After analyzing some normal evaluation functions for feature selection, a new evaluation function named the ratio of mutual information in feature selection was presented.
在分析了常用的一些特征选择的评价函数的基础上，提出了一个新的评价函数，即互信息比值。
There are many kinds of image fusion methods, such as information entropy, mutual information, mean square error, peak signal to noise ratio and mean grads.
医学图像融合的效果评价方法有很多，如信息熵、 互信息、均方值、峰值信噪比和平均梯度等。
The method "s performance is evaluated by using the entropy, cross-entropy, mutual information, error of mean square root and peak signal to noise ratio."
并采用熵、交叉熵、互信息、均方根误差和峰值信噪比等指标对该方法进行了客观评价。
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