摘要
机器人与机器学习每日新闻的一位新闻记者兼新闻编辑-机器学习的最新研究结果已经发表。根据NewsRx记者在田纳西州橡树岭的新闻报道，研究表明：“机器学习方法越来越多地用于以较低的计算成本为复杂物理系统构建代理模型。然而，这些模型的预测能力在有噪声、稀疏或动态数据的情况下会下降。”
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Current study results on Machine Learn ing have been published. According to news reporting originating in Oak Ridge, Tennessee, by NewsRx journalists, research stated, “Machine learning methods are increasingly deployed to construct surrogate models for complex physical systems at a reduced computational cost. However, the predictive capability of these su rrogates degrades in the presence of noisy, sparse or dynamic data.”
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