Diabetes Prediction using Random Forest Classifier.
Hello folks, this is my first project in Machine Learning Using Flask.
The project predicts whether a patient is diabetic or not using Random Forest Classifier which builds multiple decision trees and merges them together to get a more accurate and stable result.
Training Accuracy : 0.9870
Testing Accuracy : 0.7100
The dataset was obtained from Kaggle : https://www.kaggle.com/uciml/pima-indians-diabetes-database
A form was designed to take the inputs from the user which were passed as a parameter to our predict function which uses Random Forest Classifier (Supervised Learning) to classify the patients as diabetic or non-diabetic.The form was designed in HTML/CSS.
Following were the inputs taken from the end user :
- Number of Pregnancies
- Glucose Level
- Blood Pressure Level
- Skin Thickness
- Insulin
- BMI
GUI for end user interaction was developed using Flask Framework and HTML/CSS in the Frontend and Python in the backend for developing the controller files and model files.
Results:
Diabetic if the predicted value is ‘1’.
Non-Diabetic if the predicted value is ‘0’.
Inorder to execute it :
1] Write the following command in cmd : controller.py
2] It will start the server and provide an url i.e. "http://127.0.0.1:5000" copy it in browser and see the magic !
At last, it was totally new experience for me at first sight I find it difficult but with the help of my friends, I was able to complete this so Thanks everyone. Hope you like it as well.