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# Pima Indian Diabetes Prediction

**[HEARTBEAT](https://daily.dev/sources/hrb)** · 9 min read · 1 upvotes · 0 comments

## Summary

This project analyzes medical factors to predict whether a patient has diabetes or not. Factors such as glucose level, number of pregnancies, skin thickness, insulin level, and BMI are found to be indicators of diabetes risk. Classification models, including logistic regression, random forest, and SVM, are used to predict diabetes with logistic regression achieving the highest accuracy.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://heartbeat.comet.ml/pima-indian-diabetes-prediction-6ea1770902df>

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Tags: [#machine-learning](https://daily.dev/tags/machine-learning), [#data-science](https://daily.dev/tags/data-science), [#data-analysis](https://daily.dev/tags/data-analysis), [#classification](https://daily.dev/tags/classification), [#data-visualization](https://daily.dev/tags/data-visualization), [#logistic-regression](https://daily.dev/tags/logistic-regression), [#random-forest](https://daily.dev/tags/random-forest)

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