Machine learning in trading: theory, models, practice and algo-trading - page 3003
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Please clarify how LOSS_CCE is considered in MQL5 (if it works at all). People have already asked in this thread for explanations about the implementation of all the loss functions specified in the ENUM_LOSS_FUNCTION enumeration, but there was no answer. And if, for example, LOSS_BCE is counted, then for LOSS_CCE I always get 0, no matter what matrix I put in. In short, it doesn't work with any of the tips - keras, numpy.
Here are the sources in MQL5. With the sources where the calculation formulas are taken from.
vector,
probably the most useful thing in trading
Here are the sources in MQL5. With the sources where the calculation formulas are taken from
How does this relate to the matrices and examples of "parallel" platforms I gave above?
For example, I take matrices from the link to keras, call for them:
and get zeros.
I'm completely out of the loop, but I'm wondering if a price can be represented by a graph, and if it has any advantage over the usual two-dimensional representation.
If you have an imagination, you can represent the price with a bipartite graph. But it is better to imagine that she is a lady at heart :-)
if you have imagination, imagine the price as a bipedal count. But it is better to imagine that she is a lady at heart :-)
The count has no shares.
That leaves "lady in the shower.")
so that leaves "lady in the shower.")
I'm completely out of the loop, but I'm wondering if a price can be represented by a graph, and if it has any advantage over the usual two-dimensional representation.
Are Markov chains already boring? )
The failure of MO algorithms in trading is quite obvious and is not related to their type.
the prediction problem is incorrectly set.
1)Are the Markov chains getting boring yet? )
2) the failure of MO algorithms in trading is quite obvious and is not related to their type.
3)the prediction problem is incorrectly posed