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定义可能是错误的，如果是这样，请纠正我。我需要从以下类型的矩阵生成马尔可夫模型：

four    two "e"         
four    two "e"         
three   three   "e"         
one three   "e"         
zero    six one zero    "e" 
two two "e"         
two two "e"         
two two "e"         
two two "e"         
two two "e"         
four    zero    "e"         
two two "e"         
three   one three   "e"     
three   "e"             
four    one "e"         
three   one "e"         
two one one zero    two "e"
two five    "e"         
three   four    two "e"     
zero    five    "e"         
three   "e"             
three   three   "e"         
three   "e"             
one one "e"         
three   two "e"         
one one "e"         
three   two zero    zero    zero    "e"
three   three   "e"         
three   one "e"         
three   two "e"

我需要输出类似于： {"four":[{2:"two", 3:"one",2:"exit"},{...}],"three":[{.. .}]}

上面的数字基本上是转换到特定状态的次数。

我为此使用python。

回答常见的问题“您尝试过什么？”：“我尝试了几种方法，但它们并没有完全交付，所以我希望其中一个答案有助于澄清一些事情”。

非常感谢。

编辑，更新以显示完整的矩阵。

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2 回答 2

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您没有给出转换矩阵（这些将是概率），而是给出了由基础马尔可夫模型产生的一系列观察到的转换。

除非您有无限数量的这些观察结果，否则您无法准确地重建基础转换参数。但是，您可以选择转换，以使您的可观察序列最有可能。如果我理解您的问题，您应该研究Hidden Markov Models的解决方案。可以在这里找到一个免费提供的 python 模块 GHMM 。

于 2012-04-16T19:13:40.893 回答
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这是一个想法：与其尝试创建{"four":[{2:"two", 3:"one",2:"exit"},{...}],"three":[{...}]}（这在 python 中不太合法），不如尝试创建{"four":[{"two":2, "one":3, "exit":2},{...}],"three":[{...}]}（注意内部字典中顺序的变化）。

Iterate over the matrix, for each line:
  if the first word isn't in the big dictionary, add it.
  if the second word isn't in its sub-dictionary, add it, otherwise add 1 to its value.
于 2012-04-16T19:05:13.210 回答