Glaucoma detection using cross validation algorithm: A comparitive evaluation on rapidminer

Author

Chaudhary, Kalnana ; Maheshwari, Pushp ; Wadhwa, Sameer

Author_Institution

Dept. of CSE & IT, ITM Univ., Gurgaon, India

fYear

2014

fDate

24-26 June 2014

Firstpage

1

Lastpage

5

Abstract

This paper is basically extension of my work on glaucoma detection. This can be achieved by various data mining techniques and algorithms such as Association, Classification, Clustering, Fuzzy decision tree etc. The objective of this paper is early detection of glaucoma using cross validation algorithm. We will analyses the symptoms shown by different patients and compute and generalize them to reach a decision. This will help not only patients but doctors also to make it primarily practice to follow for new patients.

Keywords

data mining; decision trees; diseases; fuzzy set theory; medical computing; pattern classification; pattern clustering; comparative evaluation; cross validation algorithm; data association; data classification; data clustering; data mining algorithms; data mining techniques; fuzzy decision tree; glaucoma detection; rapidminer; Accuracy; Algorithm design and analysis; Classification algorithms; Decision trees; Educational institutions; Optical imaging; Prediction algorithms; BP; Classification; Cross Validation Algorithm; Decision Tree; Myopia;

fLanguage

English

Publisher

ieee

Conference_Titel

Norbert Wiener in the 21st Century (21CW), 2014 IEEE Conference on

Conference_Location

Boston, MA

Type

conf

DOI

10.1109/NORBERT.2014.6893924

Filename

6893924