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#Org.encog.ml.hmm Classes and Interfaces - 16 results found.
| Name | Description | Type | Package | Framework |
| BaseBaumWelch | This class provides the base implementation for Baum-Welch learning for HMM's. | Class | org.encog.ml.hmm.train.bw | HeatonReasearch |
| Clusters | Clusters used for the KMeans HMM training algorithm. | Class | org.encog.ml.hmm.train.kmeans | HeatonReasearch |
| ContinousDistribution | A continuous distribution represents an infinite range of choices between two real numbers. | Class | org.encog.ml.hmm.distributions | HeatonReasearch |
| DiscreteDistribution | A discrete distribution is a distribution with a finite set of states that itSee Also:Serialized Form | Class | org.encog.ml.hmm.distributions | HeatonReasearch |
| ForwardBackwardCalculator | The forward-backward algorithm is an inference algorithm for hidden Markov models which computes the posterior marginals of all hidden state variables | Class | org.encog.ml.hmm.alog | HeatonReasearch |
| ForwardBackwardCalculator .Computation | Class | org.encog.ml.hmm.alog | HeatonReasearch | |
| ForwardBackwardScaledCalculator | The forward-backward algorithm is an inference algorithm for hidden Markov models which computes the posterior marginals of all hidden state variables | Class | org.encog.ml.hmm.alog | HeatonReasearch |
| HiddenMarkovModel | A Hidden Markov Model (HMM) is a Machine Learning Method that allows for predictions to be made about the hidden states and observations of a given | Class | org.encog.ml.hmm | HeatonReasearch |
| KullbackLeiblerDistanceCalculator | This class produces a Kullback-Leibler estimation of the distance between two HMMs. | Class | org.encog.ml.hmm.alog | HeatonReasearch |
| MarkovGenerator | This class is used to generate random sequences based on a Hidden Markov Model. | Class | org.encog.ml.hmm.alog | HeatonReasearch |
| PersistHMM | Class | org.encog.ml.hmm | HeatonReasearch | |
| StateDistribution | This class represents a "state distribution". | Interface | org.encog.ml.hmm.distributions | HeatonReasearch |
| TrainBaumWelch | Baum Welch Learning allows a HMM to be constructed from a series of sequence observations. | Class | org.encog.ml.hmm.train.bw | HeatonReasearch |
| TrainBaumWelchScaled | Baum Welch Learning allows a HMM to be constructed from a series of sequence observations. | Class | org.encog.ml.hmm.train.bw | HeatonReasearch |
| TrainKMeans | Train a Hidden Markov Model (HMM) with the KMeans algorithm. | Class | org.encog.ml.hmm.train.kmeans | HeatonReasearch |
| ViterbiCalculator | The Viterbi algorithm is used to find the most likely sequence of hidden states (called the Viterbi path) that results in a sequence of observed | Class | org.encog.ml.hmm.alog | HeatonReasearch |