相对似然
This algorithm adopted the relative Bhattacharyya distance summation of each feature as the criterion function to select the features which contributed more to the reduction of classification error. These features then could be used for Gaussian maximum likelihood classification.
该算法以各特征的相对Bhattacharyya和作为准则函数选择能有效降低分类错误率的一组特征,最后利用这组特征进行高斯似然分类。
For any information source on a countable set, the limit properties of relative likelihood ratio and log-likelihood ratio of entropy density with respect to the independent geometry distribution, an important problem in the information theory is discussed.
对任意的可列集上的信息源,探讨信息论的-个重要问题,即探讨了相对于独立型几何分布的熵密度似然比与对数似然比的极限性质。
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