Data set looks like:
- 25000 observations
- up to 15 predictors of different types: numeric, multi-class categorical, binary
- target variable is binary
Which cross validation method is typical for this type of problems?
By default I'm using K-Fold. How many folds is enough in this case? (One of the models I use is random forest, which is time consuming...)