my_knn_cv: k-Nearest Neighbors Cross-Validation Function

In achew20/project3Package2021: What the Package Does (One Line, Title Case)

Description

Predicts an output class of a given training data using the k-Nearest Neighbors non-parametric statistical prediction method and cross-validation.

Usage

my_knn_cv(train, cl, k_nn, k_cv)

Arguments

train	Data frame of numeric and string values intended as training data (with no NA values).
cl	The true class value of the training data, train (with no NA values).
k_nn	Numeric value representing the number of neighbors.
k_cv	Numeric value representing the number of folds for cross-validation.

Value

List containing predicted class (y-hat) for all observations in train, and a numeric value representing the cross-validation misclassification error.

Examples

ex_penguins <- na.omit(my_penguins)
my_knn_cv(train = ex_penguins[,c(3:6)], cl = ex_penguins$species, k_nn = 1, k_cv = 5)

achew20/project3Package2021 documentation built on Dec. 18, 2021, 10:22 p.m.