cv.rfmc: cross validation random forest multicore
In fizlaz/DUN: Team DUN Kaggle milestone
Description
Usage
Arguments
Value
Description
five fold cross validation using random forest
Usage
1
cv.rfmc(train, tree = 1000, core = 4)
Arguments
train
Any train set without ID and URL
tree
Number of trees, default 1000
core
Number of cores, default 4
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 random forest
Usage
1 | cv.rfmc(train, tree = 1000, core = 4)
|
Arguments
train |
Any train set without ID and URL |
tree |
Number of trees, default 1000 |
core |
Number of cores, default 4 |
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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