cv.h2odl: cross validation neural network h2o package
In fizlaz/DUN: Team DUN Kaggle milestone
Description
Usage
Arguments
Value
Description
five fold cross validation using h2o NN
Usage
1
cv.h2odl(train, epochs = 10)
Arguments
train
Any train set without ID and URL
epochs
Number of passes over the training dataset, default 10
Value
A list containing a vector of each fold accuracy and a mean.
fizlaz/DUN documentation built on May 16, 2019, 1:13 p.m.
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Description Usage Arguments Value
Description
five fold cross validation using h2o NN
Usage
1 | cv.h2odl(train, epochs = 10)
|
Arguments
train |
Any train set without ID and URL |
epochs |
Number of passes over the training dataset, default 10 |
Value
A list containing a vector of each fold accuracy and a mean.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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