Machine learning in trading: theory, models, practice and algo-trading - page 3239
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Although non-tree models will take a very long time to learn. And the championship will become not about NS, but about trees/forests/busts)))))
It worked in the Marketplace.
Text and pictures are already enough.
Still not the first, if you think about Numerai at least. It's hard to disagree with the rest.
Although non-tree models will take a very long time to learn. And the championship will become not about NS, but about trees/forests/busts)))))
I don't know what kind of traders this is aimed at.
It looks like 5 people will participate in the contest, 4 of which are metaquotes employees who worked on integrating them into metatrader.
I'll be there.
"less people, more oxygen"))))))))))))))))))))))))))))))))))
I have a real EA with R, with the first variant of which I reached the tester.
The structure is as follows:
1. There is an ordinary mcl EA with the usual set of functions: working with orders, stops, MM..... The block of signal generation, in the examples of metaquotes - crossing of two mashes, is replaced by an appeal to R, which sends the next OHLC.
2. The R code roughly speaking consists of two parts:
2.1. converting the OHLC into a bunch of predictors for the models. These are hundreds (or thousands) of operators in R with access to some packages (not models) from R.
2.2. the actual signal computation by the model.
3. The signal for trading is sent back to the Expert Advisor: -1; 0; 1.
Returning to the topic, it turns out that to use ONNX p.2.2 will be ONNX, and in the Expert Advisor will have to move p.2.1? This is a serious undertaking for me, as besides the models themselves, other packages from R are used, the algorithms of which will have to be coded in µl.
You seem to use wooden models, and in ONNX, as I understand, you can only save network models. So, in essence, it will be a network model champion.
You seem to use wooden models, but in ONNX, as I understand, you can only save network models. So, in fact, it will be a network model championship.
Not true
What is?
What kind of things?
Which is what?
I've seen somewhere that you can put everything in ONNX that is available in the Scikit bible, and there are all sorts of models and quite a few.
Wooden models are also possible
I saw somewhere that you can put into ONNX everything that is available in the Scikit bible, and there are all sorts of models and quite a lot of them.
Well, I will not argue, I am not too strong in ONNX .