DataRobot has been granted a patent for a predictive modeling method that involves fitting a first-order predictive model to predict output variables based on input variables, followed by a second-order modeling procedure. This method includes generating input data, training data, and testing data to improve predictive accuracy. GlobalData’s report on DataRobot gives a 360-degree view of the company including its patenting strategy. Buy the report here.

According to GlobalData’s company profile on DataRobot, Predictive modeling techniques was a key innovation area identified from patents. DataRobot's grant share as of April 2024 was 38%. Grant share is based on the ratio of number of grants to total number of patents.

Predictive modeling method with first and second-order models

Source: United States Patent and Trademark Office (USPTO). Credit: DataRobot Inc

A recently granted patent (Publication Number: US11922329B2) outlines a predictive modeling method that involves obtaining a first-order predictive model to predict output variables based on input variables and then conducting a second-order predictive modeling procedure on this model. The second-order procedure includes generating second-order input data, creating training and testing data, fitting a second-order predictive model, and testing its performance. The method also allows for blending predictive models, using different types of second-order predictive models such as RuleFit or generalized additive models, and performing cross-validation to enhance accuracy.

Furthermore, the patent describes a predictive modeling apparatus that stores a machine-executable module for executing the second-order predictive modeling procedure on a first-order predictive model. The apparatus includes tasks for pre-processing and model-fitting, generating input data, training and testing data, fitting a second-order predictive model, and testing its performance. The apparatus is designed to determine the computational efficiency of the second-order model compared to the first-order model, based on resource utilization measurements. Additionally, the apparatus can handle time-series models, blend predictive models, assess accuracy scores, and deploy the most accurate second-order model. The patent also covers an article of manufacture with computer-readable instructions for implementing the predictive modeling method.

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GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.