my_rf_cv: random forest with k-fold cross validation
In seangrimm/PROJECT3PACKAGE: Package Building Project
Description
Usage
Arguments
Value
Examples
Description
Builds a classification model for the my_penguins data set to predict
body_mass_g based on bill_length_mm, bill_depth_mm, and
flipper_length_mm and applies k-fold cross-validation with
k = k.
Usage
1
my_rf_cv(k)
Arguments
k
Integer indicating how many folds train will be divided
into for k-fold cross-validation. Must have k >= 2.
Value
numeric representing the cross-validation error from the k-fold
cross-validation.
Examples
1
2
seangrimm/PROJECT3PACKAGE documentation built on March 22, 2021, 1:52 p.m.
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Description Usage Arguments Value Examples
Description
Builds a classification model for the my_penguins data set to predict
body_mass_g based on bill_length_mm, bill_depth_mm, and
flipper_length_mm and applies k-fold cross-validation with
k = k.
Usage
1 | my_rf_cv(k)
|
Arguments
k |
Integer indicating how many folds |
Value
numeric representing the cross-validation error from the k-fold cross-validation.
Examples
1 2 |
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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