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forward-backward algorithm
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forward-backward algorithm
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计算语言学
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forward-backward algorithm
向前-向后算法
从隐马尔可夫模型的参数λ= (A,B)的某个初始估计开始(λ是模型参数;A是转移概率;B是发射概率),迭代地运行期望化和最大化两个步骤,向前向后不断地重估A和B的概率,对于给定观察序列O和隐马尔可夫模型中可能状态的集合,自动地训练隐马尔可夫模型的参数A和B,这样的算法叫作向前-向后算法。又称鲍姆-韦尔奇算法(Baum-Welch algorithm)。
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