Open Access   Article Go Back

A Machine Learning Based Diabetes Prediction Using Stacking and Stacking With Hyperparameter Tuning

Sadhana Tiwari1 , Awadhesh Kumar2 , Aasha Singh3

Section:Research Paper, Product Type: Journal Paper
Volume-10 , Issue-6 , Page no. 16-21, Jun-2022

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v10i6.1621

Online published on Jun 30, 2022

Copyright © Sadhana Tiwari, Awadhesh Kumar, Aasha Singh . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

View this paper at   Google Scholar | DPI Digital Library

XML View
PDF Download

How to Cite this Paper

  • IEEE Citation
  • MLA Citation
  • APA Citation
  • BibTex Citation
  • RIS Citation

IEEE Style Citation: Sadhana Tiwari, Awadhesh Kumar, Aasha Singh, “A Machine Learning Based Diabetes Prediction Using Stacking and Stacking With Hyperparameter Tuning,” International Journal of Computer Sciences and Engineering, Vol.10, Issue.6, pp.16-21, 2022.

MLA Style Citation: Sadhana Tiwari, Awadhesh Kumar, Aasha Singh "A Machine Learning Based Diabetes Prediction Using Stacking and Stacking With Hyperparameter Tuning." International Journal of Computer Sciences and Engineering 10.6 (2022): 16-21.

APA Style Citation: Sadhana Tiwari, Awadhesh Kumar, Aasha Singh, (2022). A Machine Learning Based Diabetes Prediction Using Stacking and Stacking With Hyperparameter Tuning. International Journal of Computer Sciences and Engineering, 10(6), 16-21.

BibTex Style Citation:
@article{Tiwari_2022,
author = {Sadhana Tiwari, Awadhesh Kumar, Aasha Singh},
title = {A Machine Learning Based Diabetes Prediction Using Stacking and Stacking With Hyperparameter Tuning},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {6 2022},
volume = {10},
Issue = {6},
month = {6},
year = {2022},
issn = {2347-2693},
pages = {16-21},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=5474},
doi = {https://doi.org/10.26438/ijcse/v10i6.1621}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v10i6.1621}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=5474
TI - A Machine Learning Based Diabetes Prediction Using Stacking and Stacking With Hyperparameter Tuning
T2 - International Journal of Computer Sciences and Engineering
AU - Sadhana Tiwari, Awadhesh Kumar, Aasha Singh
PY - 2022
DA - 2022/06/30
PB - IJCSE, Indore, INDIA
SP - 16-21
IS - 6
VL - 10
SN - 2347-2693
ER -

VIEWS PDF XML
322 344 downloads 160 downloads
  
  
           

Abstract

Due to the high blood sugar or blood glucose, the problem of diabetes will occur, and it`s also referred to as a metabolic disorder. Long-term high blood glucose levels can result in several heart-related disorders, strokes, renal illness, vision difficulties, dental problems, nerve damage, and other problems. The latest recent information about diabetes worldwide may be found in the IDF Diabetes Atlas, ninth edition 2021.There are 537 million adults facing the problem of diabetes according to the measurement of 2021 year. And we are guessing that there will be total diabetes patients will number 643 million by 2030 and 783 million by 2045. To predict the diabetes, we generally use machine learning algorithms. Here we have executed various machine learning algorithms like K-Nearest Neighbor, Logistic Regression, Decision Tree, Random Forest, Support Vector Machine, Stacking and Stacking with Hyperparameter Tuning. Each model will have different accuracy in compared to other models. The most accurate result can be achieved by the stacking and stacking with hyperparameter tuning.

Key-Words / Index Term

Machine Learning, Diabetes, Random Forest, Stacking, Hyperparameter Tuning, LogisticRegression

References

[1] M. Soni, Dr. S. Varma, “Diabetes Prediction Using Machine Learning Techniques”. International Journal of Engineering Research & Technology, Vol.9, Issue. 9, pp. 921-925, 2020.
[2] K. Patil, S.D. Sawarkar, “Designing a Model to Detect Diabetes Using Machine Learning”. International Journal of Engineering Research & Technology, Vol. 8, Issue. 11, pp. 512-515, 2019.
[3] S. Gujral, “Early Diabetes Detection Using Machine Learning”. International Journal for Innovative Research in Science & Technology, Vol. 3, Issue. 10, pp. 57-62 , 2017.
[4] S. Sivaranjani, S. Ananya, J. Aravinth, R. Karthika, “Diabetes Prediction using Machine Learning Algorithms with Feature Selection and Dimensionality Reduction”, International Conference on Advanced Computing and Communication Systems, India, pp. 141-146, 2021.
[5] D. K. Choubey, S. Paul, “A Hybrid Intelligent System for Diabetes Disease Diagnosis”, International Journal of Intelligent Systems and Applications, Vol. 08, Issue. 01, pp. 49-59 , 2016.
[6] M.Shuja, S. Mittal, M. Zaman, “Diabetes Mellitus and Data Mining Techniques: A survey”, International Journal of Computer Science and Engineering, Vol. 7, Issue. 01, pp. 856-862, 2019.
[7] V. Mishra, C. Samuel, S.K. Sharma, “Use of Machine Learning to Predict the Onset of Diabetes”, International Journal of Recent advances in Mechanical Engineering, Vol. 4, Issue 2, pp. 9-14 , 2015.
[8] N.A. Farooqui, Ritika, A. Tyagi, “Prediction Model for Diabetes Mellitus Using Machine Learning Techniques”, International Journal of Computer Science and Engineering, Vol. 6, Issue. 3, pp. 292-296, 2018.
[9] A. Vaghela, G. S. Pandit, “A Fusion Approach for Prediction of Diabetes sing machine learning Techniques”, International Research Journal of Engineering and Technology, Vol. 8, Issue 01, pp. 808-813 , 2021.
[10] R. Manimaran, M. Vanitha, “Prediction of Diabetes Disease Using Classification Data Mining Techniques”, International Journal of Engineering and Technology, Vol 9, Issue 5, pp. 3610-3614 , 2017.