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
Многие рассуждают о том чтобы сеть искала и учила правила, из многообразия правил входов, которые будут работать на прибыль......У меня другой вопрос....Возможноли, вернее, как научить сеть работать по готовым правилам?......Возмём канальную систему......Неважно как и при каких обстоятельствах строится канал. Как научить сеть работать внутрь канала или на его пробитии?????? Ну нейросетевые умы......что можете предложить по этому поводу?. Взять хотябы сеть без учителя.....Рекур, например. Как подготовить входы так, чтоб сеть поняла что от неё требуеться? если изначально имееться меняющийся со временем канал........
If we have ready-made rules, what the hell do we need a neural network for?!
The question is rhetorical, no need to answer.
By adding an input, in the form of a wrecker, you can increase the profitability of the system.....The network will calculate which breakthroughs are false or true, something like that.......
By adding an input, in the form of a wrecker, you can increase the profitability of the system.....The network will calculate which breakdowns are false which are true, something like that.......
You seem to overestimate the capabilities of neural networks.
To your post of 09.08.2009 21:00.
A network by itself cannot search for anything. It can only reveal some regularities (links between inputs and outputs; it is then possible to use the accumulated "knowledge" to calculate outputs in a situation on which the network has not been directly trained). That is, the search for patterns is only possible if and when they exist.
Now to your post of 09.08.2009 21:56.
If you know the regularities on channel penetration (your example) - why use a neural network when you can implement them more easily? Neural networks are a generalised approach; it's pointless to use a generalised one when a particular case is insanely simple. MAs can also be brought into the rulebook. There has to be a correlation between MA behaviour and channel breakdowns (and you have to be able to express that correlation). Neural networks don't work miracles by themselves.
p.s. So I'll answer your question: "Is it possible, or rather, how to teach a network to work with ready-made rules?" Yes, it is possible, if you have understanding of mathematics used in neural networks. By the way, a recurrent neural network is not the best example. Take something simpler (multilayer perceptron without feedbacks) - it's done there without any problems.
see an example of which inputs are fed to a neural network. http://www.nnea.net/research/18-neural-network-forecast-indicator
I couldn't find any entrances there...
I have discovered a couple of unpleasant things: 1. The network for some reason gives out only 2 output options. Thus it seems impossible to separate weak signals from strong ones. Is this a peculiarity of the 3-layer network? Maybe it is necessary to increase the number of layers? 2. RMS error is the smaller the closer the upper and lower output thresholds are to each other. When the thresholds are equal, the reading is at least 0.22. Is this normal?
No, this is not a feature of 3-layer nets, the signal at the grid output is a continuous function. Maybe you already have some sort of classifier built in at the grid output which gives the final signal, e.g. if the grid output is greater than 0.5 then 1, less than 0, or if the grid output is greater than 0.5 then 1, less than -1.
About thresholds, I don't understand yet, you should describe in detail everything that you have in your algorithm and how it is constructed, then it will be possible to think of questions which you ask...
I can't find any entrances there...
Neither did I... We can only assume that it's the number of squares in which the price has fallen, maybe some other additional conditions...
Perhaps MeteQuotes did not see the decompiler's advertising...