Precision DropNone

Precision DropNone is a setting used in machine learning models that focus on identifying relevant items accurately. When set to "DropNone," the model is instructed not to exclude any predictions, meaning it considers every possible match without filtering out uncertain or less confident ones. This ensures the model maintains a broad scope, capturing all potential relevant results, which can be useful in scenarios where missing any relevant item is more detrimental than including some irrelevant ones. Essentially, it prioritizes thoroughness over precision by avoiding the dropping or ignoring of uncertain predictions.