Recent content by fabwa

Maybe it was just some semester project. Nobody really cares about its validity, its not a scientific publication.. :smart:

Before trading this live, i would suggest you to run historical forward tests of a few years.. dont gamble :-)

HI Krzysztof, glad you are still working on it. The persistent do win the races ;-) from your last posts you claim you had some success recently, happy to hear that. Your last graph puzzles me a little bit tho. To me it is not really clear what i am seeing there, maybe you can shed some light...

OK - fair enough :) let me do further analysis - tho if there is dependence involved my approach is likely to minimize its effect. For every bar of interest i am just looking at its 20 ancestors for feature computation (to the previous bar of interest its 288 bars) Therefore i imagine it like a...

Thx for your comment, though i think you lack some of the information of my approach to proof your points: i am only looking at x bars on a low TF before market opening to compute the features (where x is small). Then all my samples are randomly shuffled. I do know that this approach implies...

Just sharing a quick analysis: using a range of features with random forests applied on EU market open (5min bar) over the last 3 years the out of bag sample error of the training data scores considerably higher than randomness. samples where constructed on TP hit within 1 hour (in both...

One remark here, i dont know about your exact approach but i also see possible bias here: How did you optimize the external model parameters like input space, network structure, voting scheme? If you just picked these according to your results above, its biased. I agree this is a general issue...

What a coincidence to see you here! I am the one commenting your blogpost 2 days ago (clustering for mathematical expectation optimization) :) welcome to the discussion!

i would say stop trying algorithms, start understanding them! my last bit for now: http://de.slideshare.net/Pammy98/using-random-forest-proximity-for-unsupervised-learning-in-tissue

Do what you have to do :)

When i say tree i am talking ensembles of tree i.e. Random Forests, further i would never promote that one classifier is better than another its always case specific.. see this IEEE classification challenge 2013 http://hyperspectral.ee.uh.edu/?page_id=695 Winner team used random forests

:thumbsdow We are getting emotional.. I do have a sound background with 2 degrees in Machine Learning, Mathematics and Statistics and research industry experience. Part of that was intense time series analysis. If you refer to SO questions like "What is the best Classifier [closed]" that tells...

Do i hear some complains there? :cool: I am very busy at the moment- i just tried to give some from my view useful tips for now.. @RF: as i stated earlier your performance analysis form my point of view is flawed. And statements like "i tried RF but it didnt perform well" cant be taken...

RF is one of these ensemble methods :) interested in your results for sure

http://en.wikipedia.org/wiki/Boosting_(meta-algorithm)