Parameters: { "min_child_samples", "num_leaves" } are not used.
时间: 2023-11-06 13:04:58 浏览: 37
As an AI language model, I can tell you that "min_child_samples" and "num_leaves" are parameters used in the LightGBM model for gradient boosting. These parameters control the complexity of the model and the amount of data used for each split.
If they are not used, it means that either the default values are used or the code has been modified to not use these parameters. However, using these parameters can improve the performance and accuracy of the model, so it is recommended to experiment with different values to find the optimal settings for your specific use case.
相关问题
min_child_samples作用
min_child_samples是LightGBM中的一个参数,它指定了每个决策树节点(非叶子节点)必须要包含的最小训练样本数。如果某个节点的样本数小于该值,则该节点将不再分裂(成为叶子节点),这可用于防止过拟合。
min_child_samples的取值应该根据数据集的大小和特征维度进行调整。如果数据集较小,可以选择较小的值,例如100。如果数据集较大,可适当增大该值,例如1000或更大。较大的值可以降低模型的方差,但可能会增加偏差。因此,需要根据实际情况和交叉验证结果进行调整。
min_child_samples详解
min_child_samples是LightGBM中的一个参数,它指定了每个决策树节点最少需要的样本数。当样本量较大时,可以适当增大该参数以加快训练速度,但是如果样本量较小,则应该减小该参数以避免过拟合。