my_rf_cv: Random Forest Cross-Validation function
In Ranul-Liu/STAT302package: UW STAT302 Project3 Package
Description
Usage
Arguments
Value
Examples
Description
This function does Cross-Validation Random Forest prediction.
Usage
1
my_rf_cv(train, k_cv)
Arguments
train
A training data frame from my_penguins.
k_cv
An int representing the number of folds in cv.
Value
A number of the mean rate of cross-validation the MSE of predictions.
Examples
1
2
3
4
train <- na.omit(my_penguins) %>% dplyr::select(body_mass_g, bill_length_mm,
bill_depth_mm,
flipper_length_mm)
my_rf_cv(train, 5)
Ranul-Liu/STAT302package documentation built on Dec. 18, 2021, 9:52 a.m.
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Description Usage Arguments Value Examples
Description
This function does Cross-Validation Random Forest prediction.
Usage
1 | my_rf_cv(train, k_cv)
|
Arguments
train |
A training data frame from my_penguins. |
k_cv |
An int representing the number of folds in cv. |
Value
A number of the mean rate of cross-validation the MSE of predictions.
Examples
1 2 3 4 | train <- na.omit(my_penguins) %>% dplyr::select(body_mass_g, bill_length_mm,
bill_depth_mm,
flipper_length_mm)
my_rf_cv(train, 5)
|
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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