发明名称 Maximizing mutual information between observations and hidden states to minimize classification errors
摘要 The present invention relates to a system and methodology to facilitate machine learning and predictive capabilities in a processing environment. In one aspect of the present invention, a Mutual Information Model is provided to facilitate predictive state determinations in accordance with signal or data analysis, and to mitigate classification error. The model parameters are computed by maximizing a convex combination of the mutual information between hidden states and the observations and the joint likelihood of states and observations in training data. Once the model parameters have been learned, new data can be accurately classified.
申请公布号 US7007001(B2) 申请公布日期 2006.02.28
申请号 US20020180770 申请日期 2002.06.26
申请人 MICROSOFT CORPORATION 发明人 OLIVER NURIA M.;GARG ASHUTOSH
分类号 G06F15/18;G10L15/14 主分类号 G06F15/18
代理机构 代理人
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