R Deep Learning Cookbook

Defining the cost function used for optimization

The cost function is primarily used to evaluate the current performance of the model by comparing the true class labels (y_true_cls) with the predicted class labels (y_pred_cls). Based on the current performance, the optimizer then fine-tunes the network parameters, such as weights and biases, to further improve its performance.