Unable to save session in Classification Learner

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I have trained models in classification learner based on a dataset and am hoping to save the classificationLearner Session so that I do not have to rerun all the models again everytime, which takes quite a long time. I am currently using the R2022a version, and when I try to save the error, I get an error message that says "The file could not be closed, and might now be corrupt." Any advice on how I can get rid of this error and save the session?
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Walter Roberson
Walter Roberson il 22 Lug 2022
Is it possible that you ran out of disk space?
Sonia Tan
Sonia Tan il 22 Lug 2022
The device that I tried it on had >100GB of space so I think there was still sufficient disk space for storage?

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Image Analyst
Image Analyst il 23 Lug 2022
What do you mean by "rerun the models"? Why do you have to do that? Did your training data change? If not, why rerun?
What I do is to load by predictor table and ground truth responses and train the model. Then I click the Export->Compact Model to put the "trainedModel" variable into the workspace. Then I call save
save('myModel.mat', 'trainedModel');
to save the trained model to disk. Then to apply the model to predict (not train) new estimated response values, I call load
s = load('myModel.mat');
trainedModel = s.trainedModel;
then call predict() with a table of new data and the trainedModel variable. That will give me an estimated value for each new test value.
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Antonio
Antonio il 19 Gen 2024
In my case, this problem is related to MATLAB having problems saving files larger than 2GB in the default configuration of the "save" function. You can try two options:
  • Export the model as a Compact Model (Export -> Export Compact Model) to the workspace and save from there as normally done with save(). If that compact model meets the 2GB limit, you will have no problem.
  • Otherwise, export the complete or compact model from the workspace using the option '-v7.3' inside the save() function. It was this option that solved the problem in my case.
save(filename, 'modelTrained', '-v7.3')
I hope to be helpful! Sorry I'm late, but I respond for others who have the same problem.

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R2022a

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