heartdisease

Data for 303 patients tested for heart disease

datasets

Create, visualize, and test fast-and-frugal decision trees (FFTs). FFTs are very simple decision trees for
binary classification problems. FFTs can be preferable to more complex algorithms because they are easy to communicate, require very little information, and are
robust against overfitting.

Nathaniel Phillips

FFTrees

Generate, Visualise, and Evaluate Fast-and-Frugal Decision Trees

Hansjoerg Neth

Jan Woike

Wolfgang Gaissmaer

heartdisease function

A data frame containing 303 rows and 14 columns<dl class="dl-horizontal">
 <dt>age</dt><dd>Age</dd>
 <dt>sex</dt><dd>Sex, 1 = male, 0 = female</dd>
 <dt>cp</dt><dd>Chest pain type: ta = typical angina, aa = atypical angina, np = non-anginal pain, a = asymptomatic</dd>
 <dt>trestbps</dt><dd>Resting blood pressure (in mm Hg on admission to the hospital)</dd>
 <dt>chol</dt><dd>Serum cholestoral in mg/dl</dd>
 <dt>fbs</dt><dd>Fasting blood sugar &gt; 120 mg/dl: 1 = true, 0 = false</dd>
 <dt>restecg</dt><dd>Resting electrocardiographic results. "normal" = normal, "abnormal" = having ST-T wave abnormality (T wave inversions and/or ST elevation or depression of &gt; 0.05 mV), "hypertrophy" = showing probable or definite left ventricular hypertrophy by Estes' criteria.</dd>
 <dt>thalach</dt><dd>Maximum heart rate achieved</dd>
 <dt>exang</dt><dd>Exercise induced angina: 1 = yes, 0 = no</dd>
 <dt>oldpeak</dt><dd>ST depression induced by exercise relative to rest</dd>
 <dt>slope</dt><dd>The slope of the peak exercise ST segment.</dd>
 <dt>ca</dt><dd>Number of major vessels (0-3) colored by flourosopy</dd>
 <dt>thal</dt><dd>"normal" = normal, "fd" = fixed defect, "rd" = reversable defect</dd>
 <dt>diagnosis</dt><dd>1 = Heart disease, 0 = No Heart disease</dd>...
</dl>

Format

Heart disease dataset — heartdisease

Heart disease dataset

heartdisease: Heart disease dataset

Description

Usage

Arguments

Format