The Dataset and Exploratory Data Analysis
Explore the Cleveland heart disease dataset by loading and summarizing key attributes such as age, sex, cholesterol, and thalassemia status. Learn to visualize data distributions and relationships to inform decision tree algorithms for predictive modeling.
We'll cover the following...
Let's move on and work with another famous dataset on heart disease in Cleveland. This original and full dataset is a part of the UCI machine learning repository and contains four databases: Cleveland, Hungary, Switzerland, and the VA Long Beach. This dataset was donated in 1988 to the public. The original database contains 76 attributes, but all published experiments by machine learning researchers refer to using a subset of 14 of them.
The dataset
In particular, the Cleveland database is the only one widely used by machine learning researchers. In the original database, the goal field refers to a patient’s presence of heart disease. It’s an integer value from 0 (no presence) to 4. Experiments with the Cleveland database have concentrated on simply attempting to distinguish presence (values 1, 2, 3, and 4) from absence (value 0). Information on the 14 attributes that we’re going to use is provided below:
age: Yearssex...