首页|Findings from University of Leuven (KU Leuven) Broaden Understanding of Machine Learning (Explaining the Model and Feature Dependencies By Decomposition of the Shapley Value)
Findings from University of Leuven (KU Leuven) Broaden Understanding of Machine Learning (Explaining the Model and Feature Dependencies By Decomposition of the Shapley Value)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - Research findings on Machine Learning are discussed in a new report. According tonews reporting originating from Leuv en, Belgium, by NewsRx correspondents, research stated, “Shapleyvalues have bec ome one of the go -to methods to explain complex models to end -users. They prov ide amodel agnostic post -hoc explanation with foundations in game theory: what is the worth of a player (inmachine learning, a feature value) in the objectiv e function (the output of the complex machine learningmodel).”
LeuvenBelgiumEuropeCyborgsEmergi ng TechnologiesMachine LearningUniversity of Leuven (KU Leuven)
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