A Placement Prediction System using k-nearest neighbors classifier

Animesh Giri, M. V. V. Bhagavath, Bysani Pruthvi, Naini Dubey
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引用次数: 29

Abstract

In this paper, we propose a Placement Prediction System which predicts the probability of a undergrad student getting placed in an IT company by applying the machine learning model of k-nearest neighbors's classification. We also compare the results of the same against the results obtained from other models like Logistic Regression and SVM. To do so we consider the academic history of the student as well as their skill set like, programming skills, communication skills, analytical skills and team work, which are tested by the hiring companies during the recruitment process. The data that is used for this purpose is the Placement Statistics of PES Institute of Technology, Bangalore South Campus for the previous two academic batches.
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基于k近邻分类器的位置预测系统
在本文中,我们提出了一个安置预测系统,该系统通过应用k近邻分类的机器学习模型来预测大学生在IT公司的安置概率。我们还将相同的结果与其他模型(如Logistic回归和SVM)的结果进行了比较。为了做到这一点,我们考虑学生的学术历史以及他们的技能,如编程技能,沟通能力,分析能力和团队合作能力,这些都是招聘公司在招聘过程中测试的。用于此目的的数据是PES理工学院班加罗尔南校区前两个学术批次的安置统计数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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