Prediction-of-Diabetes-Using-Machine-Learning-in-Python

Dataset:

https://archive.ics.uci.edu/ml/datasets/Early+stage+diabetes+risk+prediction+dataset.

Libraries:

Pandas Matplotlib Seaborn Sklearn

Conclusion

In this Project, we have discussed the seriousness of diabetes disease and its emergence to detect it in early-stage for controlling the death rates globally. We have demonstrated the exploratory data analysis by analyzing different features in the dataset. Further, we have performed necessary data preprocessing and applied logistic regression and random forest machine learning algorithms and compared their performance, and found that random forest performed better in terms of accuracy, precision, f1-score, and ROC values. Further, we have analyzed important features contributing to the prediction of diabetes cases.