Testing real-time forecasting systems - page 28
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It's my turn to post the first day of testing:
I would have given a prediction too, but only MASHKI FALLS )))))))))))
УБИТЬ ВСЕХ ЧЕЛОВЕКОВ )))
So the cartoon characters meet. What's "broken" about it, you only know how to bend. :о) And what does it all mean, I mean - what's the point of so many lines?
So the cartoon characters meet. And why is it "broken", you only know how to bend. :о) And what does it all mean, I mean - what's the point of so many lines?
Yep... )) especially in my sleep bending Rodriguez bender.
Doesn't mean anything. I just don't know how serious the topic is... Just thought I'd throw in a little humor.
And in general 3 colour mashas 24, 182, 600 Very well behaved. (Green is buy red is gone)
Punctuation is the most global trend.
It's just that sometimes artifacts come out like this. I should write to the author of this TC to fix it. Found it in kodobase, it's even fresh.
I see you like to play with parabolas, Professor.)
Still inventing? ))
Somehow it came out like this:
Or like this:
I've made some improvements to my GRNN. The accuracy of the predictions has improved slightly. Looking into the future, we get the following prediction
And I see you Professor like to play with parabolics ))))
No, it's not parabolic, it's pure statistics.
Still inventing? ))
This system is based on a "quantum neutrino" field (C) :o)
I've made some improvements to my GRNN. The accuracy of the predictions has improved slightly. Looking into the future, we get the following prediction
If it is not a trade secret, what has been finalised?
PS: I liked the non-linear AR prediction better, maybe - it's a very promising direction. But apparently identifying such a model is very difficult.
If it's not a trade secret, what has been finalised?
PS: I liked the non-linear AR prediction better, maybe - it's a very promising direction. But apparently identifying such a model is very difficult.
The refinement consisted of removing pattern price smoothing and increasing sigma (reducing cluster size) so that the closest patterns would influence the prediction.