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Machine Learning Technique to Predicting Student Performance in Higher Education


Affiliations
1 Bhopal (M. P.), India
2 IT Dept., AISECT University, Bhopal (M. P.), India
     

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One of the famous and practical methods for inductive implication over directed data is Decision Tree learning. Decision tree is suitable to classifying categorical data using attributes of database. In this paper educational data mining has been used on qualitative data of students and analysis their performance using c4.5 decision tree algorithm.

The results indicate that student’s performance also influenced by qualitative data. Acquired knowledge in form of tree is easy to assimilate by users.


Keywords

Decision Tree, Learning, Prediction, Qualitative Data.
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  • Machine Learning Technique to Predicting Student Performance in Higher Education

Abstract Views: 187  |  PDF Views: 3

Authors

Jyoti Upadhyay
Bhopal (M. P.), India
Pratima Gautam
IT Dept., AISECT University, Bhopal (M. P.), India

Abstract


One of the famous and practical methods for inductive implication over directed data is Decision Tree learning. Decision tree is suitable to classifying categorical data using attributes of database. In this paper educational data mining has been used on qualitative data of students and analysis their performance using c4.5 decision tree algorithm.

The results indicate that student’s performance also influenced by qualitative data. Acquired knowledge in form of tree is easy to assimilate by users.


Keywords


Decision Tree, Learning, Prediction, Qualitative Data.