A Multicriteria Weighted Vote-Based Classifier Ensemble for Heart Disease Prediction-Reference-Cited by-同舟云学术

A Multicriteria Weighted Vote-Based Classifier Ensemble for Heart Disease Prediction

Published:2015-06-22 Issue:4 Volume:32 Page:615-645
ISSN:0824-7935
Container-title:Computational Intelligence
language:en
Short-container-title:Computational Intelligence

Author:

Bashir Saba¹,Qamar Usman¹,Khan Farhan Hassan¹

Affiliation:

1. Computer Engineering Department, College of Electrical and Mechanical Engineering; National University of Sciences and Technology (NUST); Islamabad Pakistan

Publisher

Wiley

Subject

Artificial Intelligence,Computational Mathematics

Reference54 articles.

1. Efficient OCR using simple features and decision trees with backtracking;Abuhaiba;The Arabian Journal for Science and Engineering,2006

2. Enhanced prediction of heart disease with feature subset selection using genetic algorithm;Anbarasi;International Journal of Engineering Science and Technology,2010

3. Chen , A. H. S. Y. Huang P. S. Hong C. H. Cheng E. J. Lin 2011 HDPS: heart disease prediction system In Hangzhou 557 560

4. Heart disease prediction system using supervised learning classifier;Chitra;International Journal of Software Engineering and Soft Computing,2013

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