Google patents method to fine-tune ad predictions for better accuracy
Google describes a system that adjusts the output of a machine learning model used to decide which digital content, such as ads, to show users. It creates a specific dataset to set new thresholds that turn raw prediction scores into final decisions, ensuring the model's guesses are more reliable before content is sent to devices.
In the filing’s own words
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for distributing digital components to client devices. The system receives a calibration request for calibrating a machine learning model, generates, according to the request, a calibration dataset. The system performs one or more calibration processes to generate one or more calibration thresholds using the calibration dataset, and applies the one or more calibration thresholds to the prediction scores generated by the machine learning model to generate calibrated prediction data including one or more predicted classifications. The system distributes the digital components to the client devices using calibrated prediction data.
What exactly they claim (claim 1)
1. A computer-implemented method, comprising: receiving a calibration request for calibrating a machine learning model, wherein the machine learning model has been trained on training data and is configured to process an input to generate prediction data for distributing digital components to client devices, the prediction data comprising one or more prediction scores; generating, according to the request, a calibration dataset; performing one or more calibration processes to generate one or more calibration thresholds using the calibration dataset; applying the one or more calibration thresholds to the prediction scores generated by the machine learning model to generate calibrated prediction data comprising one or more predicted classifications; and distributing the digital components to the client devices using calibrated prediction data.
Facts
- Company
- Google (Google LLC)
- Official title
- PREDICTION DATA CALIBRATION FOR CONTENT DISTRIBUTION
- Publication number
- US20260320429A1
- Application number
- 18859134
- Filed
- Sep 17, 2024
- Published
- Oct 15, 2026
- Inventors
- 4
- Claims
- 33
Classified under
G06N 5/04 Physics & computingMore from Google in AI & software
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Summaries are simplified from the filing’s own abstract and first claim. A patent filing is not a product announcement.
Patent data and drawings: U.S. Patent and Trademark Office (USPTO). Nebula is not affiliated with or endorsed by the USPTO.