Flask Web Application
Support Vector Machine Model
It is a web application in FLask that predicts whether the person is Diabetic or Not Diabetic based on the Recorded Data. For prediction Supervised Machine Learning Model is propose using Python. Dataset is Standardised before processing to obtain accurate results. Here, Support vector Machine (SVM) Model is used for Binary Classification problem. Model is trained for 70% of dataset and tested for 30% of dataset. Accuracy Score obtained for the test dataset was 78.78%.
About DataSet This dataset is originally from the National Institute of Diabetes and Digestive and Kidney Diseases. The objective of the dataset is to diagnostically predict whether or not a patient has diabetes, based on certain diagnostic measurements included in the dataset. Several constraints were placed on the selection of these instances from a larger database. In particular, all patients here are females at least 21 years old of Pima Indian heritage.
Get Dataset: Click Here.
This model can be used to predict whether a women 🙍♀️ is Diabetic or Not by just entering the required input. i.e., Pregnancies, Glucose, Blood Pressure, Skin thickness, Insulin, BMI, Diabetes Pedigree Function, and Age.
- Pregnancies : Number of times pregnant
- Glucose : Plasma glucose concentration a 2 hours in an oral glucose tolerance test.
- Blood Pressure : Diastolic blood pressure (mm Hg).
- Skin Thickness : Triceps skin fold thickness (mm).
- Insulin : 2-Hour serum insulin (mu U/ml).
- BMI : Body mass index (weight in kg/(height in m)^2).
- Diabetes Pedigree Function : Likelihood of diabetes based on family history.
- Age : Age in years.
- Clone the project
- Run pip install -r requirements.txt
- Add input data for which prediction is to be done.
- Run