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ML-Diabetes-Classification

Dataset Overview

The Pima are a group of Native Americans living in Arizona. A genetic predisposition allowed this group to survive normally to a diet poor of carbohydrates for years. In the recent years, because of a sudden shift from traditional agricultural crops to processed foods, together with a decline in physical activity, made them develop the highest prevalence of type 2 diabetes and for this reason, they have been subject of many studies.

Dataset The dataset includes data from 768 women with 8 characteristics, in particular:

Number of times pregnant

Plasma glucose concentration a 2 hours in an oral glucose tolerance test

Diastolic blood pressure (mm Hg)

Triceps skinfold thickness (mm)

2-Hour serum insulin (mu U/ml)

Body mass index (weight in kg/(height in m)^2)

Diabetes pedigree function

Age (years)

The last column of the dataset indicates if the person has been diagnosed with diabetes (1) or not (0)

The type of dataset and problem is a classic supervised binary classification. Given a number of elements all with certain characteristics (features), we want to build a machine learning model to identify people affected by type 2 diabetes.

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