algorithm - 减少错误修剪算法

Question

我有一个关于这个算法的问题:

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“永久修剪导致验证集准确性提高最大的节点”部分。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，但我的理解是提高准确性的节点是未修剪的节点，所以这句话与你不矛盾引用。也许它可以改写

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

让它更清晰。