Question

how do you compute the test error in 5-fold cross-validation?

Answer 1

In my language

k fold ch testing techniques we check on various testing data and various training days

Suppose you have 100 data usually uiuufit the mod on 80% data and 20%testing data.means 80/20,,

in cross validation you give k value suppose you give k=5,Then they divided your data 10equally part

K1,k2,k3,k4,k5

then build model various combination of group and testing also

like

train data k1,k2,k3,k4 and test data k5

train data k1,k2,k3,k5 and test data k4

train data k1,k2,k4 ,k5and test data k3

train data k1,k3,k4 ,k5and test data k2

train data k2,k3,k4,k5and test data k1

Advantage ge is all data cover in training period and testing period also then we combine all outputs...

thanks

belows theory I found on google...

The procedure has a single parameter called k that refers to the number of groups that a given data sample is to be split into. As such, the procedure is often called k-fold cross-validation. When a specific value for k is chosen, it may be used in place of k in the reference to the model, such as k=10 becoming 10-fold cross-validation.