{"title":"通过使用不同的机器学习方法来评估经理培训计划的有效性","authors":"Vedna Sharma, Sourabh Jain","doi":"10.1109/ICECA49313.2020.9297556","DOIUrl":null,"url":null,"abstract":"Evaluating the training program conducted for managers is very essential to check the feasibility and effectiveness of the offered training programs.. The traditional analysis of trainee managers feedback about training programs will become more prone to imprecision or inaccuracy, which are caused due to the non-consideration of quality features that will influence either directly or indirectly. Accordingly, the results of feedback analysis managerswill not be considered as a true indicator to evaluate the performance of training program. Henceforth, this paper has proposed an automated solution to evaluate the performance of training programs offered to the managers by using two supervised machine learning techniques namely support vector machine (SVM) and decision tree. The proposed research work will also help to overcome the limitations of the existing studies by enhancing the efficiency, relevancy and reliability of training programs offered to managers and also provide basic needs to enhance the performance, which will also improve the standard of training program and optimize it accordingly.","PeriodicalId":297285,"journal":{"name":"2020 4th International Conference on Electronics, Communication and Aerospace Technology (ICECA)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Managers Training Programs Effectiveness Evaluation by using different Machine Learning Approaches\",\"authors\":\"Vedna Sharma, Sourabh Jain\",\"doi\":\"10.1109/ICECA49313.2020.9297556\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Evaluating the training program conducted for managers is very essential to check the feasibility and effectiveness of the offered training programs.. The traditional analysis of trainee managers feedback about training programs will become more prone to imprecision or inaccuracy, which are caused due to the non-consideration of quality features that will influence either directly or indirectly. Accordingly, the results of feedback analysis managerswill not be considered as a true indicator to evaluate the performance of training program. Henceforth, this paper has proposed an automated solution to evaluate the performance of training programs offered to the managers by using two supervised machine learning techniques namely support vector machine (SVM) and decision tree. The proposed research work will also help to overcome the limitations of the existing studies by enhancing the efficiency, relevancy and reliability of training programs offered to managers and also provide basic needs to enhance the performance, which will also improve the standard of training program and optimize it accordingly.\",\"PeriodicalId\":297285,\"journal\":{\"name\":\"2020 4th International Conference on Electronics, Communication and Aerospace Technology (ICECA)\",\"volume\":\"13 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-11-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 4th International Conference on Electronics, Communication and Aerospace Technology (ICECA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICECA49313.2020.9297556\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 4th International Conference on Electronics, Communication and Aerospace Technology (ICECA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICECA49313.2020.9297556","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Managers Training Programs Effectiveness Evaluation by using different Machine Learning Approaches
Evaluating the training program conducted for managers is very essential to check the feasibility and effectiveness of the offered training programs.. The traditional analysis of trainee managers feedback about training programs will become more prone to imprecision or inaccuracy, which are caused due to the non-consideration of quality features that will influence either directly or indirectly. Accordingly, the results of feedback analysis managerswill not be considered as a true indicator to evaluate the performance of training program. Henceforth, this paper has proposed an automated solution to evaluate the performance of training programs offered to the managers by using two supervised machine learning techniques namely support vector machine (SVM) and decision tree. The proposed research work will also help to overcome the limitations of the existing studies by enhancing the efficiency, relevancy and reliability of training programs offered to managers and also provide basic needs to enhance the performance, which will also improve the standard of training program and optimize it accordingly.