Abstract of Predication of Stude, IJSR, Call for Papers, Online Journal
International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Call for Papers | Fully Refereed | Open Access | Double Blind Peer Reviewed

ISSN: 2319-7064


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Research Paper | Computer Science & Engineering | India | Volume 6 Issue 5, May 2017


Predication of Students Performance Using Data Mining

A. V. Kadu | Dr. G. R. Bamnote


Abstract: The achievement of the good context of different degrees and education which is in the Undergraduate degrees the important in the context of Higher Education, and both for students and for the institutions that host them. To investigate attempt to use data mining techniques to predict students outcomes based on early module performance and other student characteristics. In this work on whether the data mining can be used to highlight performance problems early in that and propose remedial actions. Many more are the some of the methods may also form the basis for recommender systems in that may guide students towards their module choices to increase the good outcomes their chances is necessary for good outcome. Here use data collected through the admission process and through the students degrees. In this predict good context of different degrees and education outcomes based on data at admission also on the first year results of modules. To validate the proposed results modules, we evaluate the system whether the data relating to students with different characteristics from the different schools and the collages. Many universities have specific targets for students achieving good honor degrees.


Keywords: Classification, Data Mining, Performance Prediction, Recommender System


Edition: Volume 6 Issue 5, May 2017,


Pages: 1223 - 1228


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How to Cite this Article?

A. V. Kadu, Dr. G. R. Bamnote, "Predication of Students Performance Using Data Mining", International Journal of Science and Research (IJSR), Volume 6 Issue 5, May 2017, pp. 1223-1228, https://www.ijsr.net/get_abstract.php?paper_id=ART20173509

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