Deep Learning Quick Reference

Measuring ROC AUC in a custom callback

Let's use one more callback. This time, we will build a custom callback that computes Receiver Operating Characteristic Area Under the Curve (ROC AUC) at the end of every epoch, on both training and testing sets.

Creating a custom callback in Keras is actually really simple. All we need to do is create a class, inherent Callback, and override the method we need. Since we want to calculate the ROC AUC score at the end of each epoch, we will override on _epoch_end:

from keras.callbacks import Callbackclass RocAUCScore(Callback):    def __init__(self, training_data, validation_data):        self.x = training_data[0]        self.y = training_data[1]        self.x_val = validation_data[0]        self.y_val = validation_data[1] super(RocAUCScore, ...