one
VARIABLE MATCHING CRITERIA DEFINING TRAINING LABELS FOR SUPERVISED RECURRENCE DETECTION

Abstract:

Provided herein are a method, a system, and a computer program product embodiments, and/or combinations and sub-combinations thereof, for dynamically detecting recurring transactions using tunable labels to train different transaction models that provide separate analysis of transaction sets. The recurrence detection of transactional data is based on labels that can be tuned to define different definitions of recurrence. Each definition of recurrence may be used to train a model which results in different trained models to suit the different tuned labels.