Gbdt（gradient boosting decision tree）是一种迭代的决策树算法，该算法由多棵决策树组成，从名字中我们可以看出来它是属于 boosting 策略。 gbdt 是被公认的泛化能力较强的算法。 总结： gbdt通过 迭代地拟合损失函数的负梯度 来逐步优化模型。 在每一次迭代中，它都会 基于当前模型 的 预测和真实的输出之间的差距 来训练一个新的决策树，然后将这个决策树的预.
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