cv_caret: Cross validation with a classification model built by caret

In tianwei-zhang/tianweiR: Utility Functions for Tianwei

Description

Cross validation with a classification model built by caret

Usage

cv_caret(df, method, n, formula, data_test, outcome_var)

Arguments

df	Dataframe containing the outcome and features to train model
method	Model type used by caret
n	number of cross validations to run
formula	a string to represent model formula used by caret
data_test	test data set
outcome_var	a string to indicate the outcome variable name

Examples

iris_select=iris%>%filter(Species %in% c('setosa','versicolor'))
iris_select$Species=as.character(iris_select$Species)
library(caret)
train_index=createDataPartition(iris_select$Species,times = 1,p = 0.8)$Resample1
data_test=iris_select[-train_index,]
data_train=iris_select[train_index,]
cv_caret(data_train,'rf',n=5,formula= 'Species~.',data_test=data_test,'Species')

tianwei-zhang/tianweiR documentation built on May 21, 2019, 3:03 a.m.