首页|Data from University of South Australia Provide New Insights into Machine Learni ng (LLpowershap: logistic loss-based automated Shapley values feature selection method)
Data from University of South Australia Provide New Insights into Machine Learni ng (LLpowershap: logistic loss-based automated Shapley values feature selection method)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators discuss new findings in artificial intelligence. According to news originating from the University of So uth Australia by NewsRx correspondents, research stated, “Shapley values have be en used extensively in machine learning, not only to explain black box machine l earning models, but among other tasks, also to conduct model debugging, sensitiv ity and fairness analyses and to select important features for robust modelling and for further follow-up analyses. Shapley values satisfy certain axioms that p romote fairness in distributing contributions of features toward prediction or r educing error, after accounting for non-linear relationships and interactions wh en complex machine learning models are employed.”
University of South AustraliaCyborgsEmerging TechnologiesMachine Learning
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