文章基本信息

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 等
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