Deep Learning, Evaluation Metric, Loss Function, Data Science, Model Evaluation.
when we have fewer number of classes One hot encoding is used for classes here Cons Slower in operation Not suitable when the number of classes is huge (due to one hot encodings used in target column) — leads to sparse features For a huge number of classes involved, we make use of Categorical Cross