSharpness

        public MCMaxEntTrainer setHyperbolicPriorSharpness​(double hyperbolicPriorSharpness)
      • getValueGradientCalls

        public int getValueGradientCalls()
        Counts how many times this trainer has computed the gradient of the log probability of training labels.
      • getValueCalls

        public int getValueCalls()
        Counts how many times this trainer has computed the log probability of training labels.
      • toString

        public java.lang.String toString()
        toString in class java.lang.Object