Thursday, 2 August 2012

Results of Comparative Cross Validation Tests

As expected the NN achieved 100 % accuracy and my prediction of 20 % to 30 % accuracy for my current Naive Bayesian Classifier was more or less right - in various runs of sample sizes up to 50,000 it achieved accuracy rates of 30 % to 33 %. A screen shot of both classifiers applied to the last 200 days worth of S & P futures prices is shown below, with the Naive Bayesian in the upper pane and the NN in the lower pane.
However, despite it vastly superior performance in the tests, I don't really like the look of the NN on real data - it appears to be more erratic or noisier than the Bayesian classifier. I suspect that the NN may be overly complex, with 54 nodes in its one hidden layer. I shall try to improve the NN by reducing the number of hidden layer nodes to 25, and then seeing how that looks on real data.


vectorman said...

Thank you for sharing lots of brilliant the posts and your attention to detail. Really excited to hear about your NN progress....and out of sample accuracy...I know this is a big commitment so have avoided using any ML so far.

Dekalog said...

@vectorman - Thanks for your kind words - it's nice to hear that my blog posts are appreciated.