首页|Research from Beijing University of Technology in the Area of Machine Learning D escribed (Analysis of the Outcome of the Driving Test for Learner Drivers Based on an Interpretable Machine Learning Framework)
Research from Beijing University of Technology in the Area of Machine Learning D escribed (Analysis of the Outcome of the Driving Test for Learner Drivers Based on an Interpretable Machine Learning Framework)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Investigators publish new report on ar tificial intelligence. According to news reporting from Beijing, People's Republ ic of China, by NewsRx journalists, research stated, "The driving test is the on ly way to verify that learner drivers have acquired the competencies stipulated in the national curriculum." Our news correspondents obtained a quote from the research from Beijing Universi ty of Technology: "Therefore, exploring the key factors that influence the outco me of the driving test is of particular importance in assisting learner drivers to gain solid behind-the-wheel skills. Interpretable machine learning (ML) is em ployed to analyze the probability of learner drivers' passing the driving skills test (called the Subject 2 test in China) using a data set comprising personal characteristics, training mode, frequency of driving errors, deducted points, pe rcentage of qualified training times, and score of constructed graphs related to driving behaviors. The data are collected from a driving school in China. A pre diction model of the Subject 2 test outcome is constructed by adapting the Light Gradient Boosting Machine (LightGBM) ML method. Furthermore, the SHapley Additi ve exPlanation (SHAP) is employed to explore the relationships between key influ encing factors and the aforementioned outcome."
Beijing University of TechnologyBeijin gPeople's Republic of ChinaAsiaCyborgsEmerging TechnologiesMachine Lea rning
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