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-调查人员讨论机器学习的新发现。根据新闻报道在科罗拉多州丹佛市,由NewsRx编辑,研究称:“我们评估美国市场回报的可预测性。”使用了一个新的数据集，该数据集包含了几百个AG级企业层面的特征。我们用弹性套索网络、随机森林、神经网络、极端梯度提升、三维光梯度提升机方法和发现这些模型经历了巨大的预测误差，导致预测失败。
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Investigators discuss new findings in Machine Learning. According to news reportingout of Denver, Colorado, by NewsRx editors, research stated, “We evaluate US market return predictabilityusing a novel data set of several hundred ag- gregated firm-level characteristics. We ap ply LASSO, ElasticNet, Random Forest, Neural Net, Extreme Gradient Boosting, an d Light Gradient Boosting Machinemethods and find these models experience large prediction errors that lead to forecast failures.”
NETL
NSTL