I have some troubles to get sklearn’s cross_val_predict run for my ResNet18 (used for image classification). The scoring function is ‘accuracy’ and I get the error:
ValueError: Classification metrics can’t handle a mix of binary and continuous-multioutput targets.
My net returns the probabilities for each image to belong to one of my ten classes as float - I assume that the scoring is not working as the probabilites are floats… I also tried to use .round() but than I get the error: ValueError: Classification metrics can’t handle a mix of binary and multilabel-indicator targets, as often more than one class is set to one.
Can you help me to solve this problem? Thank you!