为 H2O 交叉验证选择的 nfolds 是否会改变所用数据的百分比？
Does the nfolds chose for H2O cross validation change the percentage of data used?
H2O 手册描述了如何拆分数据以进行 k 折交叉验证。给出的示例用于 5 折交叉验证。
请参阅此处：http://docs.h2o.ai/h2o/latest-stable/h2o-docs/data-science/algo-params/nfolds.html 其中指出：
"The first 5 models (cross-validation models) are built on 80% of the training data, and a different 20% is held out for each of the 5 models."
如果选择了不同的折叠值，这些百分比是否会有所不同，例如，假设选择了 10 作为折叠数，以下情况是否成立？
'The first 10 models (cross-validation models) are built on 90% of the training data, and a different 10% is held out for each of the 10 models.'
是的，你是对的。用于训练的数据百分比由折叠数决定。
H2O 手册描述了如何拆分数据以进行 k 折交叉验证。给出的示例用于 5 折交叉验证。
请参阅此处：http://docs.h2o.ai/h2o/latest-stable/h2o-docs/data-science/algo-params/nfolds.html 其中指出：
"The first 5 models (cross-validation models) are built on 80% of the training data, and a different 20% is held out for each of the 5 models."
如果选择了不同的折叠值，这些百分比是否会有所不同，例如，假设选择了 10 作为折叠数，以下情况是否成立？
'The first 10 models (cross-validation models) are built on 90% of the training data, and a different 10% is held out for each of the 10 models.'
是的，你是对的。用于训练的数据百分比由折叠数决定。