DataRobot had one patents in big data during Q2 2024. DataRobot Inc’s patent filed in Q2 2024 focuses on identifying, visualizing, and mitigating bias in machine learning models. The system receives features used by the model, evaluates model performance metrics, compares output values for different categories, and generates notifications based on predefined thresholds for these metrics. GlobalData’s report on DataRobot gives a 360-degree view of the company including its patenting strategy. Buy the report here.

DataRobot had no grants in big data as a theme in Q2 2024.

Recent Patents

Application: Methods and systems for identification and visualization of bias and fairness for machine learning models (Patent ID: US20240193481A1)

The patent filed by DataRobot Inc. focuses on identifying, visualizing, and mitigating machine learning model bias. The system receives features used by a model, identifies a metric and threshold for evaluating model performance, determines metric values for different feature categories, and generates notifications based on these values. The method includes mitigating the model based on user requests, retraining the model, or adjusting weight values. The system can compare models, present graphical indicators for features, and provide information on impact or disparity values associated with features.

The patent also describes a computer system that implements these methods, with processors configured to receive features, identify metrics, determine values, and generate notifications based on model performance. The system can mitigate models, compare them with others, and present information visually. The computer system can also determine eligibility of features for value determination and adjust models based on user requests. This patent aims to provide a comprehensive solution for addressing bias in machine learning models through systematic evaluation and visualization of model performance metrics.

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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.