2008年11月，英国Global Telecoms Business为了纪念其百年华诞，评选出了电信产业最有影响力的100位人士，at＆t主席Randall、苹果CEO Steve Jobs、中国工业和信息化部部长李毅中等均入选，电信级以太网的提出者、MEF（城域以太网论坛...2008年11月，英国Global Telecoms Business为了纪念其百年华诞，评选出了电信产业最有影响力的100位人士，at＆t主席Randall、苹果CEO Steve Jobs、中国工业和信息化部部长李毅中等均入选，电信级以太网的提出者、MEF（城域以太网论坛）主席陈子滴在众多名家中位列第58位，他的入选评语是：“陈相信以太网技术将会在建筑物、街道、城市、国家之间得到广泛使用，渐渐地整个产业都听从于他，开始将他的想法付诸实施。”展开更多
This study predicts the cash holdings policy of Turkish firms,given the 20 selected features with machine learning algorithm methods.211 listed firms in the Borsa Istanbul are analyzed over the period between 2006 and...This study predicts the cash holdings policy of Turkish firms,given the 20 selected features with machine learning algorithm methods.211 listed firms in the Borsa Istanbul are analyzed over the period between 2006 and 2019.Multiple linear regression(MLR),k-nearest neighbors(KNN),support vector regression(SVR),decision trees(DT),extreme gradient boosting algorithm(XGBoost)and multi-layer neural networks(MLNN)are used for prediction.Results reveal that MLR,KNN,and SVR provide high root mean square error(RMSE)and low R2 values.Meanwhile,more complex algorithms,such as DT and especially XGBoost,derive higher accuracy with a 0.73 R 2 value.Therefore,using advanced machine learning algorithms,we may predict cash holdings considerably.展开更多
文摘2008年11月，英国Global Telecoms Business为了纪念其百年华诞，评选出了电信产业最有影响力的100位人士，at＆t主席Randall、苹果CEO Steve Jobs、中国工业和信息化部部长李毅中等均入选，电信级以太网的提出者、MEF（城域以太网论坛）主席陈子滴在众多名家中位列第58位，他的入选评语是：“陈相信以太网技术将会在建筑物、街道、城市、国家之间得到广泛使用，渐渐地整个产业都听从于他，开始将他的想法付诸实施。”
文摘This study predicts the cash holdings policy of Turkish firms,given the 20 selected features with machine learning algorithm methods.211 listed firms in the Borsa Istanbul are analyzed over the period between 2006 and 2019.Multiple linear regression(MLR),k-nearest neighbors(KNN),support vector regression(SVR),decision trees(DT),extreme gradient boosting algorithm(XGBoost)and multi-layer neural networks(MLNN)are used for prediction.Results reveal that MLR,KNN,and SVR provide high root mean square error(RMSE)and low R2 values.Meanwhile,more complex algorithms,such as DT and especially XGBoost,derive higher accuracy with a 0.73 R 2 value.Therefore,using advanced machine learning algorithms,we may predict cash holdings considerably.
