Predicting Students' Performance Using ID3 and C4.5 Classification Algorithms

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Provided by: AIRCC
Topic: Data Management
Format: PDF
An educational institution needs to have an approximate prior knowledge of enrolled students to predict their performance in future academics. This helps them to identify promising students and also provides them an opportunity to pay attention to and improve those who would probably get lower grades. As a solution, the authors have developed a system which can predict the performance of students from their previous performances using concepts of data mining techniques under Classification. They have analyzed the data set containing information about students, such as gender, marks scored in the board examinations of classes X and XII, marks and rank in entrance examinations and results in first year of the previous batch of students.
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