Error using trainNetwork. Number of observations in X and Y disagree

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Tanner Hayes
Tanner Hayes 2020-7-30
编辑： Matt J 2024-1-26
Hello!
This is my first time building a neural net and am slowly working through the process.
What I am trying to do:
I have ~40,000 rows of data with 61 columns. Each row corresponds to a spectrum of a body's surface, and each column is an observation of that surface at a different wavelength. I am trying to make a neural net that can take each row in as an input (1 x 60 double) and tell me whether or not it falls into group 1 or group 2. The first column in the 40,000 x 61 array is the label 1 or 2.
I have tried to follow https://www.mathworks.com/help/deeplearning/ug/create-simple-deep-learning-network-for-classification.html but it is not very useful for me since my data is not kept in an image datastore. I am also trying to make a 1-D cnn layer (though I am new to this and am not sure that is the best option for what I am trying to do).
I have tried reshaping my data into a 4-D array such that
>> whos nnTrainLabels
Name Size Bytes Class Attributes
nnTrainLabels 32373x1 32603 categorical
>> whos reshapedData
Name Size Bytes Class Attributes
reshapedData 1x32373x1x60 15539040 double
But I keep getting the error message
Error using trainNetwork (line 170)
Number of observations in X and Y disagree.
Here is the code I am trying to run:
height = 1;
widthTrain = size(nnTrainSet,1);
channels = 1;
sampleSizeTrain = size(nnTrainSet,2);
layers = [
imageInputLayer([height, widthTrain, channels])
% convolution2dLayer([3 1], widthTrain)
% batchNormalizationLayer
% reluLayer
fullyConnectedLayer(2)
softmaxLayer
classificationLayer];
options = trainingOptions('sgdm', ...
'MaxEpochs', 200, ...
'Plots', 'training-progress');
% ________________________________________________________________
% Train the network
net = trainNetwork(reshapedData,nnTrainLabels',layers,options);
I am stuck here, as I have tried to follow what users have said in response to similar questions, but to no avail.
I appreciate any help on this and constructing the neural net in general :)
Thank you!

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回答（3 个）

Kiran Felix Robert
Kiran Felix Robert 2020-8-14
Hi Tanner,
The first two input argument of trainNetwork function - X and Y, are reshapedData and nnTrainLables’ respectively, in your program. According to the documentation of the trainNetwork function the dimension of X and Y are required to be,
X – 4-D – h-by-w-by-c-by-N
Y – 1-D – N-by-1
According to your reshaping method, the final dimensions are (as mentioned by you),
X – 4-D – 1-by-32373-by-1-by-60
Y – 1-D – 32373-by-1
Which gives you the error. This error can be resolved if you reshape the X (reshapedData) such that its fourth dimension contains N = 32373.
Hope this Helps.
Kiran Felix Robert
pathakunta
pathakunta 2024-1-26
The first two input argument of trainNetwork function - X and Y, are reshapedData and nnTrainLables’ respectively, in your program. According to the documentation of the trainNetwork function the dimension of X and Y are required to be, X – 4-D – h-by-w-by-c-by-N Y – 1-D – N-by-1 According to your reshaping method, the final dimensions are (as mentioned by you), X – 4-D – 1-by-32373-by-1-by-60 Y – 1-D – 32373-by-1 Which gives you the error. This error can be resolved if you reshape the X (reshapedData) such that its fourth dimension contains N = 32373.
pathakunta
pathakunta 2024-1-26
This is my first time building a neural net and am slowly working through the process. What I am trying to do: I have ~40,000 rows of data with 61 columns. Each row corresponds to a spectrum of a body's surface, and each column is an observation of that surface at a different wavelength. I am trying to make a neural net that can take each row in as an input (1 x 60 double) and tell me whether or not it falls into group 1 or group 2. The first column in the 40,000 x 61 array is the label 1 or 2. I have tried to follow https://www.mathworks.com/help/deeplearning/ug/create-simple-deep-learning-network-for-classification.html but it is not very useful for me since my data is not kept in an image datastore. I am also trying to make a 1-D cnn layer (though I am new to this and am not sure that is the best option for what I am trying to do). I have tried reshaping my data into a 4-D array such that >> whos nnTrainLabels Name Size Bytes Class Attributes nnTrainLabels 32373x1 32603 categorical >> whos reshapedData Name Size Bytes Class Attributes reshapedData 1x32373x1x60 15539040 double But I keep getting the error message Error using trainNetwork (line 170) Number of observations in X and Y disagree. Here is the code I am trying to run: height = 1; widthTrain = size(nnTrainSet,1); channels = 1; sampleSizeTrain = size(nnTrainSet,2); layers = [ imageInputLayer([height, widthTrain, channels]) % convolution2dLayer([3 1], widthTrain) % batchNormalizationLayer % reluLayer fullyConnectedLayer(2) softmaxLayer classificationLayer]; options = trainingOptions('sgdm', ... 'MaxEpochs', 200, ... 'Plots', 'training-progress'); % ______________________________________________________________ % Train the network net = trainNetwork(reshapedData,nnTrainLabels',layers,options); I am stuck here, as I have tried to follow what users have said in response to similar questions, but to no avail. I appreciate any help on this and constructing the neural net in general :) Thank you!

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