摘要
由一名新闻记者-机器人与机器学习日报的工作人员新闻编辑每日新闻-一项关于机器学习的新研究现在可用。根据来自中华人民共和国杭州，NewsRx记者，研究称，“在这项研究中，四台机器本文应用学习模型估计了三个buo y站在水位变化过程中所记录的水位变化2022年汤加海啸。提出了一种新的绩效评价模型——滞后度补偿常规评估指标（如RMSE和R-2值）的局限性，它可以指定估计和原始时间序列数据之间的滞后程度，因此滞后失败。
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - A new study on Machine Learning is now available. According to news reporting fromHangzhou, People’s Republic of Chin a, by NewsRx journalists, research stated, “In this study, four machinelearning models are applied to estimate the water level variations recorded at three buo y stations duringthe 2022 Tonga tsunami. A new model performance evaluation met ric, the lag degree, is introduced tocompensate for the limitations of the conv entional evaluation metrics (such as RMSE and R-2 values),which could specify t he lag extent, thus lag failure, between the estimated and original time series data.”
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