Maxim Dmitrievsky #: And if there are very few signs, 3-5, will it be able to draw beautifully? The fewer signs, the better it can be on the test.
I think it depends on the data itself, if you take the data in the example, I think it can draw beautifully, but if you take real 100-dimensional data and shrink them by PCA to two-dimensional data, for example.
I don't know if it's 50/50.
It is better to include "good trading" on the test in the list of criteria in FF.
mytarmailS #: I think it depends on the data itself, if you take the data in the example, I think he can draw beautifully, but if you take real 100-dimensional data and shrink them PCA, for example, to two-dimensional.
I don't know if it's 50/50.
It is better to include "good trading" on the TEST in the list of criteria in FF.
Well, it's worth digging. I'll soon finish my new creation, and I'll post what I've got.
Maxim Dmitrievsky #: Why is that a problem? I've been doing it this way for a long time. There you can search both signs and teachers, like who forbids it :)
I don't see any problem either, you can search for both features and targets in one algorithm....
but from the computational point of view it's very inefficient, but that's another issue.
I didn't get into his reasoning, it takes him a long time to get his point across.
but Katschyik was right about the big bang (according to the latest observations), about black holes it is still unclear :))
Well there in the end he already about intelligence and Gpt says interesting things, but having missed the beginning, there is no sense to listen to the end.
Allow the use of cookies to log in to the MQL5.com website.
Please enable the necessary setting in your browser, otherwise you will not be able to log in.
You are signed in. Two-factor authentication has been disabled. Set it up again and scan a new QR code, or continue with two-factor authentication disabled.
Exactly.
And if there are very few signs, 3-5, will it be able to draw beautifully? The fewer signs, the better it can be on the test.
And if there are very few signs, 3-5, will it be able to draw beautifully? The fewer traits, the better on a test can be.
That's a wonderful idea to create a teacher.
What would it look like in practice?
1. Create a set of traits for an unknown teacher.
2. We create a teacher based on the set of attributes.
3. Ask the question: will these traits have predictive power in the future for the created teacher?
4. We check the stability of the predictive ability in the future . If they do - lucky, but if they don't pass the test? Then how?
The problem is that the teacher is created for the traits, and the opposite should be the case.
I think it depends on the data itself, if you take the data in the example, I think he can draw beautifully, but if you take real 100-dimensional data and shrink them PCA, for example, to two-dimensional.
Wonderful idea for creating a teacher.
What would it look like in practice?
1. Create a set of attributes to an unknown teacher.
2. By the set of attributes we create a teacher.
3. Ask the question: Will these attributes have predictive power in the future for the created teacher?
4. We test the stability of the predictive ability in the future . If they will - lucky, but if they don't pass the test? Then how?
The problem is that the teacher is created for the traits, when it should be the other way round.
Why is that a problem? I've been doing it this way for a long time. There you can search both signs and teachers, like who forbids it :)
I don't see any problem either, you can search for both features and targets in one algorithm....
but from the computational point of view it's very inefficient, but that's another issue.
About AI
I didn't get into his reasoning, it takes a long time to express something.
but Katschyik was right about the big bang (according to the latest observations), about black holes it is not clear yet :)
I didn't get into his reasoning, it takes him a long time to get his point across.
but Katschyik was right about the big bang (according to the latest observations), about black holes it is still unclear :))