Invention Grant
- Patent Title: Predictive modeling across multiple horizons combining time series and external data
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Application No.: US15178445Application Date: 2016-06-09
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Publication No.: US10671931B2Publication Date: 2020-06-02
- Inventor: Gagan Bansal , Amita Surendra Gajewar , Debraj GuhaThakurta , Konstantin Golyaev , Mayank Shrivastava , Vijay Krishna Narayanan , Walter Sun
- Applicant: Microsoft Technology Licensing, LLC
- Applicant Address: US WA Redmond
- Assignee: MICROSOFT TECHNOLOGY LICENSING, LLC
- Current Assignee: MICROSOFT TECHNOLOGY LICENSING, LLC
- Current Assignee Address: US WA Redmond
- Agency: Workman Nydeggar
- Main IPC: G06N5/04
- IPC: G06N5/04 ; G06N20/00 ; G06Q10/10 ; G06Q50/10 ; G06Q10/04

Abstract:
A multi-horizon predictor system that predicts a future parameter value for multiple horizons based on time-series data of the parameter, external data, and machine-learning. For a given time horizon, a time series data splitter splits the time into training data corresponding to a training time period, and a validation time period corresponding to a validation time period between the training time period and the given horizon. A model tuner tunes the prediction model of the given horizon fitting an initial prediction model to the parameter using the training data thereby using machine learning. The model tuner also tunes the initial prediction model by adjusting an effect of the external data on the prediction to generate a final prediction model for the given horizon using the validation data. A multi-horizon predictor causes the time series data splitter and the model tuner to operate for each of multiple horizons.
Public/Granted literature
- US20170220939A1 PREDICTIVE MODELING ACROSS MULTIPLE HORIZONS COMBINING TIME SERIES & EXTERNAL DATA Public/Granted day:2017-08-03
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