Discussion of article "Neural networks made easy (Part 3): Convolutional networks"
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Hello. Thanks for this. I have a question for you. How do you get the pixel values for the chart or image? I have looked but can't seem to find an explanation on how to derive the pixel values of the chart to use in the input convolutional layer.
New article Neural networks made easy (Part 3): Convolutional networks has been published:
Author: Dmitriy Gizlyk
Michael Mureithi Mbugua #:
Hello. Thanks for this. I have a question for you. How do you get the pixel values for the chart or image? I have looked but can't seem to find an explanation on how to derive the pixel values of the chart to use in the input convolutional layer.
Hello. Thanks for this. I have a question for you. How do you get the pixel values for the chart or image? I have looked but can't seem to find an explanation on how to derive the pixel values of the chart to use in the input convolutional layer.
Hello, you right. The convolution layer doesn't take pixels from chart. My idea was else. I take data from differnet indicators and historical price and put it to input of neural network. The conwolution layer looks patterns of this data and returns some value for every candle.
Dmitriy Gizlyk #:
Hello, you right. The convolution layer doesn't take pixels from chart. My idea was else. I take data from differnet indicators and historical price and put it to input of neural network. The conwolution layer looks patterns of this data and returns some value for every candle.
I understand, thanks.
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New article Neural networks made easy (Part 3): Convolutional networks has been published:
As a continuation of the neural network topic, I propose considering convolutional neural networks. This type of neural network are usually applied to analyzing visual imagery. In this article, we will consider the application of these networks in the financial markets.
Testing was performed using the EURUSD pair with the H1 timeframe. Two Expert Advisors, one with a convolutional neural network and the other one with fully connected network, were launched simultaneously on different charts of the same symbol, in the same terminal. The parameters of the fully connected layers of the convolutional neural network match the parameters of the fully connected network of the second Expert Advisor, i. e. we have simply added convolutional and subsampled layers to a previously created network.
Visually, you can see that signals appear less frequently on the convolutional neural network chart, but they are closer to the target.
Author: Dmitriy Gizlyk