Campus Placement Data Analysis Using Classification Techniques
Author(s):
E. Hari Haran, S.Ramesh, A.S. Omkumar , S.R.Arun Kumar , V. Saravanan, M.S. Sassirekha, Anbarasan Balakrishnan
Keywords:
Classification, Numpy, Pandas, Sklearn, Seaborn, Logistic Regression, Decision Tree, Random Forest, K - Nearest Neighbours, Support Vector Machine, XGBoost, AdaBoost, Outliers, Label Encoding and One Hot Encoding
Abstract
The dataset revolves around the placement season of a Business School in India. Where it has various factors on candidates getting hired such as work experience,exam percentage etc. Finally it contains the status of recruitment and remuneration details. A Set of Classification analysis is performed to predict whether the student is placed or not.
Article Details
Unique Paper ID: 154169

Publication Volume & Issue: Volume 8, Issue 7

Page(s): 32 - 34
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