Integrating Weka Into Web Application: Predicting Student’s Performance
Journal Title: International Journal of engineering Research and Applications - Year 2017, Vol 7, Issue 12
Abstract
In today‟s world, there are many stand alone data mining tools that can be used by the academicians to carry out data mining tasks. Any Educational Institute can show the curiosity to know the future performance of recently joined students. To address this, We have analyzed the data set containing information about students, and results in first year of the previous batch of students. By applying the ID3 (Iterative Dichotomiser 3), C4.5, Naive Bayes, Multilayer Perceptron and K-Nearest Neighbour classification algorithms on this data, we have predicted the general and individual performance of freshly admitted students in future examinations and made the entire implementation dynamic to train the prediction parameters itself when new training sets are fed into the web application.
Authors and Affiliations
D. Fatima, Dr. Sameen Fatima, Dr. A. V. Krishna Prasad
Keywords
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- EP ID EP393307
- DOI 10.9790/9622-071207785.
- Views 88
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