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  • 标题:Salary Estimation Using Model Building Regression Technique
  • 本地全文:下载
  • 作者:CHAITANYA LAHARI NAYUDU ; CHETANA LAASYA NAYUDU ; G.MOUNIKA
  • 期刊名称:International Journal of Innovative Research in Computer and Communication Engineering
  • 印刷版ISSN:2320-9798
  • 电子版ISSN:2320-9801
  • 出版年度:2021
  • 卷号:9
  • 期号:7
  • 页码:8700-8703
  • DOI:10.15680/IJIRCCE.2021.0907149
  • 语种:English
  • 出版社:S&S Publications
  • 摘要:The goal of this paper is to predict salary of a person after a certain year. The graphical representation of predicting salary is a process that aims for developing computerized system to maintain all the daily work of salary growth graph in any field and can predict salary after a certain time period.These days, the problem faced by employees is the lack of knowledge base to negotiate their salaries during their employment. Often, HR asks the interviewee – “How much salary are you expecting?”. Since, the interviewee is not aware of various parameters to come to a conclusion, they settle for less. So, this proposed project lets you to estimate various salaries in a particular field from a beginner level job role to highest managerial job role. The Estimator gives you estimation by using the data collected from a particular website of around 1000 companies. This project optimizes linear, lasso and random forest regressions and will reach the best model and will built client facing API using flask.
  • 关键词:API;regression
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