Developing a machine learning model that can predict whether people have diabetes when their characteristics are specified.
The dataset is part of the large dataset held at the National Institutes of Diabetes-Digestive-Kidney Diseases in the USA. Data used for diabetes research on Pima Indian women aged 21 and over living in Phoenix, the 5th largest city of the State of Arizona in the USA. It consists of 768 observations and 8 numerical independent variables. The target variable is specified as "outcome"; 1 indicates positive diabetes test result, 0 indicates negative.
Pregnancies: Number of pregnancies Glucose: Glucose. BloodPressure: Blood pressure. SkinThickness: Skin Thickness Insulin: Insulin. BMI: Body mass index. DiabetesPedigreeFunction: A function that calculates our probability of having diabetes based on our ancestry. Age: Age (years) Outcome: Information whether the person has diabetes or not. Have the disease (1) or not (0))
- Exploratory Data Analysis
- Data Preprocessing
- Model & Prediction
- Model Evaluation
- Model Validation: Holdout
- Model Validation: 10-Fold Cross Validation
- Prediction for A New Observation