Abstract: A method may include obtaining a cluster. The cluster may include a subset of reference entities. The method may further include calculating distances between features of a target entity and features of the subset of reference entities, selecting, based on the distances, peer entities from the subset, and generating an estimated value of a metric. The generating may include applying, to the features of the target entity, a machine learning model trained using training data including values of the features for the peer entities labeled with a value of the metric. The method may further include presenting the estimated value of the metric.

Abstract: A method including training, using accepted data having known labels, an untrained prediction model to generate a trained prediction model. The method also includes generating, using the trained prediction model, predicted labels for unknown data. The method also includes generating, using a confidence model, confidence scores for the predicted labels. The method also includes selecting, using the confidence scores, a subset of the unknown data and confident labels. The confident labels include ones of the predicted labels for the subset of the unknown data. The method also includes training, using the subset of the unknown data and the confident labels, the trained prediction model to generate an updated prediction model.