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java.lang.Objectbe.ac.ulg.montefiore.run.jahmm.learn.KMeansLearner<O>
public class KMeansLearner<O extends Observation & CentroidFactory<? super O>>
An implementation of the K-Means learning algorithm.
Constructor Summary | |
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KMeansLearner(int nbStates,
OpdfFactory<? extends Opdf<O>> opdfFactory,
java.util.List<? extends java.util.List<? extends O>> sequences)
Initializes a K-Means algorithm implementation. |
Method Summary | |
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boolean |
isTerminated()
Returns true if the algorithm has reached a fix point,
else returns false . |
Hmm<O> |
iterate()
Performs one iteration of the K-Means algorithm. |
Hmm<O> |
learn()
Does iterations of the K-Means algorithm until a fix point is reached. |
Methods inherited from class java.lang.Object |
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clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
Constructor Detail |
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public KMeansLearner(int nbStates, OpdfFactory<? extends Opdf<O>> opdfFactory, java.util.List<? extends java.util.List<? extends O>> sequences)
nbStates
- The number of states the resulting HMM will be made of.opdfFactory
- A class that builds the observation probability
distributions associated to the states of the HMM.sequences
- A vector of observation sequences. Each observation
sequences is a vector of
observations
compatible with the
k-means algorithm
.Method Detail |
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public Hmm<O> iterate()
public boolean isTerminated()
true
if the algorithm has reached a fix point,
else returns false
.
public Hmm<O> learn()
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