Author
Listed:
- Mayuri S. Dongre
- Neha S.Vidya
- Vanita D. Telrandhe
- Shweta R. Chaudhari
- Anup A. Umrikar
- Prachiti V. Adghulkar
Abstract
Data in educational institutions are growing progressively along these lines there is a need of progress this tremendous data into helpful data and information utilizing data mining. Educational data mining is the zone of science where diverse techniques are being produced for looking and investigating data and this will be valuable for better comprehension of understudies and the settings they learned. Classification of data objects in view of a predefined learning of the articles is a data mining and information administration procedure utilized as a part of collection comparable data questions together. Decision Tree is a valuable and well known classification method that inductively takes in a model from a given arrangement of data. One explanation behind its prominence comes from the accessibility of existing calculations that can be utilized to assemble decision trees. In this paper we will survey the different ordinarily utilized decision tree calculations which are utilized for classification. We will likewise contemplating how these decision tree calculations are appropriate and valuable for educational data mining and which one is ideal.
Suggested Citation
Mayuri S. Dongre & Neha S.Vidya & Vanita D. Telrandhe & Shweta R. Chaudhari & Anup A. Umrikar & Prachiti V. Adghulkar, 2019.
"A Review on Various Algorithms for Student Performance Prediction,"
International Journal of Scientific Research in Computer Science, Engineering and Information Technology, International Journal of Scientific Research in Computer Science, Engineering and Information Technology, vol. 5(1), pages 235-239, February.
Handle:
RePEc:jbh:ijsrcs:v5:y2019:i1:id:hcseit195167
Note: Article URL: https://ijsrcseit.com/CSEIT195167
Download full text from publisher
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:jbh:ijsrcs:v5:y2019:i1:id:hcseit195167. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Pankaj Sharma (email available below). General contact details of provider: https://ijsrcseit.com/home .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.