Machine learning in trading: theory, models, practice and algo-trading - page 1332
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You don't want to talk about sampling, fine. Thanks for the suggestion to read the specific literature.
But, I do not understand your logic about Seed - each time you start model creation, a random variable is generated, which can be fixed with parameter Seed, this variable affects model creation, so the statement "Do you build a model or random events" brings me to a logical stupor - explain your thought, please.
Models are built on predictor relationships, Seed affects the formation of those relationships, and hence model building. What is the contradiction - I can not understand!?
Besides, in lectures it's recommended to brute force this Seed, including yesterday's video on CatBoost seed in python file example is fixed - obviously obtained by brute force.I wrote, but it all got deleted... Read the books, I am too tired to retell their content.
That's exactly what he used, there's the MSUA lib, MLP and SVM
This is a bicycle. Using basic things and introducing certain features we get something new.
Isn't his product any better than MSUA, MLP and SVM taken separately? (if only because he combined them in one program).
This is the bicycle. Using basic things, and making some features we get something new.
Is his product better than MSUA, MLP and SVM taken separately? (at least by the fact that he combined them in one program)
What do you mean something better? that it takes 10 hours to train because mikhailo trained it on datasets of 100 points?
And where are the proven results?
exactly it is about that if with standard means and approaches it is not possible to reach the goal, then these MO perversions precisely will not lead to anything good.Anyway... I wrote but it all got deleted... read the books, I don't want to retell their contents.
...
What do you mean something better? that it takes 10 hours to train because mikhailo trained it on datasets of 100 points?
And where are the proven results?
I'm just saying that if standard means and approaches fail to achieve the goal, these M.O. perversions will certainly not lead to anything good.That's exactly why I didn't study it in detail.
And about the fact that someone uses it - you said (whether about toxic, or about visard).
And about using only standard tools, I still don't agree. Otherwise science would have stood still and we would still be sitting in caves and studying location of embers in the fire, predicting fatness of mammoth tomorrow.)
Alexei's results look good. We just need to check on the account/signal for a year. Unfortunately he has such a time frame... with drawdowns for half a year. If I were him, I'd look into something less long term. Even a one week drawdown would make me want to fix something.
And so the argument is about nothing. Someone likes to invent something, he invents. Who doesn't like it, doesn't invent.
It's like in science - you can set up 1000 experiments of which 999 will be unsuccessful and only 1 will lead to the discovery of something new and useful. But 999 unsuccessful experiments will of course take a lot of your time. So it is better to do it when you are well provided for (salary/grant/sponsor/own funds). In our field would also be a supercomputer, so that not 10 hours, but 10 minutes of calculation took.
That's exactly why I didn't study it in detail.
And about the fact that someone uses it - you said (either about toxic, or about wizard).
And about using only standard tools, I still do not agree. Otherwise science would have stood still and we would still be sitting in caves and studying the location of embers in the fire, predicting the fatness of tomorrow's mammoth)))
Alexei's results look good. We just need to check on the account/signal for a year. Unfortunately he has such a time frame... with drawdowns for half a year. If I were him, I'd look into something less long term. Even a one week drawdown would make me want to fix something.
What I'm saying is that the results are predictable and based on theory.
you don't have to do a lot of unnecessary work, although it may be useful
We are just talking about different things and examples are beside the point.