Copyright © 2026 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

@article{145750,
        author = {T. Shilpa and k. Venkataramana},
        title = {Prediction of Academic Performance Using Data mining Techniques},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {4},
        number = {11},
        pages = {84-86},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=145750},
        abstract = {This paper displays the aftereffects of applying an instructive information mining way to deal with demonstrate scholarly weakening  (loss of scholarly status) at the Universidad Nacional de Colombia. Two information mining models were characterized to dissect the scholarly and nonacademic information; the models utilize two order strategies, gullible Bayes and a choice tree classifier, all together to gain a superior comprehension of the weakening amid the to begin with enlistments and to evaluate the nature of the information for the arrangement errand, which can be comprehended as the expectation of the loss of scholastic status because of low scholarly execution. The models mean to anticipate the steady loss in the understudy's initial four enlistments. To start with, thinking about any of these periods, and afterward, at a particular enlistment. Chronicled scholarly records and information from the affirmation procedure were utilized to prepare the models, which were assessed utilizing cross-approval and before hand inconspicuous records from a full scholarly period. Test comes about demonstrate that the forecast of the loss of scholarly status is enhanced when the scholarly information are included.},
        keywords = {data mining, prediction, attrition},
        month = {},
        }