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Heart Disease Classification Learning Model Project from Zero to Mastery Academy Machine Learning Course

Predicting heart disease using ML

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

1. Problem definition

In a statement,

Given clinical parameters about a patient, can we predict whether or not they have heart disease?

2. Data

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