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for this specific case yes but for other complex stuff no
for this specific case yes but for other complex stuff no
But that's what I mean, as far as my imagination goes, I cannot think of a use case where you actually need that.
i've used it somewhere if i recall , something with distances .
And the ceo is playing around with ai so this came about from a need probably .
These libraries are supposed to be "faster" than any custom solution .
Also in this case you probably can get the benefit of initializing inside a compute unit if you utilize open cl , i assume
although , you will still initialize sequentially ... hmmi've used it somewhere if i recall , something with distances .
And the ceo is playing around with ai so this came about from a need probably .
These libraries are supposed to be "faster" than any custom solution .
Also in this case you probably can get the benefit of initializing inside a compute unit if you utilize open cl , i assume
although , you will still initialize sequentially ... hmmor we can't see what's coming up and it has to be this way
yeah , or its abandoned 😅
also , this stuff is brutal so@Lorentzos Roussos @Dominik Egert
I was just about to start with matrices and vectors, but reading this thread got me thinking again.
Tell me honestly, is it worth spending time to learn them? The documentation is very poor at explaining the correct ways to use them.
Example from https://www.mql5.com/en/docs/matrix/matrix_machine_learning/matrix_regressionmetrics
Another example at https://www.mql5.com/en/book/common/matrices/matrices_sle is used without the input parameter const vector& vctName!!!
So which one is correct?
Below is my first attempt and I got inconclusive results.
results :
Any clues as to what is wrong here?
The book was written in 2021-2022. Since then, MQL5 has changed a lot. In particular, the functions for working with matrices have changed: in RegressionMetric, the prototype has changed - a new first parameter has been added.
The source code of the MatrixForexBasket.mq5 example was corrected for it immediately after the announcement of the changes - see the 4th part in the codebase - https://www.mql5.com/en/code/45593.
Matrix Factorization: The Basics