Parameter tuning and algorithm selection! I just don’t want to manually start 5 different runs of algorithms i believe which could work good on the data and manually compare the results. And maybe i was too lazy to run the 6th algorithm which now performs much better.

But to be sure, every test should be done with k-fold cross validation. The decision whether to split the training set should not be chosen by the user. It‘s crucial that this is a must!