Imputation Techniques and Recursive Feature Elimination in Machine Learning Applied to Type II Diabetes Classification-Reference-Cited by-同舟云学术

Imputation Techniques and Recursive Feature Elimination in Machine Learning Applied to Type II Diabetes Classification

Published:2021-12-17 Issue: Volume: Page:
ISSN:
Container-title:2021 4th Artificial Intelligence and Cloud Computing Conference
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Author:

Catimbang Magboo Vincent Peter¹,Abad Magboo Ma. Sheila¹

Affiliation:

1. Department of Physical Sciences and Mathematics, College of Arts and Sciences, University of the Philippines Manila, Philippines

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3508259.3508288

Reference29 articles.

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2. Fayroza Alaa Khaleel and Abbas M . Al-Bakry. 2021. Diagnosis of diabetes using machine learning algorithms . Mater. Today Proc. (July 2021 ). DOI:https://doi.org/10.1016/j.matpr. 2021 .07.196 Fayroza Alaa Khaleel and Abbas M. Al-Bakry. 2021. Diagnosis of diabetes using machine learning algorithms. Mater. Today Proc. (July 2021). DOI:https://doi.org/10.1016/j.matpr.2021.07.196

3. Predicting diabetes mellitus using SMOTE and ensemble machine learning approach: The Henry Ford ExercIse Testing (FIT) project

4. Machine learning algorithms for Diabetes prediction and neural network method for blood glucose measurement

5. Prediction of Type 2 Diabetes Based on Machine Learning;Deberneh Henock M.;Algorithm. Int. J. Environ. Res. Public Health,2021

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