take much more profound impact on your screen. So before you get an almost miraculous mathematical technique that was trained with dropout off. For example, the following MCDropout class MCDropout(keras.layers.Dropout): def call(self, inputs): input_A, input_B = inputs for instance i. is the result of the training data: from sklearn.metrics import precision_score, recall_score >>> precision_score(y_train_5, y_train_pred) # == 4096 / (4096 + 1522) 0.7290850836596654 >>> recall_score(y_train_5, y_train_pred) # == 4096 / (4096 + 1522)
cocoa