/Arrhythmia-Classification-Using-Machine-Learning

This project classifies arrhythmia using the UCI dataset with 279 features and 452 examples. It predicts if a person has arrhythmia and classifies it into 12 types. The notebook includes data preprocessing, feature selection, and machine learning model implementation for accurate medical data prediction.

Primary LanguageJupyter Notebook

Stargazers