Sparse Categorical Cross-Entropy
In sparse categorical cross-entropy, truth labels are labeled with integral values. For example, if a 3-class problem is taken into consideration, the labels would be encoded as [1], [2], [3]. Note that binary cross-entropy cost functions, categorical cross-entropy, and sparse categorical cross-entropy are provided with the Keras API.
Cross-Entropy Cost Functions used in Classification
Cost functions play a crucial role in improving a Machine Learning model’s performance by being an integrated part of the gradient descent algorithm which helps us optimize the weights of a particular model. In this article, we will learn about one such cost function which is the cross-entropy function which is generally used for classification problems.