公开(公告)号：US10915602B2

公开(公告)日：2021-02-09

申请号：US15553278

申请日：2015-03-18

Applicant: ENTIT SOFTWARE LLC

Inventor： Lakshmi Nagarajan

IPC: G06F17/00 ,  G06F17/18 ,  G06N3/08

Abstract: Automatic detection of outliers in multivariate data is disclosed. One example is a system including a distance generator to determine Mahalanobis distances for data elements of multivariate input data, the Mahalanobis distance of a given data element indicative of a measure of distance of the given data element from a probability distribution associated with the input data. A filter module selects a portion of the input data, the cohesive portion indicative of cohesive data elements, and the selection based on minimizing the Mahalanobis distances, and identifies candidate outliers to be data elements not in the cohesive portion. An outlier detector automatically detects outliers of the candidate outliers, the detection based on median absolute deviations of the Mahalanobis distances of the input data, and a modified z-score. A display module generates a visual representation of the detected outliers.

公开(公告)号：US10909540B2

公开(公告)日：2021-02-02

申请号：US15545826

申请日：2015-02-24

Applicant: ENTIT SOFTWARE LLC

Inventor： Han Ju ,  Lakshmi Nagarajan ,  Shi Xing Yan

IPC: G06Q20/40 ,  G06Q40/02 ,  G06N5/04 ,  G06N7/00

Abstract: A method includes receiving an alert representing that application of at least one rule to a scenario occurring with a financial account indicates that the scenario is consistent with illegal activity. The method includes, in response to the alert, using a fuzzy inference derived from activity of the financial account to determine a likelihood that the scenario is associated with illegal activity.