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AN EFFECTIVE ANALYSIS FOR STUDENT JOB OPPORTUNITIES USING MULTIPLE LINEAR REGRESSION MODEL

. J.Umamageswaran1, S.MohanRaj 2, Allamadhev 3, M. Rahul 4, Logesh


Abstract

Nowadays, the job opportunity for university and college graduates is becoming a disputed point for the people in India. With the increased growth of current technology, lot and lot of people have realized that only to uphold the balances and transparency about the information can provide more opportunities for many graduates. Normally admission and reputation is mainly depends on employability of the institute graduate. Hence, all college strives to strengthen the placement department. In this paper, we proposed an machine learning algorithm to analyse previous year's student's historical data and predict placement chance for the current students and the percentage placement chance of the institution. Furthermore, we have implemented an multi linear regression algorithms to predict the placement chance of students to each company. Data relating to this work collected from the same institution for which the prediction the placement chance and placement percentage need to be establishing from 2014 to 2018. The year 2017 is the test data and 2018 data is considered as current data. We have also applied appropriate data pre-processing methods are applied. This proposed model is compared with Simple Linear Regression. From the results obtained, it is found that the proposed algorithm predicts better in comparison with other algorithms. 
 
 
Keywords: Data mining, prediction, Simple Linear Regression, Multiple Linear regression 

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