Microsoft Technology Licensing, LLC

Omari Carter-thorpe

Igor B Peev

Stephen C Rowe

Steven Marcel Elza Wilssens

Xiaoyu Chai

Connie Qin Yang

Alexander S Weil

Soheil Sadeghi

Tomas Aleksas Mereckis

Eamon Guthrie Cosgrove Millman

Disclosed herein is a system for leveraging telemetry data representing usage of a component installed on a group of sampled computing devices to confidently infer the quality of a user experience and/or the behavior of the component (e.g., an operating system) on a larger group of unsampled computing devices. The system is configured to use a propensity score matching approach to identify a sampled computing device that best represents an unsampled computing device using configuration data that is collected from both the sampled and unsampled computing devices. The quality of the user experience and/or the behavior of the component may be captured by a metric of interest (e.g., a QoS value). Accordingly, the system is configured to use the known metric of interest, determined from the telemetry data collected for the sampled computing device, to determine or predict the metric of interest for the unsampled computing device.

Using propensity score matching to determine metric of interest for unsampled computing devices

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Seattle, WA, United States of America

Omari Carter-thorpe