减少错误修剪算法

Question

我对这个算法有疑问：

Partition training data in “grow” and “validation” sets.
Build a complete tree from the “grow” data.
Until accuracy on validation set decreases do:
    For each non-leaf node, n, in the tree do:
        Temporarily prune the subtree below n and replace it with a leaf labeled with
                                              the current majority class at that node.
        Measure and record the accuracy of the pruned tree on the validation set.
    Permanently prune the node that results in the greatest increase in accuracy on the
                                                                         validation set.

我不明白那部分"Permanently prune the node that results in the greatest increase in accuracy on the validation set." 我们应该保留提高准确性的节点并修剪那些提高错误率的节点。我错了吗？

Answer 1

我什至不知道这个算法适用于哪个领域，但据我了解，提高准确性的节点是未修剪的节点，所以没有你引用的短语自相矛盾。也许可以改写

permanently prune the node that, when pruned, causes the greatest increase in accuracy on the validation set

为了更清楚。