Package org.ptolemy.machineLearning.hmm

Class HMMExponentialEstimator

  • All Implemented Interfaces:
    java.lang.Cloneable, Actor, Executable, FiringsRecordable, Initializable, TypedActor, Changeable, Debuggable, DebugListener, Derivable, Instantiable, ModelErrorHandler, MoMLExportable, Moveable, Nameable
    public class HMMExponentialEstimator
extends ParameterEstimator

    This actor implements a parameter estimator for Hidden Markov Models with exponential emissions. The base class ParameterEstimator performs the parameter estimation and the HMMGaussianEstimator class contains density-specific methods for the exponential PDF calculations and produces the relevant estimates at its output ports.

    The output ports for an exponential HMM model is the lambda vector that contains the rate estimates of the exponential distributions in each possible emission category.

    The user-defined parameters are initial guesses for the model parameters, given by lambda0, the rate vector guess, prior, the prior state distribution guess and A0, the transition matrix guess. iterations is the number of EM iterations allowed until convergence. If, during iteration, the conditional log-likelihood of the observed sequence given the parameter estimates converges to a value within likelihoodThreshold, the parameter estimation stops iterating and delivers the parameter estimates.

    Since:
    Ptolemy II 10.0
    Version:
    $Id$
    Author:
    Ilge Akkaya
    Pt.AcceptedRating:
    Pt.ProposedRating:
    Red (ilgea)