hai_svm_rbf_data_prepper: Prep Data for SVM_RBF - Recipe

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

Prep Data for SVM_RBF - Recipe

Description

Automatically prep a data.frame/tibble for use in the SVM_RBF algorithm.

Usage

hai_svm_rbf_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 diamonds data then the formula would most likely be something like price ~ .

Details

This function will automatically prep your data.frame/tibble for use in the SVM_RBF algorithm. The SVM_RBF algorithm is for regression only.

This function will output a recipe specification.

Value

A recipe object

Author(s)

Steven P. Sanderson II, MPH

See Also

https://parsnip.tidymodels.org/reference/svm_rbf.html

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_knn_data_prepper(), hai_ranger_data_prepper(), hai_svm_poly_data_prepper(), hai_xgboost_data_prepper()

Other SVM_RBF: hai_auto_svm_rbf()

Examples

library(ggplot2)

# Regression
hai_svm_rbf_data_prepper(.data = diamonds, .recipe_formula = price ~ .)
reg_obj <- hai_svm_rbf_data_prepper(diamonds, price ~ .)
get_juiced_data(reg_obj)

# Classification
hai_svm_rbf_data_prepper(Titanic, Survived ~ .)
cla_obj <- hai_svm_rbf_data_prepper(Titanic, Survived ~ .)
get_juiced_data(cla_obj)

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