calculate training coeffecient of determination r^2 and mean absolute error

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Hi everyone,I hope this message finds you well. I am currently working on a prediction task using LSTM, and I have successfully obtained the training RMSE using info in following codde
[net info] = trainNetwork(xtrain, ytrain, layers, options);
i have also obtained testing metrics using their formulas
Y = predict(net, xtest);
e = (ytest - Y);
rmse = mean(sqrt(mean((Y - ytest).^2)));
mae1 = mae(e);
Rsq1 = 1 - sum((ytest - Y).^2) / sum((ytest - mean(ytest)).^2);
mse = mean(mean((ytest - Y).^2));
However, I am curious to know if there is a straightforward way to retrieve additional training metrics such as R² and MAE for the LSTM model. Your insights and guidance on this matter would be greatly appreciated.
Thank you in advance for your time and assistance.

Accepted Answer

Debraj Maji
Debraj Maji on 25 Dec 2023
Hi @Mahi,
I understand that you are trying to retrieve additional training metrics for the aforementioned LSTM Model. As of 2023b the available metrics for tracking are:
  • AccuracyMetric
  • AUCMetric
  • FScoreMetric
  • PrecisionMetric
  • RecallMetric
  • RMSEMetric
One of the ways to track R-squared and MAE during training is by creating a custom Deep Learning Metric Object and specifying it in 'trainingOptions' under Metrics argument. The steps to create a Deep Learning Metric Object can be found here:
For more info on options available during training you can refer to the following documentation:
I hope this resolves your query.
With regards,

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