h2o分布式随机森林最大特征参数
h2o Distributed Random Forest maximum features parameter
我正在对随机森林进行超参数调整，我想调整有关每棵树的最大特征的参数。通过 sklearn 的 documentation 是：
The number of features to consider when looking for the best split: If
int, then consider max_features features at each split.
If float, then max_features is a percentage and int(max_features * n_features) features are considered at each split.
If “auto”, then max_features=sqrt(n_features).
If “sqrt”, then max_features=sqrt(n_features) (same as “auto”).
If “log2”, then max_features=log2(n_features).
If None, then max_features=n_features.
我试过查看 h2o documentation 无济于事。
h2o 中是否存在此参数或您可以调整该参数的任何不同方式（例如特征日志）？
H2O 随机森林中此参数的名称是 mtries。
我正在对随机森林进行超参数调整，我想调整有关每棵树的最大特征的参数。通过 sklearn 的 documentation 是：
The number of features to consider when looking for the best split: If int, then consider max_features features at each split.
If float, then max_features is a percentage and int(max_features * n_features) features are considered at each split.
If “auto”, then max_features=sqrt(n_features).
If “sqrt”, then max_features=sqrt(n_features) (same as “auto”).
If “log2”, then max_features=log2(n_features).
If None, then max_features=n_features.
我试过查看 h2o documentation 无济于事。
h2o 中是否存在此参数或您可以调整该参数的任何不同方式（例如特征日志）？
H2O 随机森林中此参数的名称是 mtries。