ITERATIVE MACHINE LEARNING BASED TECHNIQUES FOR VALUE-BASED DEFECT ANALYSIS IN LARGE DATA SETS

One or more defect analysis iterations are performed on a collection of records. In a given iteration, a defect presence probability is obtained using a machine learning model for a record group. An estimated audit benefit is then assigned to the record group based at least partly on a defect remediation importance score of the record group. An indication of the estimated audit benefit of the record group is provided to an auditor. An audited defect status for the record group, generated by the auditor, is used to initiate one or more automated actions.