CFP last date
20 January 2025
Call for Paper
February Edition
IJCA solicits high quality original research papers for the upcoming February edition of the journal. The last date of research paper submission is 20 January 2025

Submit your paper
Know more
The week's pick
Responsive image
SFLA-Based Line Balancing and Task Optimization in Master-Slave Controlled Hanger Transportation Systems for Garment Production

Duc Hoang Nguyen
Random Articles
Reseach Article

Classification Rules by Decision Tree for Disease Prediction

by Smitha. T, V. Sundaram
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 43 - Number 8
Year of Publication: 2012
Authors: Smitha. T, V. Sundaram
10.5120/6121-8323

Smitha. T, V. Sundaram . Classification Rules by Decision Tree for Disease Prediction. International Journal of Computer Applications. 43, 8 ( April 2012), 6-12. DOI=10.5120/6121-8323

@article{ 10.5120/6121-8323,
author = { Smitha. T, V. Sundaram },
title = { Classification Rules by Decision Tree for Disease Prediction },
journal = { International Journal of Computer Applications },
issue_date = { April 2012 },
volume = { 43 },
number = { 8 },
month = { April },
year = { 2012 },
issn = { 0975-8887 },
pages = { 6-12 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume43/number8/6121-8323/ },
doi = { 10.5120/6121-8323 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:32:52.289884+05:30
%A Smitha. T
%A V. Sundaram
%T Classification Rules by Decision Tree for Disease Prediction
%J International Journal of Computer Applications
%@ 0975-8887
%V 43
%N 8
%P 6-12
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This research paper mainly focuses on a data mining technique, that had an objective of creating a prediction model, using decision tree for predicting the chances of occurances of diseases in an area, particularly slum. This model also identifies different significant parameters which can be used to help for the creation of model. Decision tree is one of the learning algorithm which possess certain advantages which make it suitable for discovering rules for data mining application. In this paper the decision tree has been applied to classify the inhabitants in an area based on the chances of hitting a disease. This paper intended to discover the rules for the disease hit using decision tree algorithm. The paper also explores what rule can act in this area for the future prediction.

References
  1. Jaiwei Han;Micheline kamber;Data mining concepts and Techniques;Morgan Kaufmann Publishers.
  2. Fayyad U. M. Piatetsky-Shapiro. G & smith. P" From data mining to knowledge discovery in databases'AI magazine 17(3) pp-37-54.
  3. Ms. Sunu Mary Abraham"User Behaviour BasedClustering and Decision Tree Model for predicting customer insolvency in Telecommunication Business. Karpagam Journal-Jan-2011, Volume 5
  4. K. S. Adekeye and M. A. Lamidi, "Prediction Intervals: A tool for monitoring outbreak of diseases" Intternational journal for data Analysis and information System jan-2011-Vol-3.
  5. Aitchison. J and Dunsmore, Statistical Prediction Analysis: Cambridge University Press.
  6. Waleed Alsabhan and Oualid Ben Ali " A new multimodal approach using data mining: the case of jobseekers in the USA" Intternational journal for data Analysis and information System jan-2011-Vol-3.
  7. Rui Xu , Donald C. and WunschClustering, Iee Press-2008.
  8. Bori Mirkin(2005) clustering for Data mining Chapman & Hall/Crc.
  9. Apte, C. and Weiss,S. M(1997), " Data mining with Decision Trees and Decision Rules" Future generation computer systems, 13,197-210.
  10. Ch. Ding, X. He"K means clustering via principal component Analysis Proc. of international conference on machine learning(2004),pp. 225-232,2004.
Index Terms

Computer Science
Information Sciences

Keywords

Clustering Data Mining Decision Tree Prediction

Powered by PhDFocusTM