my_knn_cv: K Nearest Neighbors Cross Validation Function

In oliverlinehan41/project3package: Collection of Lab Functions from Stat 302 Class

Description

Function performs cross validation to determine appropriate "k" for k-nearest-neighbors.

Usage

my_knn_cv(train, cl, k_nn, k_cv)

Arguments

train	The dataset on which your model will be trained.
cl	The vector containing the actual classes of your observations.
k_nn	The number of nearest neighbors used to predict the class of an observation.
k_cv	The number of folds your training data will be divided into for cross-validation.

Value

A list containing vector "class", which contains the predicted classes using the entire data as training data, and the numeric "cv_err" which is the mean cross-validation error for your chosen "k".

Examples

library(dplyr)
library(class)
my_knn_cv(my_penguins, my_penguins$species, 1, 5)
my_knn_cv(my_penguins, my_penguins$species, 5, 5)

oliverlinehan41/project3package documentation built on Dec. 22, 2021, 4:21 a.m.