Machine learning in trading: theory, models, practice and algo-trading - page 1749
You are missing trading opportunities:
- Free trading apps
- Over 8,000 signals for copying
- Economic news for exploring financial markets
Registration
Log in
You agree to website policy and terms of use
If you do not have an account, please register
record a video with explanations, it's so unclear
Went to choose a color for the lamp...
Don't tell me there's a mistake, I searched ... did not find ... I hope that I will not find it))
A multidimensional function is an ordinary mathematical function whose definition area is a multidimensional space. In the case of NS it is the feature space.
I want to ask you as a mathematician - did you study mathematics at school at all?)
...
I mean that the "weight" language of the network, gives it universality, and it can work with any data types, (after converting them into "weight"). And this is unification (reduction to a single system/form).
the data is not converted into weight, but each instance is weighted, and each input begins to affect the final result differently
An artificial neuron is a purely mathematical object, it doesn't make any physical sense
so you have to understand it through mathematics
Download Heikin's book "neural networks full course".Went to choose a color for the lamp...
Don't tell me there's a mistake, I searched ... did not find ... I hope that I will not find it))
not much of a story
what's the method?
Learned. But, what does this have to do with the essence of the NS device?
From the mathematical point of view, any NS is a parametric family of multidimensional functions. A set of weights are the parameters that define this parametrization. Learning - defining specific values of weights, which corresponds to the selection of a particular multidimensional mapping from the original parametric family.
the data is not converted into weight, but each instance is weighted, with each input starting to affect the final result differently
The artificial neuron is a purely mathematical object, it doesn't make any physical sense
so you need to understand it through mathematics
download the book Haykin "neural networks full course"little history
what is the method?
1.spectral analysis
2.adaptive systems
3.forecasting
4.MO
5. And two dummies at the end of "DEMA" )))) for smoothing the signal
I haven't found an independent definition of "multivariate function". There is a "distribution function" of probability theory, and within it is a view of "multivariate distribution functions," but there is no mention of MO technology.
x=y+z, although yes, it is strange that definitions, if the arguments are more than 1 then it ... not on the fly.