PyEMD returning different number of IMFs for train, test data
You can decompose the data first, and then divide the training set and the test set for each component
I am using PyEMD (Empirical Mode Decomposition) on a signal (train & test ) data. All seems be working fine for all signals (datasets), but in my one of the dataset number of IMFs it is decomposing is different for train & test dataset.
I have tried (max_imf: ) argument, but by limiting the number to minimum value so that both (train & test ) have same number of IMF, the decomposition is not correct ( it is not decomposing till final trend).
Any suggest will be appreciated.