We can show by inspection that the algorithm proceeds sequentially and the proof is already halfway there.

通过观察可知，算法继续进行，证明已经完成了一半。

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The proposed algorithm is then compared with the commonly used DR algorithm, and we show that our algorithm is very effective.

最后，将提出的这种自适应DR算法与普通DR算法进行了比较研究。

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The paper offer a new heuristic attribute reduction algorithm based on conditional granularity entropy, though running an example, we show that this algorithm is effective.

提出了一种基于条件粒度熵的属性约简的启发式算法，通过例子分析，表明该算法是有效的。

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