Stitch Fix. has filed a patent for a method to optimize computer machine learning by selecting base options matching an optimization goal from a database, determining prediction values for alternative features, and generating an ordered list for manufacturing alternative versions. Claim 1 has been canceled. GlobalData’s report on Stitch Fix 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 Stitch Fix, AI assisted CAD was a key innovation area identified from patents. Stitch Fix's grant share as of January 2024 was 49%. Grant share is based on the ratio of number of grants to total number of patents.

Optimizing computer machine learning for personalized clothing recommendations

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

The patent application (Publication Number: US20230385689A1) describes a method for optimizing computer machine learning by determining components of an optimization goal, selecting eligible base options based on the goal, evaluating these options using a trained model, identifying candidate base options, selecting trained models to evaluate alternative features, and providing an ordered list for manufacturing an alternative version of the candidate base options. The components of the optimization goal can be associated with various metrics such as sales, inventory, variety, style, size, fit, quality, retention, personalization, style grouping, or price value. The target segments for optimization can include business lines, product types, client segments, or seasonality.

The method involves ranking eligible base options based on corresponding score indicators for each component of the optimization goal and selecting candidate base options with scores above a threshold. The system described in the patent includes a processor and memory to carry out these operations, while a computer program product provides instructions for implementing the optimization process. By evaluating alternative features for candidate base options and combining prediction results from trained models, the method aims to enhance the performance and customization of machine learning models for various applications. This approach can lead to more efficient decision-making processes and improved outcomes in manufacturing and other industries where optimization is crucial for success.

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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.