When using a model to score a dataset, which three of the following options can be computed for the scored dataset?

The individual explanations $($ie the most important features$)$ for each prediction.

The output prediction value.

The probability associated with each class, for a classification task.

The ML model and hyperparameters that have been used for this prediction.