Coupa Software. has been granted a patent for a method that enables configurable machine learning systems via graphical user interfaces. The system allows users to select neural network types and parameters, process input datasets, and compute output datasets, including confidence score evaluations for data items. GlobalData’s report on Coupa Software gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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According to GlobalData’s company profile on Coupa Software, was a key innovation area identified from patents. Coupa Software's grant share as of July 2024 was 62%. Grant share is based on the ratio of number of grants to total number of patents.
Configurable machine learning systems via graphical user interfaces
The granted patent US12039177B2 outlines a computer-implemented method for configuring and training machine learning systems using a graphical user interface (GUI). The method involves storing multiple machine learning configuration files, each containing instructions for different types of machine learning systems. Users can select from various neural network types and parameters through the GUI, which allows for the customization of machine learning systems based on specific input datasets. The process includes training the configured systems with distinct training datasets and computing output datasets, which are evaluated against a confidence score threshold. If any output data items fall below this threshold, the method allows for the generation of a second output dataset to replace the less confident items.
Additionally, the patent describes the capability to manage multiple machine learning training datasets, including categorization for better selection based on input data characteristics. The system can automatically select appropriate training datasets based on identified categories, enhancing the training process's efficiency. The method also includes provisions for testing various configurations to determine the most accurate machine learning system, which can then be stored for future use. Overall, the patent presents a comprehensive framework for the dynamic configuration, training, and evaluation of machine learning systems, emphasizing user interaction and adaptability in machine learning applications.
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