How to use k fold cross validation in R

In this recipe , we shall learn how to perform cross validation in R. We shall be making use of k-fold cross validation for the same.

Recipe Objective: How to use k-fold cross-validation in R

Cross-validation is mainly done on a machine learning model to check how well the model performs on unseen data. It is always recommended to use cross-validation as the train, and test error will not be the same. The steps to use k-fold cross-validation are as follows-

Set seed to generate a reproducible random sampling

#setting seed
set.seed(123)

Define training control (it generates parameters that further control how models are created)

#define training control as cv (cross-validation) and value of k as 10
train_control <- trainControl(method = "cv",
number = 10)

Build the model

#building the model
#add any method as per your requirement
#eg: if classification, you can use method="nb"
#eg: if regression, you can use method="lm"
model <- train(y_label~., data = dataset,
trControl = train_control,
method = " ")

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