Calculation of R2 and Mean Square Error for multiple response outputsDeep Learning: Feed Forward for Unbalanced Classes Using Tensor FlowLearning rate and memory of Least Mean Square algorithmAn Artificial Neuron Network (ANN) with an arbitrary number of inputs and outputsEncog neural network multiple outputsIn a convolutional neural network (CNN), when convolving the image, is the operation used the dot product or the sum of element-wise multiplication?Class leaking on validation setDeep advantage learning: how to predict the valuehow to optimize the weights of a neural net when feeding it with multiple training samples?Wrangling data for CNNKeras NN - Learning a simple formula
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Calculation of R2 and Mean Square Error for multiple response outputs
Deep Learning: Feed Forward for Unbalanced Classes Using Tensor FlowLearning rate and memory of Least Mean Square algorithmAn Artificial Neuron Network (ANN) with an arbitrary number of inputs and outputsEncog neural network multiple outputsIn a convolutional neural network (CNN), when convolving the image, is the operation used the dot product or the sum of element-wise multiplication?Class leaking on validation setDeep advantage learning: how to predict the valuehow to optimize the weights of a neural net when feeding it with multiple training samples?Wrangling data for CNNKeras NN - Learning a simple formula
$begingroup$
My neural network model is 20 inputs and 3 outputs for a regression problem. I am learning how to report the performance or the goodness of fit. http://www.wardsystems.com/manuals/neuroshell2/index.html?rsquared.htm link shows the formula for R2 test. My prediction is a matrix of N by 3
where N
is the number of elements.
Question 1) Would R2 be a matrix of 3 by 3 size or a scalar?
Question 2) Calculation of Error_Percentage = (abs(Errors)./Test_Y) * 100;
where Errors
is also 3 by N. Then would the Mean Absolute Error (MAE) be a scalar given by the formula
MAE = mean(abs(Error_Percentage))
neural-network prediction
New contributor
$endgroup$
add a comment |
$begingroup$
My neural network model is 20 inputs and 3 outputs for a regression problem. I am learning how to report the performance or the goodness of fit. http://www.wardsystems.com/manuals/neuroshell2/index.html?rsquared.htm link shows the formula for R2 test. My prediction is a matrix of N by 3
where N
is the number of elements.
Question 1) Would R2 be a matrix of 3 by 3 size or a scalar?
Question 2) Calculation of Error_Percentage = (abs(Errors)./Test_Y) * 100;
where Errors
is also 3 by N. Then would the Mean Absolute Error (MAE) be a scalar given by the formula
MAE = mean(abs(Error_Percentage))
neural-network prediction
New contributor
$endgroup$
add a comment |
$begingroup$
My neural network model is 20 inputs and 3 outputs for a regression problem. I am learning how to report the performance or the goodness of fit. http://www.wardsystems.com/manuals/neuroshell2/index.html?rsquared.htm link shows the formula for R2 test. My prediction is a matrix of N by 3
where N
is the number of elements.
Question 1) Would R2 be a matrix of 3 by 3 size or a scalar?
Question 2) Calculation of Error_Percentage = (abs(Errors)./Test_Y) * 100;
where Errors
is also 3 by N. Then would the Mean Absolute Error (MAE) be a scalar given by the formula
MAE = mean(abs(Error_Percentage))
neural-network prediction
New contributor
$endgroup$
My neural network model is 20 inputs and 3 outputs for a regression problem. I am learning how to report the performance or the goodness of fit. http://www.wardsystems.com/manuals/neuroshell2/index.html?rsquared.htm link shows the formula for R2 test. My prediction is a matrix of N by 3
where N
is the number of elements.
Question 1) Would R2 be a matrix of 3 by 3 size or a scalar?
Question 2) Calculation of Error_Percentage = (abs(Errors)./Test_Y) * 100;
where Errors
is also 3 by N. Then would the Mean Absolute Error (MAE) be a scalar given by the formula
MAE = mean(abs(Error_Percentage))
neural-network prediction
neural-network prediction
New contributor
New contributor
New contributor
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