摘要
由一名新闻记者-机器人与机器学习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以获得。根据NewsRx Journalis TS在意大利的里雅斯特的新闻报道，Research称：“这项研究探索了监督机器学习技术在人力资源管理领域将原始数据转化为战略知识的潜力。通过分析一个包含205个变量和2932个与电信跨国公司有关的观察数据的数据库，”本研究检验了分类决策树在检测自愿性员工离职决定因素方面的预测和分析能力。这项研究的财政支持来自的里雅斯特大学。新闻记者从里雅斯特大学的研究中引用了一句话：“结果显示了可能非自愿离开公司的员工群体的决定因素，”突出了分类决策树分析深度的层次。本研究通过突出分类决策树在识别具有高度自愿离职倾向的员工群体特征方面的战略价值，为人力资源管理领域做出了贡献。
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-A new study on Machine Learning is now available. According to news reporting from Trieste, Italy, by NewsRx journalis ts, research stated, "This research explores the potential of supervised machine learning techniques in transforming raw data into strategic knowledge in the co ntext of human resource management. By analyzing a database with over 205 variab les and 2,932 observations related to a telco multinational corporation, this st udy tests the predictive and analytical power of classification decision trees i n detecting the determinants of voluntary employee turnover." Financial support for this research came from Universit degli Studi di Trieste. The news correspondents obtained a quote from the research from the University o f Trieste, "The results show the determinants of groups of employees who may vol untarily leave the company, highlighting the level of analytical depth of the cl assification tree. This study contributes to the field of human resource managem ent by highlighting the strategic value of the classification decision tree in i dentifying the characteristics of groups of employees with a high propensity to voluntarily leave the firm."
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