I am working on making prediction from 2d data. Data size is 7640x200x2; for each 200x2 matrix, I want a 2x1 array predicted from it. I am a beginner, and I am confused how to bulid a useful model. I have tried a cnn+lstm model, but the result was really bad. Could anyone please give me some advice?
1 Answers
Doesn't seem there are any sequences as said in the question, so LSTM isn't applicable here.
(200x2) --> (2,1) can be simply done by a dense network after flattening:
inp (200x2) --> flatten (to 400) --> dense(2, activation=identity)
2D convolutional layers may be put in between inp layer and flatten layer:
inp --> conv2d --> flatten
Depends on the range of the expected output, the activation in output dense layer can be changed, for example, use 'relu' instead of 'identity' if output is always positive.
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