AUTOMATED TIME-SERIES PREDICTION PIPELINE SELECTION

Information

  • Patent Application
  • 20230297876
  • Publication Number
    20230297876
  • Date Filed
    March 17, 2022
    2 years ago
  • Date Published
    September 21, 2023
    a year ago
Abstract
Selecting a time-series forecasting pipeline by receiving target variable time-series data and exogenous variable time-series data, generating a regular forecasting pipeline comprising a model according to the target variable time-series data, generating an exogenous forecasting pipeline comprising a model according to the target variable time-series data and the exogenous variable time-series data, evaluating the regular forecasting pipeline and the exogenous forecasting pipeline, selecting a pipeline according to the evaluation, and providing the selected pipeline.
Description
Claims
  • 1. A computer implemented method for selecting a time-series forecasting pipeline, the method comprising: receiving, by one or more computer processors, target variable time-series data and exogenous variable time-series data;generating, by the one or more computer processors, a regular forecasting pipeline comprising a model according to the target variable time-series data;generating, by the one or more computer processors, an exogenous forecasting pipeline comprising a model according to the target variable time-series data and the exogenous variable time-series data;evaluating, by the one or more computer processors, the regular forecasting pipeline and the exogenous forecasting pipeline;selecting, by the one or more computer processors, a pipeline according to the evaluation; andproviding, by the one or more computer processors, the selected pipeline.
  • 2. The computer implemented method according to claim 1, further comprising: receiving, by the one or more computer processors, libraries for at least one of data imputation, data transformation, and pipeline generation; andgenerating, by the one or more computer processors, a pipeline according to the at least one of the data imputation, data transformation and pipeline generation library.
  • 3. The computer implemented method according to claim 1, further comprising providing, by the one or more computer processors, an explanation of forecast time-series data using information from at least one of the target variable time-series data and the exogenous variable time-series data.
  • 4. The computer implemented method according to claim 3, further comprising providing, by the one or more computer processors, an explanation of forecast time-series data according to past and future exogenous variable data.
  • 5. The computer implemented method according to claim 1, further comprising concurrently evaluating, by the one or more computer processors, the regular and exogenous pipelines under a common framework.
  • 6. The computer implemented method according to claim 1, further comprising imputing, by the one or more computer processors, missing data for at least one of the target variable time-series data and the exogenous variable time-series data.
  • 7. The computer implemented method according to claim 6, further comprising masking, by the one or more computer processors, the imputed data.
  • 8. A computer program product for selecting a time-series forecasting pipeline, the computer program product comprising one or more computer readable storage devices and collectively stored program instructions on the one or more computer readable storage devices, the stored program instructions comprising instructions, which when executed, cause a computing system to: receive target variable time-series data and exogenous variable time-series data;generate a regular forecasting pipeline comprising a model according to the target variable time-series data;generate an exogenous forecasting pipeline comprising a model according to the target variable time-series data and the exogenous variable time-series data;evaluate the regular forecasting pipeline and the exogenous forecasting pipeline;select a pipeline according to the evaluation; andprovide the selected pipeline.
  • 9. The computer program product according to claim 8, the stored program instructions further causing the computing system to: receive libraries for at least one of data imputation, data transformation, and pipeline generation; andgenerate a pipeline according to the at least one of the data imputation, data transformation and pipeline generation library.
  • 10. The computer program product according to claim 8, the stored program instructions further causing the computing system to provide an explanation of forecast time-series data using information from at least one of the target variable time-series data and the exogenous variable time-series data.
  • 11. The computer program product according to claim 10, the stored program instructions further causing the computing system to provide an explanation of forecast time-series data according to past and future exogenous variable data.
  • 12. The computer program product according to claim 8, the stored program instructions further causing the computing system to concurrently evaluate the regular and exogenous pipelines under a common framework.
  • 13. The computer program product according to claim 8, the stored program instructions further causing the computing system to impute missing data for at least one of the target variable time-series data and the exogenous variable time-series data.
  • 14. The computer program product according to claim 13, the stored program instructions further causing the computing system to mask the imputed data.
  • 15. A computer system for selecting a time-series forecasting pipeline, the computer system comprising: one or more computer processors;one or more computer readable storage devices; and stored program instructions on the one or more computer readable storage devices for execution by the one or more computer processors, the stored program instructions comprising instructions, which when executed, cause the computer system to: receive target variable time-series data and exogenous variable time-series data;generate a regular forecasting pipeline comprising a model according to the target variable time-series data;generate an exogenous forecasting pipeline comprising a model according to the target variable time-series data and the exogenous variable time-series data;evaluate the regular forecasting pipeline and the exogenous forecasting pipeline;select a pipeline according to the evaluation; andprovide the selected pipeline.
  • 16. The computer system according to claim 15, the stored program instructions further causing the computer system to: receive libraries for at least one of data imputation, data transformation, and pipeline generation; andgenerate a pipeline according to the at least one of the data imputation, data transformation and pipeline generation library.
  • 17. The computer system according to claim 15, the stored program instructions further causing the computer system to provide an explanation of forecast time-series data using information from at least one of the target variable time-series data and the exogenous variable time-series data.
  • 18. The computer system according to claim 17, the stored program instructions further causing the computer system to provide an explanation of forecast time-series data according to past and future exogenous variable data.
  • 19. The computer system according to claim 15, the stored program instructions further causing the computer system to concurrently evaluate the regular and exogenous pipelines under a common framework.
  • 20. The computer system according to claim 15, the stored program instructions further causing the computer system to impute missing data for at least one of the target variable time-series data and the exogenous variable time-series data.