Machine learning in trading: theory, models, practice and algo-trading - page 2127
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Two columns must be fed into the model - both sine and cosine for the clock. And sine + cosine for the day of the week. See the link for a description of why this should be done.
pi = 3.141529 ... from school.
Okay, I'll give you two...
And about pi, so the number may be too big - who knows what accuracy is required...
You have CATboost 😑
So, and? I wonder :))) Days of the week he spit out, now let's see in the new numbers wrap on the result.
So, and? I'm curious :))) Days of the week he spit out, now let's see in the new numbers wrap on the result.
Above added
You have CATboost 😑 just mark features as categorical
I can't add categoricality to MQL code :(
I have no way to load categoricality into MQL code :(
Okay, I'll give you two...
As for Pi, that number might be too high - who knows what accuracy is required...
7 digits is enough
Doesn't that lib work with kat chips?
No.
No.
saw this book a couple of years ago
It looks... Well, yes, it fascinates, but really - why? if the purpose of writing a diploma or PhD - yes, it's a board book
if the purpose of time series - this book is about something else, about the invention of the random forest at the dawn of the computer
imho, even ensembles of NS poorly accustomed to application in practice, how to work with BP? well, as an option to mess up a bunch of a lot of NS, and in the end you get autoecoder? - I doubt that even a convolutional network can be obtained with the help of this book
Old knowledge, Vorontsov is more relevant, and data processing - I'm chewing on some online courses on BP - there's something in it ;)
Train in python, there are 2 lines
I must have misunderstood your question.
There is no model interpreter on MT5 with categorization predictors and CatBoost with command line is able to do everything that python version does, except purely python things, such as visualization.