Scoring is the process of applying new data to a trained model to produce predictions, probabilities, rankings, or categories. In recommendation systems, scoring may also mean assigning values to candidate items so they can be ranked for presentation.
Scoring is the process of applying new data to a trained machine learning model, and generating predictions. Scoring is also known as inferencing. Depending on the type of model, the score can be a raw value, a probability, or a category.
The part of a recommendation system that provides a value or ranking for each item produced by the candidate generation phase.