Invention Grant
- Patent Title: Explaining machine learning based time series models
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Application No.: US17084955Application Date: 2020-10-30
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Publication No.: US12210939B2Publication Date: 2025-01-28
- Inventor: Manish Anand Bhide , Venkata R Madugundu , Pratap Kishore Varma Vemulamanda
- Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION
- Applicant Address: US NY Armonk
- Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
- Current Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
- Current Assignee Address: US NY Armonk
- Agency: Amin, Turocy & Watson, LLP
- Main IPC: G06N20/00
- IPC: G06N20/00 ; G06F16/22

Abstract:
A method, computer system, and computer program product for explaining time series machine learning model are provided. The embodiment may include determining a first order difference in time series input data and historical training data. The embodiment may also include performing perturbation of time series input data based on the determined first order difference and the determined historical training data. The embodiment may further include computing closeness of the determined first order difference in the historical training data to the determined first order difference in the time series input data. The embodiment may also include generating a uniform random sample of first value input to a time series machine learning model. The embodiment may further include determining values of other inputs to the time series machine learning model based on the generated random sample and a random sample from the historical training data first order differences.
Public/Granted literature
- US20220138614A1 EXPLAINING MACHINE LEARNING BASED TIME SERIES MODELS Public/Granted day:2022-05-05
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