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At line 125 in utils.py, inside the _normalized() function, it seems that a normalization of the whole dataset is performed for both the train, valid, and test sets.
# normalized by the maximum value of each row(sensor).ifnormalize==2:
foriinrange(self.m):
self.scale[i] =np.max(np.abs(self.raw_data[:, i])) # <- This lineself.dat[:, i] =self.raw_data[:, i] /np.max(np.abs(self.raw_data[:, i]))
I think it is not proper to use the information in the test data for training.
The text was updated successfully, but these errors were encountered:
Hello Prof. LAI,
At line 125 in
utils.py
, inside the_normalized()
function, it seems that a normalization of the whole dataset is performed for both the train, valid, and test sets.I think it is not proper to use the information in the test data for training.
The text was updated successfully, but these errors were encountered: