首页|Reports Outline Machine Learning Study Results from University of Trieste (Emplo yee Turnover In Multinational Corporations: a Supervised Machine Learning Approa ch)
Reports Outline Machine Learning Study Results from University of Trieste (Emplo yee Turnover In Multinational Corporations: a Supervised Machine Learning Approa ch)
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
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."
TriesteItalyEuropeCyborgsEmergin g TechnologiesMachine LearningUniversity of Trieste
NETL
NSTL
