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

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Mahi
Mahi 2023-12-24
评论： Mahi 2023-12-25
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.

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Debraj Maji
Debraj Maji 2023-12-25
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: https://in.mathworks.com/help/deeplearning/ug/define-custom-deep-learning-metric.html
For more info on options available during training you can refer to the following documentation:
https://in.mathworks.com/help/deeplearning/ref/trainingoptions.html
I hope this resolves your query.
With regards,
Debraj.

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