A Model to Predict Pay Scale Fixation in Job Market Based on Educational Excellence
Abishek Kamalanathan1, Archana Tamizharasan2
1Abishek Kamalanathan, Department of Computer Science, Vit University, Vellore, India.
2Archana Tamizharasan,, Department of Computer Science, Asst. Professor, Vit University, Vellore, India

Manuscript received on 28 June 2019 | Revised Manuscript received on 05 July 2019 | Manuscript published on 30 July 2019 | PP: 909-914 | Volume-8 Issue-9, July 2019 | Retrieval Number: I7831078919/19©BEIESP | DOI: 10.35940/ijitee.I7831.078919

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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: The students of current generation worry a lot about their future salary when they get employment. The salary of an employee has always remained the major concern. In this paper we study and understand the major factors which are influencing the pay scales of the employees. This Research paper is based on predicting the pay scales of employees working in the southern part of India. The pay scale of an employee with below 4 lakh per annum is treated as medium pay scale and pay scale with above 4 lakh per annum is treated as good pay scale. In this paper the machine learning model is applied to predict the pay scale of an employee with the features which best suits the model. The year of passing, English marks, Quant marks, logical marks scores in AMCAT’s exam, programming skills and college CGPA were the major factors influencing the pay scales. Three machine learning algorithms were applied to the dataset Naïve bayes, Decision tree and Bagging .Naive bayes and bagging model gave the best accuracy of 85.2%
Index Terms: Feature Selection, Job Market, Pay Scale Forecast, Predicting Salaries.

Scope of the Article: Regression and Prediction