提出新的条件信息熵及其高效知识约简算法。
A new conditional entropy and knowledge reduction algorithms are proposed.
提出了一种基于条件信息熵的知识约简启发式算法，并指出该算法的时间复杂度是多项式的。
A heuristic algorithm based on conditional information entropy for knowledge reduction is proposed, and the complexity of this algorithm is analyzed.
论文中利用信息熵、条件熵公式推导出先验知识度划分标准公式，该公式把信息熵公式中加权和转换为加权和加先验知识度参数。
The formula of the prior knowledge classification standard was deduced used of the information entropy and the condition entropy formula, which add the priori knowledge parameter to the weighting sum.
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