Loading patent…
AssigneeCapital One Services, LLC
InventorsPhanindra Rao, Peter Gaspare Terrana, Vannia Gonzalez Macias
Estimating the term…
Methods and systems are described herein for determining auxiliary parameters within datasets, the auxiliary parameters being used to segregate the datasets such that anomaly detection may be performed on the segregated datasets. Based on anomaly detection, alert conditions may then be identified. In particular, a system may, using a machine learning model, determine for a particular target feature (e.g., a parameter being monitored) one or more auxiliary features (other parameters) that effect the values of that parameter and transmit the target feature and the auxiliary features in a message to a monitoring system indicating which features to monitor. The collected data may then be received by the system and transformed into a timeseries dataset, which may then be used to detect anomalies within the data and thereby identify any anomalous points.
A system for determining monitoring parameters within datasets and detecting anomalies within the datasets transformed into timeseries data, the system comprising:
A method for determining monitoring parameters and detecting anomalies within generated timeseries datasets, the method comprising:
A non-transitory, computer-readable medium storing instructions that, when executed by one or more processors, cause the one or more processors to perform operations comprising:
Dependencies are inferred from the claim text.