Intuit Inc.
MINIMIZING REGRET THROUGH ACTIVE LEARNING FOR TRANSACTION CATEGORIZATION

Abstract:

Aspects of the present disclosure provide techniques for training a machine learning model. Embodiments include determining a set of unlabeled user transaction records associated with a user. Embodiments include selecting a first unlabeled user transaction record associated with a first vendor from the set of unlabeled user transaction records based on a transaction record prioritization scheme. Embodiments include presenting the first unlabeled user transaction record to the user in a label query. Embodiments include receiving, from the user in response to the label query, a label of a first account for the first unlabeled user transaction record. Embodiments include selecting a second unlabeled user transaction record associated with a second vendor from the set of unlabeled user transaction records based on: the transaction record prioritization scheme; and a determination that the second vendor is least likely to be categorized by the user in the first account.