Invention Grant
- Patent Title: Method and system for adaptively removing outliers from data used in training of predictive models
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Application No.: US15707454Application Date: 2017-09-18
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Publication No.: US11308049B2Publication Date: 2022-04-19
- Inventor: Yaser I. Suleiman , Michael Zoll , Subhransu Basu , Angelo Pruscino , Wolfgang Lohwasser , Wataru Miyoshi , Thomas Breidt , Thomas Herter , Klaus Thielen , Sahil Kumar
- Applicant: Oracle International Corporation
- Applicant Address: US CA Redwood Shores
- Assignee: Oracle International Corporation
- Current Assignee: Oracle International Corporation
- Current Assignee Address: US CA Redwood Shores
- Agency: Vista IP Law Group, LLP
- Main IPC: G06F16/21
- IPC: G06F16/21 ; G06F16/215 ; G06K9/62 ; G06F11/34 ; G06N20/20 ; H04L41/142 ; G06N7/00 ; H04L41/069 ; G06N20/00 ; H04L41/0695 ; H04L41/0823 ; H04L43/02
Abstract:
Described is an improved approach to remove data outliers by filtering out data correlated to detrimental events within a system. One or more detrimental even conditions are defined to identify and handle abnormal transient states from collected data for a monitored system.
Public/Granted literature
- US20180081913A1 METHOD AND SYSTEM FOR ADAPTIVELY REMOVING OUTLIERS FROM DATA USED IN TRAINING OF PREDICTIVE MODELS Public/Granted day:2018-03-22
Information query
