本文整理汇总了Python中hmm.HMM.influence方法的典型用法代码示例。如果您正苦于以下问题：Python HMM.influence方法的具体用法？Python HMM.influence怎么用？Python HMM.influence使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类hmm.HMM的用法示例。
在下文中一共展示了HMM.influence方法的1个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: HMM
# 需要导入模块: from hmm import HMM [as 别名]
# 或者: from hmm.HMM import influence [as 别名]
hmm = HMM(a, b, pi)
# Viterbi Test - It Works!!!
# obs = hmm.generate(100, True)
# (prob, path) = hmm.viterbi(obs)
# print prob
# for i in range(len(obs)):
# print str(obs[i])+' '+path[i]
# Learning Test
hmmLearn = HMM(a2, b2, pi2)
#Defines the influence that new observations have on previous probabilities
hmmLearn.influence = (3, 14)
# hmmLearn.generateMatrix(states, alphabet)
##Supervised Learning
# for x in range(50):
# hmmLearn.supertrain(hmm.generate(2000))
# print "-----"
# print hmmLearn.pi
# print hmmLearn.a
# print hmmLearn.b
##Unsupervised Learning (EM/Baum-Welch)
for x in range(100):
hmmLearn.baum_welch(hmm.generate(100, True))