Heart Disease Classification Learning Model Project from Zero to Mastery Academy Machine Learning Course
This notebook looks into using various Python-based ML and data science libraries in an attempt to build a ML model capable of predicting whether or not somebody has heart disease based on their medical attributes.
Approach:
- Problem definition
- Data
- Evaluation
- Features
- Modelling
- Experimentation
In a statement,
Given clinical parameters about a patient, can we predict whether or not they have heart disease?
This data set dates from 1988 and consists of four databases: Cleveland, Hungary, Switzerland, and Long Beach V. It contains 76 attributes, including the predicted attribute, but all published experiments refer to using a subset of 14 of them. The "target" field refers to the presence of heart disease in the patient. It is integer valued 0 = no disease and 1 = disease.
The original data came from the Cleavland data grom the UCI Machine Learning Repository. https://archive.ics.uci.edu/ml/datasets/heart+Disease