DATAMATICS TEAM - 22

Inspiration

To predict diabetes

What it does

This machine learning project helps to find out whether the patient has diabetes or not at the earlier stage without spending lot of money to test . At the same time it shows the accurate possibility.

How we built it

We built using
1) Logistic Regression 2) Support Vector Machine 3) KNN 4) Random Forest Classifier 5) Naivye Bayes 6) Gradient Boosting

Challenges we ran into

To come up with the perfect dataset and the most accurate output prediction is a challenging task to be performed.

Accomplishments that we're proud of

To overcome the challenge and we came up with the most accurate using Random Forest Classifier.

What we learned

1) Accuracy Score 2) ROC AUC Curve 3) Cross Validation 4) Confusion Matrix

What's next for DIABETES PREDICTION

To find out whether the patient has diabetes or not at the earlier stage.

Built With

• jupyter
• python