Deep Learning, Machine Learning, Python, TensorFlow, Artificial Intelligence.
(1–0.1)+(0.1/2)= 0.95 Similarly, if the true label is 0, the modified label will be epsilon/n_classes. 0.1/2 = 0.05 The purpose of this smoothing is to avoid the model from becoming overconfident about its predictions. It encourages the model to be more uncertain and distribute some probability