python lightgbm 调参

在Python中进行LightGBM的调参可以通过设置一系列参数来实现。首先，可以调整学习率和估计器的数目。学习率（learning_rate）控制每个估计器对于前一个估计器的权重。较小的学习率可以使模型更加稳定，但可能需要更多的估计器来达到最佳性能。估计器的数目（num_estimators）表示要使用的决策树的数量，较大的数目可能会增加模型的复杂度。<span class="em">1</span><span class="em">2</span><span class="em">3</span>
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