An Effective Feature Selection for Type II Diabetes Prediction
Author:
Affiliation:
1. Alzahra University,Data Mining Laboratory,Department of Computer Engineering Faculty of Engineering,Tehran,Iran
2. Alzahra University,Faculty of Engineering,Department of Computer Engineering,Tehran,Iran
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10533315/10533316/10533371.pdf?arnumber=10533371
Reference23 articles.
1. Hybrid decision tree-based machine learning models for diabetes prediction
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3. A novel evolutionary ensemble prediction model using harmony search and stacking for diabetes diagnosis
4. Remote elderly healthcare: a robust deep learning approach for wearable sensors-based complex activities recognition;Serpush;AUT Journal of Modeling and Simulation AUT J. Model. Simul,2023
5. KFPredict: An ensemble learning prediction framework for diabetes based on fusion of key features
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