This model use K-neighbour, Naive bayes etc, classification models to predict the presences of dibetes in a patience.
The data set that is used in the model is take from Kraggle which is under the name of "Pima Indians Diabetes Database" which is provided here itself
The data set used in the model has 768 entries and 9 variables namely Pregnancies, Glucose, Blood Pressure, Skin Thickness, Insuline, BMI(Body Mass Index), Diabetes Pedigree Function, Age, Outcome and the enties doesn't contain any null values.
Discricption of the Variables:
- Pregnancies: It is no of pregnancies the patient has had which is in terms of numerical values.(Type: float)
- Glucose: It is blood glucose levels (Type: float).
- Blood Pressure: Its Diastolic Blood pressure (Type: float).
- Skin Thickness: Triceps skin fold thickness in mm (Type: float).
- Insulin: It’s the insulin levels in the patient blood (Type: float).
- BMI: Body Mass Index i.e., (weight in kg/(height in m)^2) (Type: float).
- Diabetes Pedigree Function (Type: float).
- Age: In years (Type: int).
- Outcome: In 0 or 1 where 1 represents presents of diabetes and 0 shows there is no diabetes (Type: 0 or 1).