How to approach the numer.ai competition with anonymous scaled numerical predictors?
I've looked at the approach and I'd select K by trying a range, i.e. 5k, 10k, 15k etc and then exploring the range in which the best result falls, say the best is 15k then I might do 13, 14, 15, 16, 17 and so on.

So far I've not found any pre-processing to be effective.

Answering the comment:

I've tried using LogisticRegression, SVM, Neural Networks, RandomForests, Multinomial NB, Extra Trees. All except Neural Networks using the implementations in sklearn. PyBrain for the NN.