CFP last date
20 December 2024
Call for Paper
January Edition
IJCA solicits high quality original research papers for the upcoming January edition of the journal. The last date of research paper submission is 20 December 2024

Submit your paper
Know more
The week's pick
Responsive image
Improved Shuffled Frog Leaping Algorithm with Self-Adaptive Shuffling for Fuzzy Logic PD+G Controller Optimization in Robotic Manipulators

Duc Hoang Nguyen
Random Articles
Reseach Article

Effect of Numerous Data Sets on Performance Prediction

by Jyoti Upadhyay, Pratima Gautam
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 147 - Number 5
Year of Publication: 2016
Authors: Jyoti Upadhyay, Pratima Gautam
10.5120/ijca2016911100

Jyoti Upadhyay, Pratima Gautam . Effect of Numerous Data Sets on Performance Prediction. International Journal of Computer Applications. 147, 5 ( Aug 2016), 30-32. DOI=10.5120/ijca2016911100

@article{ 10.5120/ijca2016911100,
author = { Jyoti Upadhyay, Pratima Gautam },
title = { Effect of Numerous Data Sets on Performance Prediction },
journal = { International Journal of Computer Applications },
issue_date = { Aug 2016 },
volume = { 147 },
number = { 5 },
month = { Aug },
year = { 2016 },
issn = { 0975-8887 },
pages = { 30-32 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume147/number5/25652-2016911100/ },
doi = { 10.5120/ijca2016911100 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:51:07.229862+05:30
%A Jyoti Upadhyay
%A Pratima Gautam
%T Effect of Numerous Data Sets on Performance Prediction
%J International Journal of Computer Applications
%@ 0975-8887
%V 147
%N 5
%P 30-32
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

There are many factors, which may affects performance. But the number of factors also affects on result of computational model. We are presenting a computational model to forecast students’ performance. To calculate we will use 8 different factors that are directly or indirectly influence performance. Influencing factors how much correlated to each other we also present this. Through this paper we classify those factors using fuzzy decision tree.

References
  1. Ramageri, Mrs. Bharati M. "DATA MINING TECHNIQUES AND APPLICATIONS ." Indian Journal of Computer Science and Engineering Vol. 1 No. 4 301-305 (2010): 301-305.
  2. Sonia Joseph, Laya Devadas. "Student’s Performance Prediction Using Weighted Modified ID3 Algorithm ." International Journal of Scientific Research Engineering & Technology (IJSRET), 4.5 (2015): 571.
  3. Zadeh, L. A. "fuzzy set." information and control 8 (1965): 338-352.
  4. Alec Pawling, Nitesh V. Chawla, and Amitabh Chaudhary. "Computing Information Gain in Data Streams." TDM 2005: 2005 Temporal Data Mining Workshop (2005): 72-81.
  5. G. V. Kass, “An Exploratory Technique for Investigating Large Quantities of Categorical Data”, Applied Statistic, Vol. 29, (1980): 119-127.
  6. M. Ramaswami , R. Bhaskaran , "A CHAID Based Performance Prediction Model in Educational Data Mining",International Journal of Computer Science Issues, Vol. 7, (2010) :10-18
  7. https://rapidminer.com/products/studio/, dated march 2016.
  8. Xiaodong Liu,Xinghua Fenga, andWitold Pedryczc, "Extraction of fuzzy rules from fuzzy decision trees: An axiomatic fuzzy sets (AFS) approach", Data & Knowledge EngineeringVolume 84, (2013) , 1–25
Index Terms

Computer Science
Information Sciences

Keywords

Data Mining Fuzzy Decision Tree Classification correlation and Prediction.

Powered by PhDFocusTM