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Systems and techniques for predictive data analytics

  • US 9,652,714 B2
  • Filed: 07/22/2016
  • Issued: 05/16/2017
  • Est. Priority Date: 05/23/2014
  • Status: Active Grant
First Claim
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1. A predictive modeling apparatus comprising:

  • a memory configured to store a machine-executable module encoding a predictive modeling procedure, wherein the predictive modeling procedure includes a plurality of tasks, wherein the machine-executable module includes a directed graph representing dependencies between the tasks, and wherein the plurality of tasks includes at least one pre-processing task, at least one model-fitting task, and at least one post-processing task; and

    at least one processor configured to execute the machine-executable module, wherein executing the machine-executable module causes the apparatus to perform the predictive modeling procedure, including;

    manipulating input data, comprising performing the pre-processing task on the input data;

    performing the model-fitting task, comprising;

    generating, from the pre-processed input data, training data and testing data,fitting a predictive model to the training data, andtesting the fitted model on the testing data; and

    performing the post-processing task,wherein the pre-processed input data comprise at least one data set, wherein generating the training data comprises obtaining a first subset of the data set, and wherein generating the testing data comprises obtaining a second subset of the data set,wherein performing the predictive modeling procedure further includes performing cross-validation of the predictive model,wherein the training data are first training data, wherein the testing data are first testing data, wherein the fitted model is a first fitted model, and wherein performing the cross-validation of the predictive model comprises;

    (a) generating, from the data set, second training data and second testing data, wherein generating the second training data comprises obtaining a third subset of the data set, and wherein generating the second testing data comprises obtaining a fourth subset of the data set;

    (b) fitting the predictive model to the second training data to obtain a second fitted model; and

    (c) testing the second fitted model on the second testing data.

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