five

Predicting the Results of Evaluation Procedures of Academics: Additional Materials

收藏
DataCite Commons2020-08-28 更新2024-07-27 收录
下载链接:
https://figshare.com/articles/Predicting_the_Results_of_Evaluation_Procedures_of_Academics_Additional_Materials/6814550
下载链接
链接失效反馈
官方服务:
资源简介:
Additional materials containing the results of the analyses described in the paper entitled "Predicting the Results of Evaluation Procedures of Academics".In the tables, Precision (P), Recall (R) and F-Measure (FM) values are reported for each Recruitment Field (RF) and Area. The results are ordered in descending order with respect to the F-measure values. Non-bibliometric disciplines have a gray background.The data are organized as follows:<b>-Table 1:</b> contains the performance of the SVM algorithm for academic level I (Full Professor) using 291 predictors. Analysis of the 184 recruitment fields;<b>-Table 2:</b> contains the performance of the SVM algorithm for academic level II (Associate Professor) using 291 predictors. Analysis of the 184 recruitment fields;<b>-Table 3:</b> contains the performance of the SVM algorithm for academic level I (full Professor) and II (Associate Professor). Analysis of the scientific areas;<b>-Table 4:</b> contains the performance of the SVM algorithm for academic level I (Full Professor) using the top 15 predictors. Analysis of the 184 recruitment fields;<b>-Table 5:</b> contains the performance of the SVM algorithm for academic level II (Associate Professor) using the top 15 predictors. Analysis of the 184 recruitment fields.<br>
提供机构:
figshare
创建时间:
2018-07-13
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作