Because of the difficulty in calibrating parameters in the maximum information entropy models, the entropy method that can effectively select models is used to describe the system distribution.
鉴于最大信息熵模型中参数标定比较困难,提出了确定系统分布的熵方法。实验验证表明这种方法简单可行,是对最大信息熵原理的扩充。
A score function for optimization based on maximum mutual information entropy with odditional restriction is proposed.
提出了基于最大互信息熵且具有奇数约束的优化得分函数。
Based on the theory of maximum entropy, MEFS USES mutual information and Z-test technologies, and takes two-step method to execute feature selection.
MEFS在基于最大熵原理的基础上,运用互信息和Z -测试技术,采用两步方法进行空间特征选择。
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