National Institute of Diabetes and Digestive and Kidney Diseases research creates knowledge about and treatments for the most chronic, costly, and consequential diseases. The dataset used in this project is originally from NIDDK. The objective is to predict whether or not a patient has diabetes, based on certain diagnostic measurements included in the dataset. Build a model to accurately predict whether the patients in the dataset have diabetes or not.
The datasets consists of several medical predictor variables and one target variable (Outcome). Predictor variables includes the number of pregnancies the patient has had, Glucose,Blood Pressure, Skin Thickness, Insulin, their BMI, DiabetesPedigreeFunction, Age, Outcome(0,1).
I have performed the following steps to predict whether or not a patient has diabetes:
(i) Data Wrangling (ii) Exploratory Data Analysis (iii) Creation of different classifiers and choosing the best one among these algorithms (iv) Model validation to overcome the overfitting problem. (v) Evaluation of model (vi) Creating a dashboard with charts in Tableau.