My question on k-fold is not about evaluations of the model, but rather the coefficients that are returned by it.
In the R code below, I am performing 3-fold cross validation, which is to say the model is trained and tested three times. The keyword I am looking at is "trained".
My question is... how do the coefficient values get set? Is it an average of the three folds or another method?
library(caret) formula <- nos_yn ~ phone_conf_yn + nos10iact train_control <- trainControl(method = "cv", number = 3, summaryFunction = twoClassSummary, classProbs = T) model <- train(formula, data=training, trControl=train_control, method="glm", metric = "ROC", family=binomial(link="logit")) data.frame(summary(model)$coefficients[,1]) summary.model..coefficients...1. (Intercept) -2.1853334 `phone_conf_ynBad Phone Number` 0.7364689 phone_conf_ynConfirmed -1.2032336 `phone_conf_ynNull/Other` -0.6636189 nos10iact 0.3016733