We can predict the class for new data instances using the Sequential classification model in Keras using the predict_classes() function. What is the way to predict the class for models that developed using the functional API?
For example, I have a model (functional API based) with sigmoid activation on the last layer to get probabilities in a multi-label classification. When I apply model.predict(), I got a series of probabilities even though the loss is binary_crossentropy.
I understand that I can do this classification manually e.g. following approach.
test_predict_proba = model.predict(x_test, batch_size=batch_size) class_predict = (test_predicted_proba > 0.5).astype(int)
I am wondering is there any standard procedure to do the same?