Machine learning in trading: theory, models, practice and algo-trading - page 3377
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The nature of the profit curve does not change by OOS: Size(OOS_Left) = Size(OOS_Right) = Size(Sample). All in all, a result you can't go past.
Well through re-optimisation with OOS checking can be found :)
Please disclose in a few sentences.
Please disclose in a few sentences.
I think everyone knows about wolf-forward. When optimised for sample, the results are taken from oos. The best overall result with averaged parameters is taken so that curves do not differ.
Let's say 100 steps are taken - we get 100 sets of input. If we form the average set according to the principle "each input set is equal to the average of the corresponding input 100 sets", it is unlikely that this set will pass well the whole initial interval.
Let's assume that 100 steps have been taken - 100 input sets have been obtained. If we form an average set according to the principle "each input set is equal to the average of the corresponding input 100 sets", it is unlikely that this set will pass well through the whole initial interval.
If it doesn't, there are no good sets at all, logically.
Not logical! Sets depend on FF, for example.
Illogical! Sets depend on the FF, for example.
I wonder, does anyone read this endless stream of articles called "neural networks are easy"?
I scroll down to the balance and realise that the man doesn't know the following saying:
"it's not enough to see here, here you have to look, here you have to think ... "
he studies the material superficially and his conclusions are not quite competent.Illogical! Sets depend on FF, for example.