{"title":"预测模型:应届大学毕业生就业因素研究","authors":"Li Li","doi":"10.3233/jcm-226951","DOIUrl":null,"url":null,"abstract":"The employment situation of fresh college graduates is affected by many factors. In this paper, on the basis of decision tree, the C4.5 method was used to analyze the employment factors of fresh college graduates. An improved C4.5 model was designed by simplifying the calculation formula of the C4.5 method and combining the error tolerance. Experiments were performed on the actual data of fresh college graduates. The results found that the practice level had a great impact on the employment of fresh college graduates, so the training of the practice level should be focused on before graduation. The results of the prediction models showed that the improved C4.5 method had a smaller training error than ID3 and C4.5 methods, a significantly higher prediction accuracy (88.39%), higher precision, recall rate, and F1 value, and a shorter running time (1.642 s); the improved model remained a high accuracy even when the data volume increased. The experimental results verify the reliability of the improved C4.5 model in predicting the employment situation of fresh college graduates. The model can be applied in actual employment guidance.","PeriodicalId":45004,"journal":{"name":"Journal of Computational Methods in Sciences and Engineering","volume":"3 1","pages":""},"PeriodicalIF":0.5000,"publicationDate":"2023-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A predictive model: A study of employment factors for fresh college graduates\",\"authors\":\"Li Li\",\"doi\":\"10.3233/jcm-226951\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The employment situation of fresh college graduates is affected by many factors. In this paper, on the basis of decision tree, the C4.5 method was used to analyze the employment factors of fresh college graduates. An improved C4.5 model was designed by simplifying the calculation formula of the C4.5 method and combining the error tolerance. Experiments were performed on the actual data of fresh college graduates. The results found that the practice level had a great impact on the employment of fresh college graduates, so the training of the practice level should be focused on before graduation. The results of the prediction models showed that the improved C4.5 method had a smaller training error than ID3 and C4.5 methods, a significantly higher prediction accuracy (88.39%), higher precision, recall rate, and F1 value, and a shorter running time (1.642 s); the improved model remained a high accuracy even when the data volume increased. The experimental results verify the reliability of the improved C4.5 model in predicting the employment situation of fresh college graduates. The model can be applied in actual employment guidance.\",\"PeriodicalId\":45004,\"journal\":{\"name\":\"Journal of Computational Methods in Sciences and Engineering\",\"volume\":\"3 1\",\"pages\":\"\"},\"PeriodicalIF\":0.5000,\"publicationDate\":\"2023-12-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Computational Methods in Sciences and Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3233/jcm-226951\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"ENGINEERING, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Computational Methods in Sciences and Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3233/jcm-226951","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENGINEERING, MULTIDISCIPLINARY","Score":null,"Total":0}
A predictive model: A study of employment factors for fresh college graduates
The employment situation of fresh college graduates is affected by many factors. In this paper, on the basis of decision tree, the C4.5 method was used to analyze the employment factors of fresh college graduates. An improved C4.5 model was designed by simplifying the calculation formula of the C4.5 method and combining the error tolerance. Experiments were performed on the actual data of fresh college graduates. The results found that the practice level had a great impact on the employment of fresh college graduates, so the training of the practice level should be focused on before graduation. The results of the prediction models showed that the improved C4.5 method had a smaller training error than ID3 and C4.5 methods, a significantly higher prediction accuracy (88.39%), higher precision, recall rate, and F1 value, and a shorter running time (1.642 s); the improved model remained a high accuracy even when the data volume increased. The experimental results verify the reliability of the improved C4.5 model in predicting the employment situation of fresh college graduates. The model can be applied in actual employment guidance.
期刊介绍:
The major goal of the Journal of Computational Methods in Sciences and Engineering (JCMSE) is the publication of new research results on computational methods in sciences and engineering. Common experience had taught us that computational methods originally developed in a given basic science, e.g. physics, can be of paramount importance to other neighboring sciences, e.g. chemistry, as well as to engineering or technology and, in turn, to society as a whole. This undoubtedly beneficial practice of interdisciplinary interactions will be continuously and systematically encouraged by the JCMSE.