Diabetes Prediction using Machine Learning

Authors

  • Saniya Faraz Amity University Uttar Pradesh, Lucknow
  • Dr. Pawan Singh Amity School of Engineering and Technology, Amity University Uttar Pradesh, LucknowCampus, India

DOI:

https://doi.org/10.54060/jase.v2i2.13

Keywords:

Diabetes mellitus, Diabetes prediction, Machine Learning, Python, Support Vector Machine

Abstract

Machine Learning is a type of AI (also known as Artificial Intelligence) that makes the pc or computer act like individuals and learn more as they experience additional information from their client or user. So here in this report we got basic introduction about machine learning like actually what is it, what is its use, how it works and many more things. Thereafter, we discussed about the python the language, which is used for making pro-ject, important libraries such as pandas and numPy which is being is used for this partic-ular project and we have also discussed about Support Vector machine which has been used as classifier. We have also talked about the linear and non-linear svm that is used to check the accuracy of the predictive system. For the implementation we have started with importing the dependencies numpy smp and pandas pd and for the analysis we have taken a csv Pima Indian diabetes dataset after that we have trained the model with the help of support vector classifier. For the model evaluation we have checked the accuracy of the training data and test data. Numerous people suffer from diabetes mellitus, one of the most serious diseases. Age, obesity, inactivity, genetic diabetes, a poor diet, high blood pressure, and other factors can all contribute to diabetes mellitus. Diabetes in-creases a person's risk of developing various illnesses, including heart disease, renal dis-ease, stroke, vision problems, nerve damage, etc. So, here we will be building a system that can predict whether a person has diabetes or not with the help of Machine Learning.

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Published

2022-11-25

How to Cite

[1]
S. Faraz and P. Singh, “Diabetes Prediction using Machine Learning”, J. Appl. Sci. Educ., vol. 2, no. 2, pp. 1–12, Nov. 2022.

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Section

Research Article