my_knn_cv: k-Nearest Neighbors Cross-Validation
In samcho11/STAT302package: What the Package Does (One Line, Title Case)

Description Usage Arguments Value Examples

View source: R/my_knn_cv.R

This function splits the data into k groups for evaluating test set and training sets to predict the best value referring the neighbors.

1	my_knn_cv(train, cl, k_nn, k_cv)

`train`	Input data frame.
`cl`	True class value of your training data.
`k_nn`	Integer representing the number of neighbors.
`k_cv`	Integer representing the number of folds.

A list consists of a vector class comprised of prediction made by knn() function from class package, and misclassification rate cv_err, a value between 0 and 1 representing the proportion of observations that were classified incorrectly.

penguins <- STAT302package::my_penguins
penguins2 <- na.omit(penguins)
my_cl <- penguins2 %>% dplyr::pull(species)
result_nn1 <- my_knn_cv(penguins2[, 3:6], my_cl, 1, 5)