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US Patent 10984367 Systems and techniques for predictive data analytics

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Patent abstractTimelineTable: Further ResourcesReferences
Is a
Patent
Patent
1

Patent attributes

Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
1
Patent Number
109843671
Patent Inventor Names
Timothy Owen1
Jeremy Achin1
Thomas DeGodoy1
Xavier Conort1
Date of Patent
April 20, 2021
1
Patent Application Number
155879511
Date Filed
May 5, 2017
1
Patent Citations
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US Patent 10366335 Systems and methods for symbolic analysis
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US Patent 10366346 Systems and techniques for determining the predictive value of a feature
1
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US Patent 10387900 Methods and apparatus for self-adaptive time series forecasting engine
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US Patent 10318874 Selecting forecasting models for time series using state space representations
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US Patent 10558924 Systems for second-order predictive data analytics, and related methods and apparatus
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US Patent 10496927 Systems for time-series predictive data analytics, and related methods and apparatus
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US Patent 10102483 System and method for auto-query generation
1
Patent Citations Received
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US Patent 11922329 Systems for second-order predictive data analytics, and related methods and apparatus
10
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US Patent 11250449 Methods for self-adaptive time series forecasting, and related systems and apparatus
‌
US Patent 11373127 Connection multiplexing for a parallel processing environment
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US Patent 11551156 Systems and methods for forecast alerts with programmable human-machine hybrid ensemble learning
Patent Primary Examiner
‌
Luis A Sitiriche
1
Patent abstract

Systems and techniques for predictive data analytics are described. In a method for selecting a predictive model for a prediction problem, the suitabilities of predictive modeling procedures for the prediction problem may be determined based on characteristics of the prediction problem and/or on attributes of the respective modeling procedures. A subset of the predictive modeling procedures may be selected based on the determined suitabilities of the selected modeling procedures for the prediction problem. A resource allocation schedule allocating computational resources for execution of the selected modeling procedures may be generated, based on the determined suitabilities of the selected modeling procedures for the prediction problem. Results of the execution of the selected modeling procedures in accordance with the resource allocation schedule may be obtained. A predictive model for the prediction problem may be selected based on those results.

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