Machine learning in trading: theory, models, practice and algo-trading - page 2392
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Is MLPClassifier also not suitable for this problem?
There is a method for estimating the probability of which class the sample belongs to.
https://scikit-learn.org/stable/modules/generated/sklearn.neural_network.MLPClassifier.htmlThese are different models. GMM is used for estimating probability density and sampling samples, and classifier classifies
Apparently you want to replace CatBoost with a neural network. But it doesn't make much sense.
These are different models. GMM is used to estimate probability density and sampling examples, while classifier classifies
Apparently you want to replace CatBoost with a neural network. But that doesn't make much sense.
there you write that a neural network is better than GMM
https://www.mql5.com/ru/forum/356331#comment_19373237
there you write that the neural network is better suited than GMM
https://www.mql5.com/ru/forum/356331#comment_19373237
You were talking about generative networks and autoencoders. I have tested classical versions, they are worse. I've already written in this thread before and the code was posted on the pitcher I think.
there you write that the neural network is better suited than GMM
https://www.mql5.com/ru/forum/356331#comment_19373237
Have a look at this modelhttps://sdv.dev/SDV/user_guides/timeseries/par.html
I haven't tried it myself, I need to generate and visualize it
as far as i understand, the model is in active development, you can communicate with the developers directly
+ I have sent a new article for testing, with new ideas
Thank you.
Thank you.
I am not installing the bible, a lot of errors. Probably not the actual version.
Pulls some version of nampai, which is not installed on either the computer or google colab
Reinstalling nampai in colab worked
Some kind of crooked monsters write these libraries.
Pulls some version of Nampai, which is not installed on a computer or google colab
This version 0.5.0 is fine.
https://pypi.org/project/sdv/0.5.0
This version 0.5.0 is fine.
https://pypi.org/project/sdv/0.5.0
In kolab ran the last one. Need to smoke the functionality of the model on the git, you can just copy the python module. Otherwise it is not clear how it works, there is no description in the manual.
And you can't google anything about it.
in the colab ran the last one. It is necessary to smoke the functionality of the model on the git, you can just copy the python module. Otherwise it is unclear how it works, there is no description in the manual.
pr_c = pr.copy() X = pr_c[pr_c.columns[1:]] sdv = PAR.fit(X)
I got to the fit, then the error: fit() missing 1 required positional argument: 'timeseries_data'
i think i need another format for feeding time series
https://sdv.dev/SDV/user_guides/timeseries/par.html