I m using a hidden markov model for classification, the jahmm implementation.
在培训一个模型一时,使用先式模型组群。 然后是使用任意的循环,优化模型。 我很想知道,这些灾难发生。
我的争.告诉我, se是建立在最初模式基础上的,而这种模式又被用于再培训。
is this true or is there something else which happens?
谢谢!
I m using a hidden markov model for classification, the jahmm implementation.
在培训一个模型一时,使用先式模型组群。 然后是使用任意的循环,优化模型。 我很想知道,这些灾难发生。
我的争.告诉我, se是建立在最初模式基础上的,而这种模式又被用于再培训。
is this true or is there something else which happens?
谢谢!
BaumWelch Learninger.java:
public <O extends Observation> Hmm<O>
learn(Hmm<O> initialHmm, List<? extends List<? extends O>> sequences)
{
Hmm<O> hmm = initialHmm;
for (int i = 0; i < nbIterations; i++)
hmm = iterate(hmm, sequences);
return hmm;
}
实际上,它正在每艘航程中再一次使用规定的观察顺序。 由于模型有时会慢慢到地方的顶峰,因此需要变形。 a. 起草一个类似方案,在每一版本之后看到模型:
BaumWelchLearner bwl = new BaumWelchLearner();
for (int i=0; i<=bwl.getNbIterations(); i++) {
Hmm iteration = bwl.iterate(yourHmm, learningSequences);
System.out.println("
Iteration " + i + ":
" + iteration.toString());
yourHmm = iteration;
}
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