Optimization of Diabetes Training DATA using Machine Learning Algorithms

Authors

  • M Samba Siva Rao Dept. Of CSE, Usha Rama college of engineering and Technology, Tealaprolu, JNTUK, INDIA
  • M Yaswanth Dept. of CSE, PVP Siddhartha college of engineering, Vijayawada, JNTUK, INDIA
  • K Raghavendra swamy Dept. Of IT, BDPS IT Training and Data Processing Solutions, Vijayawada, INDIA

DOI:

https://doi.org/10.26438/ijcse/v6i2.283286

Keywords:

python, Machine Learning, Pandas, Seaborn, Sklearn, Diabetes

Abstract

Diabetes Disease is one of most common disease in our modern life, and in this paper we are using different Super vised and un Super vised Machine learning Algorithms to Analyze and optimize accuracy of Training Data and classify , diagnosis , accuracy of Algorithms with python Machine learning modules like pandas, sklearn, Seaborn.

References

[1] Sikit learn cook Book

[2] https://www.kdnuggets.com/2015/11/seven-steps-machine-learning- python.html

[3] Understanding Machine Learning: From Theory to Algorithms By Shai Shalev-Shwartz and Shai Ben-David

[4] Machine Learning Yearning By Andrew Ng

[5] Introduction to Machine Learning with Python: A Guide for Data Scientists Book by Andrea C. Müller

[6] Machine Learning in Python: Essential Techniques for Predictive Analysis

[7] https://towardsdatascience.com/machine-learning-for-diabets

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Published

2025-11-12
CITATION
DOI: 10.26438/ijcse/v6i2.283286
Published: 2025-11-12

How to Cite

[1]
M. Samba Siva Rao, M. Yaswanth, and K. Raghavendra swamy, “Optimization of Diabetes Training DATA using Machine Learning Algorithms”, Int. J. Comp. Sci. Eng., vol. 6, no. 2, pp. 283–286, Nov. 2025.

Issue

Vol. 6 No. 2 (2018): IJCSE February Edition

Section

Research Article

License

Creative Commons License

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