Open AccessMachine Learning for Predictions in Academics
Author(s) -
Shashi Sharma*,
Sunil Pandey,
Prof. Kumkum Garg
Publication year - 2020
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.e6965.018520
Subject(s) - machine learning , support vector machine , cluster analysis , naive bayes classifier , artificial intelligence , computer science , path (computing) , classifier (uml) , regression , mathematics , statistics , programming language
In recent years, a lot of data has been generated about students, which can be utilized for deciding the career path of the student. This paper discusses some of the machine learning techniques which can be used to predict the performance of a student and help to decide his/her career path. Some of the key Machine Learning (ML) algorithms applied in our research work are Linear Regression, Logistics Regression, Support Vector machine, Naïve Bayes Classifier and K- means Clustering. The aim of this paper is to predict the student career path using Machine Learning algorithms. We compare the efficiencies of different ML classification algorithms on a real dataset obtained from University students.