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Scala Baum-Welch实现_Scala_Machine Learning_Hidden Markov Models - Fatal编程技术网

Scala Baum-Welch实现

Scala Baum-Welch实现,scala,machine-learning,hidden-markov-models,Scala,Machine Learning,Hidden Markov Models,我一直在努力解决机器学习课上的一个问题,但我似乎无法解决 如果我理解正确,算法的要点是: 期望: • For each sentence s in S: ○ For each word/tag pair (w,t): § For every occurence of w (at position i) in s: □ EmissionCounts(w,t) += (forward[t][i]*backward[t][i])/(sum of forw

我一直在努力解决机器学习课上的一个问题,但我似乎无法解决

如果我理解正确,算法的要点是:

期望:

• For each sentence s in S:
    ○ For each word/tag pair (w,t):
        § For every occurence of w (at position i) in s:
            □ EmissionCounts(w,t) += (forward[t][i]*backward[t][i])/(sum of forward[tag][N] for all tags)
    ○ For every tag/tag pair:
        § For every adjacent pair of words (starting at position i):
            □ TransitionCounts(t1,t2) += forward[t1][i]*P(t2|t1)*P(w[i+1]|t2)*backward[t2][i+1] / (sum of forward[tag][N] for all tags)
    ○ For every tag:
        § For the first word in the sentence:
            □ InitialCounts(t) = pi(t)*P(w[1]|t)*backward[t][1] / (sum forward[t][N] for all tags)
• For each tag t:
    ○ For every word w:
        § TagCounts(t) += EmissionCounts(w,t)
最大化:

• PI(t) = InitalCounts(t)/(# sentences)
• P(t2|t1) = TransitionCounts(t1,t2)/TagCounts(t1)
• P(w|t) = EmissionCounts(w,t)/TagCounts(t)
检查收敛性:

这是我的baum-welch算法的链接。有人知道我做错了什么吗

这里还有一个链接,指向整个回购协议:

是什么让你认为你搞错了?你有什么错误吗?输出不正确?根据任务描述,其准确率应为90%。我也觉得奇怪的是,对于每个句子,它用一个“,”标记对每个术语进行分类