I have two data frames in R (training + test). The test set is not drawm splitted from one sample by myself but I got those two dataset and am supposed to built the model on the training set and make predictions with this model on the test set (without the target variable being in the validation set). I understand that predictions for the test dataset provided are only possible if we can confirm that training and test datasets have been follow the same distribution (are from one population).
In this [Non-parametric test if two samples are drawn from the same distribution post it has been discussed to use the Kolmogorov–Smirnov test. However, in R the
ks.test seems to only be possible to conduct on vectors. Would I therefore have to do this test for each numeric variable independently or is there a test/way to do that on the whole data set at once?