Invention Grant
- Patent Title: Soft segmentation based rules optimization for zero detection loss false positive reduction
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Application No.: US16395112Application Date: 2019-04-25
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Publication No.: US11694292B2Publication Date: 2023-07-04
- Inventor: Scott Michael Zoldi , Qing Lin
- Applicant: FAIR ISAAC CORPORATION
- Applicant Address: US MN Roseville
- Assignee: FAIR ISAAC CORPORATION
- Current Assignee: FAIR ISAAC CORPORATION
- Current Assignee Address: US MN Roseville
- Agency: Mintz Levin Cohn Ferris Glovsky and Popeo, P.C.
- Main IPC: G06Q50/26
- IPC: G06Q50/26 ; G06Q40/00 ; G06F40/30 ; G06Q40/12

Abstract:
A system and method includes soft-segment based rules optimization that can mitigate the overall false positives while maintaining 100% true positive detection. The soft clustering allows real-time re-assignment of an account to a dominate archetype behavior, as well as rule optimization based on a logical order with more relaxation on thresholds for the most inefficient rules is performed within each archetype. The rule optimization provides false positive reduction compared to a baseline rule system. The method can be used to reduce false positives for any rule-based detection system in which the same true positive detection is required.
Public/Granted literature
- US20200342556A1 SOFT SEGMENTATION BASED RULES OPTIMIZATION FOR ZERO DETECTION LOSS FALSE POSITIVE REDUCTION Public/Granted day:2020-10-29
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