How can I adjust a deep neural network input layer to use a matrix as the input layer?

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Lynn Marciano
Lynn Marciano 2018-7-5
回答： Jahetbe 2022-2-9
I have a matrix of 419632 x 1420 doubles. I tried to create a custom deep neural network model but it seems as though the inputLayers that MATLAB provides are the imageInputLayer and sequenceInputLayer. I tried inputting my data as a sequenceInputLayer but when I did that, it wanted to make my model into a recurrent neural network; which is not what I want to do. Is there anyway to have basically a 'matrixInputLayer' or has anyone encountered this issue and could lead me in the right direction to get good insight to maybe create my custom input layer that handles matrices?
Thanks in advance.
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Alpha Bravo
Alpha Bravo 2018-7-7
A black and white image is basically a matrix. You could try to use [419632 1420 1] as the input dimension or somehow fool Matlab into thinking your matrix is a black and white image.

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回答（2 个）

Samuel Louis Sudhof
Samuel Louis Sudhof 2019-12-18
I have the same question. Telling matlab that it's somehow image data when it's not seems hacked. Isn't there a cleaner way to insert raw matrix data into a neural network?
Seems to me like the most basic input layer of a neural network is missing, if that's the case. What gives?
Jahetbe
Jahetbe 2022-2-9
nFeatures = 20;
nExamples = 10000;
nOutputs = 1; % this example is for setting up a regression problem
x = rand(nExamples,nFeatures);
t = rand(nExamples, nOutputs);
XNew = reshape(x', [1,1,size(x,2),size(x,1)]);
layers = [ ...
imageInputLayer([1 1 nFeatures]); % this layer needs the first 3 dimensions of input "XNew"
fullyConnectedLayer(10);
fullyConnectedLayer(nOutputs); % this connected layer needs to have an output-size same as the number of responses (columns) in the output data set "t"
regressionLayer];
options = trainingOptions('sgdm');
trainedNet = trainNetwork(XNew, t, layers, options);

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