Ul LLC

Jiyuan Kang

Anthony Tassone

Christopher Hauman

Systems and methods for using machine learning models to predict an outcome of a product test are described. According to certain aspects, an electronic device may calculate, based on a received set of small-scale results as a first input to a first machine learning model of a plurality of machine learning models, a first result predicting an outcome of the product tested according to the large-scale product test. The electronic device may then calculate, based on the set of small-scale results as a second input to at least one second machine learning model of the plurality of machine learning models, a second result predicting the outcome of the product tested according to the large-scale product test. The electronic device may then predict an outcome of the large-scale product test based at least on the first result and the second result.

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Highland Park, IL, United States of America

Jiyuan Kang