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第460行： − 为了处理成千上万个变量的问题，一种不同的方法是必要的。一种是先对一种有序化进行取样，然后根据这种有序化找到最优的氮化硼结构。这意味着可能排序的搜索空间比网络结构的搜索空间小，因而方便。然后对多重排序进行采样和评估。这种方法已被证明在具有大量数据的可用文献时是最佳的。+
→Structure learning结构预测
In order to deal with problems with thousands of variables, a different approach is necessary. One is to first sample one ordering, and then find the optimal BN structure with respect to that ordering. This implies working on the search space of the possible orderings, which is convenient as it is smaller than the space of network structures. Multiple orderings are then sampled and evaluated. This method has been proven to be the best available in literature when the number of variables is huge.
In order to deal with problems with thousands of variables, a different approach is necessary. One is to first sample one ordering, and then find the optimal BN structure with respect to that ordering. This implies working on the search space of the possible orderings, which is convenient as it is smaller than the space of network structures. Multiple orderings are then sampled and evaluated. This method has been proven to be the best available in literature when the number of variables is huge.
为了处理成千上万个变量的问题，一种不同的方法是必要的。一种是先对一种有序化进行取样，然后根据这种有序化找到最优的氮化硼结构。这意味着可能排序的搜索空间比网络结构的搜索空间小，因而方便。然后对多重排序进行采样和评估。这种方法已被证明在所有文献中变量数量巨大的情况下是最佳的。