决策树以图形方式描述导致某项操作的相关条件链。

Decision trees graphically depict chains of dependent conditions leading to an action.

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该方法运用了粗糙集理论中条件属性相对于决策属性的核，引入启发式条件计算并选择条件属性作为决策树的根结点或子结点。

The method adopts the core of condition attributes with respect to decision attributes, and calculates condition of heuristic to find root or root of subtree.

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并且该算法改进了决策树创建叶节点的条件，从而决策树不会用尽所有的候选属性才停止构造，这就消除了没有原始数据造成的影响。

And the algorithm improves the ending condition of building decision tree which don't stop constructing from using all of the attributes. So it has no influence on original data.

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