Machine learning in trading: theory, models, practice and algo-trading - page 2314

 

Lopez De Prado's 2nd book is out, I liked the first one. The second promises to be no less interesting

 
Vladimir Perervenko:

How did you manage that?

And what is the output of what dimensions?

When forecasting the network, I pull out the states of the weights in the layers, the layers in the form of matrices, I make a dataset from the matrices and send it to "youmap". The output is 2 dimensions.

networks from the "neuralnet" package
 
mytarmailS:

When forecasting the network, I pull the states of weights in the layers, the layers as matrices, from the matrices I make a dataset and "yumap". The output is 2 dimensions.

networks from the "neuralnet" package

I see. So, what is the idea?

It makes sense to divide training data into parts and use non-intersecting parts when training each layer of the neural network. (Winwector's idea).Haven't tried it, but they claim it's useful.

Good luck

 
Vladimir Perervenko:

I see. What is the idea?

It makes sense to divide the training data into parts and use the non-intersecting parts when training each layer of the neural network. (Winwector's idea).Haven't tried it, but they claim it's useful.

Good luck

My idea was the following

1) to train neural network in some actions let it be bye/seat

2) the network on new data will make a lot of mistakes

3) I wanted to cluster the patterns in the layers of the network to see if I could separate the wrong decisions of the network from the right ones by looking at the patterns that occur in the network during signal processing...

=========

Vladimir, do you know if there is a package in R-ka where I can interact with the graphics, for example, so I can select an area on a graph with my mouse and get the parameters of this area in the code

 
A neural network is learning to trade on the real market.
This is a small real account on BitMEX.
Bot enters on public signals neuron and closes itself, full automatic.
Maximum pose of no more than 30% of the depo.
***

Now the initial easiest version, no stops, waiting for when it will sell everything))
 
Evgeny Dyuka:
Neuronet is learning to trade on the real market.
This is a small real account on BitMEX.
Bot enters on public signals neuron and closes himself, full automatic.
Maximum pose of no more than 30% of the depo.
***

Now the initial is the easiest version, no stops, waiting when it will sell out))
What happened to the account monitoring link?
 
Evgeny Dyuka:
and where did the link to monitor the account go?

Apparently the bot removes the link. Judging by how fast.

 
Valeriy Yastremskiy:

Apparently the bot removes links. Judging by how quickly.

The bot would have removed immediately, but it lasted ten minutes.

I know who this bot is))

 

New Catbust features

uncertainty prediction is an interesting thing, similar to Active Lerning, about which I wrote an article


 
But they explain it in such a way that it's easier to ask the Napoleons in the nuthouse
Reason: