/Pima-Indians-Diabetes-DataSet-UCI

This problem is comprised of 768 observations of medical details for Pima indians patents. In this repository, we study this dataset by using K nearest neighbour classification method.

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Pima-Indians-Diabetes-DataSet-UCI

The test problem we will use in this repository is the Pima Indians Diabetes problem taken from Machine Learning Repository UCI: https://archive.ics.uci.edu/ml/datasets/pima+indians+diabetes

This problem is comprised of 768 observations of medical details for Pima indians patents. The records describe instantaneous measurements taken from the patient such as their age, the number of times pregnant and blood workup. All patients are women aged 21 or older. All attributes are numeric, and their units vary from attribute to attribute.

Each record has a class value that indicates whether the patient suffered an onset of diabetes within 5 years of when the measurements were taken (1) or not (0).

This is a standard dataset that has been studied a lot in machine learning literature. A good prediction accuracy is 70%-76%.

In this repository, we study this dataset by using K nearest neighbour classification method