/KNN-on-Diabetes-Data-KAGGLE-

This project utilizes the KNN classification algorithm to predict the likelihood of a patient developing diabetes. Using data from the National Institute of Diabetes and Digestive and Kidney Diseases dataset to provide insights into diabetes risk assessment.

Primary LanguageJupyter Notebook

Diabetes Prediction with KNN Classification

Objective

The primary objective of this study is to employ the KNN classification algorithm to determine the susceptibility of a patient to developing diabetes. Using various medical measurements sourced from the National Institute of Diabetes and Digestive and Kidney Diseases dataset, the project aims to provide valuable insights into predictive modeling for diabetes risk assessment.

Content

  1. Details on Data

    • Overview of the National Institute of Diabetes and Digestive and Kidney Diseases dataset, including key medical measurements.

  2. Data Visualization

    • Visual representation of the dataset to facilitate a better understanding of the underlying patterns and relationships.

  3. Building the Model

    • Implementation details of the KNN classification algorithm for diabetes prediction.

  4. Testing the Model Accuracy

    • Assessment of the model's performance with a focus on accuracy metrics, providing insights into its reliability and predictive capabilities.