Hi everyone
I am new to MATLAB and modelling. I have a LSTM deep learning model that I am experimenting with. I need some help in determining if the model is a good fit for my data. I am not sure where to start so I will start with validation RMSE. If there are other metrics to look at please let me know.
I have three versions of the model. There are close to 3000 data points used in the model. 80% is used for training. 20% is used for testing/validation.
Model 1 22 sec, validation RMSE = 0.35918
Model 2 34 sec, validation RMSE = 0.065824
Model 3 41 sec, validation RMSE = 0.50482
My elementary knowledge of modelling tells me that the lower the RMSE the better. So, if I use this approach then Model 2 is the winner. Is this enough? Should I be looking at other ways to assess quality of fit?
Here is some basic information about the data set:
Average 17.45502778
Min 8.8901784
Max 74.563979
Standard Deviation (Sample) 6.500568667
Standard Deviation (Population) 6.499343878
Thank you