hai_knn_data_prepper: Prep Data for k-NN - Recipe

In healthyR.ai: The Machine Learning and AI Modeling Companion to 'healthyR'

Prep Data for k-NN - Recipe

Description

Automatically prep a data.frame/tibble for use in the k-NN algorithm.

Usage

hai_knn_data_prepper(.data, .recipe_formula)

Arguments

.data	The data that you are passing to the function. Can be any type of data that is accepted by the data parameter of the recipes::reciep() function.
.recipe_formula	The formula that is going to be passed. For example if you are using the iris data then the formula would most likely be something like Species ~ .

Details

This function will automatically prep your data.frame/tibble for use in the k-NN algorithm. The k-NN algorithm is a lazy learning classification algorithm. It expects data to be presented in a certain fashion.

This function will output a recipe specification.

Value

A recipe object

Author(s)

Steven P. Sanderson II, MPH

See Also

Other Preprocessor: hai_c50_data_prepper(), hai_cubist_data_prepper(), hai_data_impute(), hai_data_poly(), hai_data_scale(), hai_data_transform(), hai_data_trig(), hai_earth_data_prepper(), hai_glmnet_data_prepper(), hai_ranger_data_prepper(), hai_svm_poly_data_prepper(), hai_svm_rbf_data_prepper(), hai_xgboost_data_prepper()

Other knn: hai_glmnet_data_prepper()

Examples

library(ggplot2)

hai_knn_data_prepper(.data = Titanic, .recipe_formula = Survived ~ .)
rec_obj <- hai_knn_data_prepper(iris, Species ~ .)
get_juiced_data(rec_obj)

healthyR.ai documentation built on April 3, 2023, 5:24 p.m.