Techniques for prediction models using time series data
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United States of America Patent
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Feb 6, 2024
Grant Date -
Oct 6, 2022
app pub date -
Mar 31, 2021
filing date -
Mar 31, 2021
priority date (Note) -
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Abstract
Various aspects involve a lagged prediction model trained for risk assessment or other purposes. For instance, a risk assessment computing system receives a risk assessment query for a target entity and provides an input predictor record for the target entity to a lagged prediction model. The input predictor record includes a first group of lagged values from a first time-series attribute associated with the target entity. The lagged prediction model is trained by implementing a group feature selection technique configured to select the first time-series attribute as input and to deselect a second time-series attribute associated with the target entity. The risk assessment computing system computes an output risk indicator from the input predictor record and transmits the output risk indicator to a remote computing system. The output risk indicator can be used to control access by the target entity to one or more interactive computing environments.
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