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Originally posted by Qlexio December 30, 2023
I have been facing poor results while using scikit-learn accuracy whereas tensorflow's evaluation was good.
Here is the initial code:
# unbatch test_data and extract labels
y_labels = []
for image, label in test_data.unbatch():
y_labels.append(label.numpy().argmax())
y_labels[:10]
It returns a serie of 0s.
Fix
label variable is a unique integer. So, argmax of an integer always returns 0.
To fix this, drop the .argmax() fonction.
The text was updated successfully, but these errors were encountered:
Discussed in #620
Originally posted by Qlexio December 30, 2023
I have been facing poor results while using scikit-learn accuracy whereas tensorflow's evaluation was good.
Here is the initial code:
It returns a serie of 0s.
Fix
label variable is a unique integer. So, argmax of an integer always returns 0.
To fix this, drop the
.argmax()
fonction.The text was updated successfully, but these errors were encountered: