Student Academic Performance analysis using Classification algorithms

E. Iyappan; K. Rajapriya; A. Santhosh; T. Sasikumar; P. Vinitha; M.S. Sassirekha; Anbarasan Balakrishnan

Student Academic Performance analysis using Classification algorithms

Authors: E. Iyappan, K. Rajapriya, A. Santhosh, T. Sasikumar, P. Vinitha, M.S. Sassirekha, Anbarasan Balakrishnan

Unique Paper ID: 154170
Volume: 8
Issue: 7
PageNo: 35-38

Keywords: Classification Support Vector classification Adaboost Matplotlib Seaborn Logistic regression Decision tree Random forest Stochastic classification

Abstract:
In this paper, we performed analysis is to measure performance of the students and factors affecting their performance. The model can be used for early predicting student performance to help in improving student performance on the subject. Supervised algorithms like Decision tree, Adaboost, Random Forest, Stochastic classification and Logistic regression are used to predict the model.

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Cite This Article

ISSN: 2349-6002
Volume: 8
Issue: 7
PageNo: 35-38

Student Academic Performance analysis using Classification algorithms

Available:https://ijirt.org/Article?manuscript=154170

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