摘要
机器人与机器学习的新闻编辑每日新闻-机器学习的新研究是一篇报道的主题。根据NewsR X记者在希腊雅典的新闻报道，研究表明，"由于计算机科学周围机器的成功使用和金融文献的广泛接受，我们利用欧元区周边国家2008-2018年期间的月度数据，以便开始一项双重任务。采用机器学习技术，构建欧元区外围国家银行存款流量的短期预测模型。记者们从雅典经济与商业大学的研究中获得了一句话，“第二，检验文本特征是否提高了我们模型的预测能力。从测试的各种模型中，我们发现，包括文本特征和宏观变量的随机森林模型优于仅包括宏观因素或文本特征的模型。”
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Machine Learning is th e subject of a report. According to news reporting from Athens, Greece, by NewsR x journalists, research stated, “Motivated by the successful usage of machine le arning around computer science and its wide acceptance from the finance literatu re, we utilize monthly data spanning the period 2008-2018 for the Euro area peri pheral countries, in order to embark on a two-fold mission. First, to construct short-term prediction models for bank deposit flows in the Euro area peripheral countries, employing machine learning techniques.” The news correspondents obtained a quote from the research from the Athens Unive rsity of Economics and Business, “Second, to examine whether textual features en hance the predictive ability of our models. From the variety of models tested, w e find that Random Forest models including both textual features and macroeconom ic variables outperform models including only macro factors or textual features. ”
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