Data classification of statistical configuration

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I am trying to build a neural network to classify data, my data are thousands of txt files, every file represent a 2D dimensional array with values 1 or -1, every array represent one configuration, and the labels that I should have are just two labels

I need a startup code snippet that build the network and train it

What I have tried:

I converted all of these txt files into images of black and white, and I used ML.NET through VS to train a network that is already built (I don't know anything about the structure of this network, it is hidden) then I wrote code to test it and it works very good

but this is nit what I need, I need to classify them without the need to convert them to images, and I want to build my own neural network, that I can control its structure at any point

Note: I just started this field, don't blame me if you find my question is very naïve or simple

Posted 17-May-23 9:20am

Sabry1905

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[no name] 18-May-23 10:57am

If this particulare neural net expects an "image file", a text file won't do it. The text may represent image pixels, but that's still not an "image file". Even if it did work, it would probably be using a "plugin" which is effectively what you created (according to your post).

Sabry1905 18-May-23 12:35pm

I don't want to use images, I want to use txt files, because my configuration files will be higher dimensions more than two.

What I need is a startup code that build the network and train it, a network that expects txt files as an input

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