Anomaly detection using feedback training

Techniques for anomaly detection are described. An exemplary method includes receiving one or more requests to train an anomaly detection machine learning model using feedback-based training, the request to indicate one or more of a type of analysis to perform, a model selection indication, and a co...

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Bibliographic Details
Main Authors Brouwers, Niels, Patel, Anant, Krishnan, Prakash, Mcdowell, Shaun Ryan James, Mainthia, Anushri, Zepeda Salvatierra, Joaquin, Balasubramanian, Barath, Aghoram Ravichandran, Avinash, Nambiar, Rakesh Madhavan, Swaminathan, Gurumurthy, Das, Ranju, Bhotika, Rahul
Format Patent
LanguageEnglish
Published 14.05.2024
Subjects
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
ELECTRIC COMMUNICATION TECHNIQUE
ELECTRIC DIGITAL DATA PROCESSING
ELECTRICITY
PHYSICS
TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHICCOMMUNICATION
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Summary:Techniques for anomaly detection are described. An exemplary method includes receiving one or more requests to train an anomaly detection machine learning model using feedback-based training, the request to indicate one or more of a type of analysis to perform, a model selection indication, and a configuration for a training dataset; training the anomaly detection machine learning model according to the one or more requests using the training data; performing feedback-based training on the trained anomaly detection machine learning model; and using the retrained anomaly detection machine learning model.
Bibliography:Application Number: US202017106023