Deep Learning, Machine Learning, Python, TensorFlow, Artificial Intelligence.
smoothing factor (usually denoted as epsilon) is applied to the true labels. This means that a fraction of the loss is attributed to the complementary class. For example, if epsilon is equal to 0.1, the modified label will be (1-epsilon)+(epsilon/n_classes). So, the modified label becomes: