Abstract: In general, embodiments of the present invention provide systems, methods and computer readable media for curating a training data set to ensure that training data being updated continuously from a data reservoir of verified possible training examples remain an accurate, high-quality representation of the distribution of data that are being input to a predictive model for processing.

Abstract: In general, embodiments of the present invention provide systems, methods and computer readable media for an adaptive oracle-trained learning framework for automatically building and maintaining models that are developed using machine learning algorithms. In embodiments, the framework leverages at least one oracle (e.g., a crowd) for automatic generation of high-quality training data to use in deriving a model. Once a model is trained, the framework monitors the performance of the model and, in embodiments, leverages active learning and the oracle to generate feedback about the changing data for modifying training data sets while maintaining data quality to enable incremental adaptation of the model.

Abstract: Systems, apparatus, and methods for determining unique contacts from a collection or pool of merchant data are discussed herein. Some embodiments may provide for an apparatus including circuitry configured to determine programmatic match results indicating whether different instances of merchant data match (e.g., describe the same contact). The circuitry may further determine probabilities of precision or recall errors with the programmatic match results. Programmatic match results having a high probability of error may be annotated by a user to generate user match results. The user match results may be used to generate a more reliable contacts database including unique contacts, as well as to train and/or update the match scoring algorithm. As such, the accuracy of machine-implemented binary classification is improved.

Abstract: In general, embodiments of the present invention provide systems, methods and computer readable media for curating a training data set to ensure that training data being updated continuously from a data reservoir of verified possible training examples remain an accurate, high-quality representation of the distribution of data that are being input to a predictive model for processing.