1 year ago
#339474
ForestGump
How can I define custom geometric mean evaluation metrics in tensorflow 2.0?
How can implement the following imblearn geometric mean in Tensorflow to compile LSTM model?
from imblearn.metrics import geometric_mean_score
gmean = geometric_mean_score(yTest,yPred)
I wanted to use the following option, but it is not working like metrics=[keras.metrics.AUC(name='auc')]
from keras import backend
def gmean(y_true, y_pred):
return backend.geometric_mean_score(yTest,yPred)
I tried this Available StackOverflow suggestions , but it didn't work as well.
keras
tensorflow2.0
tf.keras
imblearn
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