fmeta.h2odl: h2o deep learning meta predictor
In fizlaz/DUN: Team DUN Kaggle milestone
Description
Usage
Arguments
Value
Description
Creates probabilities for each class
Usage
1
fmeta.h2odl(train, test = NULL, csv = FALSE)
Arguments
train
Train set without ID and URL
test
Test set without ID and URL. If left empty then it the
functions trains on train with 5 fold cross validation
csv
Boolean, default FALSE. If TRUE, saves csv output.
Value
A data frame with 5 probabilites for each row
fizlaz/DUN documentation built on May 16, 2019, 1:13 p.m.
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Description Usage Arguments Value
Description
Creates probabilities for each class
Usage
1 | fmeta.h2odl(train, test = NULL, csv = FALSE)
|
Arguments
train |
Train set without ID and URL |
test |
Test set without ID and URL. If left empty then it the functions trains on train with 5 fold cross validation |
csv |
Boolean, default FALSE. If TRUE, saves csv output. |
Value
A data frame with 5 probabilites for each row
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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