In the context of product innovation, there is an emerging trend to use Machine Learn ing (ML) models with the support of Design Of Experiments (DOE). The paper aims firstly to review the most suitable designs and ML models to use jointly in an Active Learning (AL) approach; it then reviews ALPERC, a novel AL approach, and proves the validity of this method through a case study on amorphous metallic alloys, where this algorithm is used in combination with a Random Forest model.
Design of experiments and machine learning with application to industrial experiments
Molena Alberto;Pegoraro Luca;Salmaso Luigi
2023
Abstract
In the context of product innovation, there is an emerging trend to use Machine Learn ing (ML) models with the support of Design Of Experiments (DOE). The paper aims firstly to review the most suitable designs and ML models to use jointly in an Active Learning (AL) approach; it then reviews ALPERC, a novel AL approach, and proves the validity of this method through a case study on amorphous metallic alloys, where this algorithm is used in combination with a Random Forest model.
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