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Packages that use Observation | |
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be.ac.ulg.montefiore.run.jahmm | This package is an Hidden Markov Model implementation. |
be.ac.ulg.montefiore.run.jahmm.io | This package holds classes that read and write Hidden Markov Model-related objects. |
be.ac.ulg.montefiore.run.jahmm.learn | This package holds Hidden Markov Model-related learning algorithms. |
be.ac.ulg.montefiore.run.jahmm.toolbox | This package holds Hidden Markov Model-related tool algorithms. |
Uses of Observation in be.ac.ulg.montefiore.run.jahmm |
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Classes in be.ac.ulg.montefiore.run.jahmm with type parameters of type Observation | |
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class |
Hmm<O extends Observation>
Main Hmm class; it implements an Hidden Markov Model. |
interface |
Opdf<O extends Observation>
Objects implementing this interface represent an observation probability (distribution) function. |
Subclasses of Observation in be.ac.ulg.montefiore.run.jahmm | |
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class |
ObservationDiscrete<E extends Enum<E>>
This class implements observations whose values are taken out of a finite set implemented as an enumeration. |
class |
ObservationInteger
This class holds an integer observation. |
class |
ObservationReal
This class implements observations made of a real value. |
class |
ObservationVector
This class holds an Observation described by a vector of reals. |
Methods in be.ac.ulg.montefiore.run.jahmm with type parameters of type Observation | ||
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protected
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ForwardBackwardCalculator.computeAlpha(Hmm<? super O> hmm,
java.util.List<O> oseq)
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protected
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ForwardBackwardScaledCalculator.computeAlpha(Hmm<? super O> hmm,
java.util.List<O> oseq)
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protected
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ForwardBackwardCalculator.computeAlphaInit(Hmm<? super O> hmm,
O o,
int i)
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protected
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ForwardBackwardCalculator.computeAlphaStep(Hmm<? super O> hmm,
O o,
int t,
int j)
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protected
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ForwardBackwardCalculator.computeBeta(Hmm<? super O> hmm,
java.util.List<O> oseq)
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protected
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ForwardBackwardScaledCalculator.computeBeta(Hmm<? super O> hmm,
java.util.List<O> oseq)
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protected
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ForwardBackwardCalculator.computeBetaStep(Hmm<? super O> hmm,
O o,
int t,
int i)
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Methods in be.ac.ulg.montefiore.run.jahmm with parameters of type Observation | |
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void |
Opdf.fit(O... oa)
Fits this observation probability (distribution) function to a (non empty) set of observations. |
void |
Opdf.fit(O[] o,
double[] weights)
Fits this observation probability (distribution) function to a weighted (non empty) set of observations. |
Uses of Observation in be.ac.ulg.montefiore.run.jahmm.io |
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Classes in be.ac.ulg.montefiore.run.jahmm.io with type parameters of type Observation | |
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class |
ObservationReader<O extends Observation>
Reads an observation up to (and including) the semi-colon. |
class |
ObservationWriter<O extends Observation>
Writes an observation up to (and including) the semi-colon. |
Methods in be.ac.ulg.montefiore.run.jahmm.io with type parameters of type Observation | ||
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static
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HmmReader.read(java.io.Reader reader,
OpdfReader<? extends Opdf<O>> opdfReader)
Reads a HMM from a text file. |
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static
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ObservationSequencesReader.readSequence(ObservationReader<O> oir,
java.io.Reader reader)
Reads an observation sequence out of a file Reader . |
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static
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ObservationSequencesReader.readSequences(ObservationReader<O> or,
java.io.Reader reader)
Reads observation sequences file. |
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static
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ObservationSequencesWriter.write(java.io.Writer writer,
ObservationWriter<? super O> ow,
java.util.List<? extends java.util.List<O>> sequences)
Writes a set of sequences to file. |
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static
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HmmWriter.write(java.io.Writer writer,
OpdfWriter<? extends Opdf<O>> opdfWriter,
Hmm<O> hmm)
Writes a HMM description. |
Uses of Observation in be.ac.ulg.montefiore.run.jahmm.learn |
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Classes in be.ac.ulg.montefiore.run.jahmm.learn with type parameters of type Observation | |
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class |
KMeansLearner<O extends Observation & CentroidFactory<? super O>>
An implementation of the K-Means learning algorithm. |
Methods in be.ac.ulg.montefiore.run.jahmm.learn with type parameters of type Observation | ||
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protected
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BaumWelchLearner.estimateXi(java.util.List<? extends O> sequence,
ForwardBackwardCalculator fbc,
Hmm<O> hmm)
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protected
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BaumWelchScaledLearner.estimateXi(java.util.List<? extends O> sequence,
ForwardBackwardCalculator fbc,
Hmm<O> hmm)
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protected
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BaumWelchLearner.generateForwardBackwardCalculator(java.util.List<? extends O> sequence,
Hmm<O> hmm)
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protected
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BaumWelchScaledLearner.generateForwardBackwardCalculator(java.util.List<? extends O> sequence,
Hmm<O> hmm)
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BaumWelchLearner.iterate(Hmm<O> hmm,
java.util.List<? extends java.util.List<? extends O>> sequences)
Performs one iteration of the Baum-Welch algorithm. |
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BaumWelchLearner.learn(Hmm<O> initialHmm,
java.util.List<? extends java.util.List<? extends O>> sequences)
Does a fixed number of iterations (see BaumWelchLearner.getNbIterations() ) of the
Baum-Welch algorithm. |
Uses of Observation in be.ac.ulg.montefiore.run.jahmm.toolbox |
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Classes in be.ac.ulg.montefiore.run.jahmm.toolbox with type parameters of type Observation | |
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class |
MarkovGenerator<O extends Observation>
Generates sequences of markovian observations given a HMM. |
Methods in be.ac.ulg.montefiore.run.jahmm.toolbox with type parameters of type Observation | ||
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KullbackLeiblerDistanceCalculator.distance(Hmm<O> hmm1,
Hmm<? super O> hmm2)
Computes the Kullback-Leibler distance between two HMMs. |
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