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US Patent 11966340 Automated time series forecasting pipeline generation

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Is a
Patent
Patent
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Patent attributes

Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
0
Patent Number
119663400
Patent Inventor Names
Horst Cornelius Samulowitz0
Wesley M. Gifford0
Saket K. Sathe0
Dhavalkumar C. Patel0
Ji Hui Yang0
Dakuo Wang0
Jing James Xu0
Long Vu0
...
Date of Patent
April 23, 2024
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Patent Application Number
176549650
Date Filed
March 15, 2022
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Patent Citations
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US Patent 10713574 Cognitive distributed network
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US Patent 6928398 System and method for building a time series model
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US Patent 11494587 Systems and methods for optimizing performance of machine learning model generation
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US Patent 7124055 Time series analysis and forecasting program
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US Patent 10375098 Anomaly detection based on relationships between multiple time series
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US Patent 10671435 Data transformation caching in an artificial intelligence infrastructure
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Patent Primary Examiner
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Stephanie Wu
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Patent abstract

To automate time series forecasting machine learning pipeline generation, a data allocation size of time series data may be determined based on one or more characteristics of a time series data set. The time series data may be allocated for use by candidate machine learning pipelines based on the data allocation size. Features for the time series data may be determined and cached by the candidate machine learning pipelines. Predictions of each of the candidate machine learning pipelines using at least the one or more features may be evaluated. A ranked list of machine learning pipelines may be automatically generated from the candidate machine learning pipelines for time series forecasting based upon evaluating predictions of each of the one or more candidate machine learning pipelines.

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