A positive and unlabeled learning (PUL) problem occurs when a machine learning set of training data has only a few positive labeled items and many unlabeled items. PUL problems often occur with ...

Our understanding of progress in machine learning has been colored by flawed testing data. The 10 most cited AI data sets are riddled with label errors, according to a new study out of MIT, and it’s ...