The novel online heuristic algorithm of representation based on polygonal boundary reduction is presented in detail.
提出了一种新颖的可在线计算的时间序列启发式算法。
A heuristic algorithm based on conditional information entropy for knowledge reduction is proposed, and the complexity of this algorithm is analyzed.
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。
In this paper, we propose a new attributes reduction algorithm based on the significance of attribute dependencies as heuristic information and add a certain variable precision.
粗糙集理论是一种新的数据挖掘算法，文章以属性依赖重要性作为启发信息提出了一种新的属性约简算法，且加入了一定的分类正确度。
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