heart

A mixed variable dataset containing 14 variables of 297 patients for
their heart disease diagnosis.

datasets

Algorithms of distance-based k-medoids clustering: simple and fast
k-medoids, ranked k-medoids, and increasing number of clusters in k-medoids.
Calculate distances for mixed variable data such as Gower, Podani, Wishart,
Huang, Harikumar-PV, and Ahmad-Dey. Cluster validation applies internal and
relative criteria. The internal criteria includes silhouette index and shadow
values. The relative criterium applies bootstrap procedure producing a heatmap
with a flexible reordering matrix algorithm such as complete, ward, or average
linkages. The cluster result can be plotted in a marked barplot or pca biplot.

Weksi Budiaji

kmed

Distance-Based k-Medoids

heart function

A data frame with 297 rows and 14 variables:<dl>
 <dt>age</dt>
<dd>Age in years (numerical).</dd> <dt>sex</dt>
<dd>Sex: 1 = male, 0 = female (logical).</dd> <dt>cp</dt>
<dd>Four chest pain types: (1) typical angina, (2) atypical angina
 (3)non-anginal pain, (4) asymptomatic (categorical).</dd> <dt>trestbps</dt>
<dd>Resting blood pressure (in mm Hg on admission to
 the hospital) (numerical).</dd> <dt>chol</dt>
<dd>Serum cholestoral in mg/dl (numerical).</dd> <dt>fbs</dt>
<dd>Fasting blood sugar more than 120 mg/dl (logical).</dd> <dt>restecg</dt>
<dd>Resting electrocardiographic results: (0) normal,
 (1) having ST-T wave abnormality, (2) showing probable or definite
 left ventricular hypertrophy by Estes' criteria (categorical).</dd> <dt>thalach</dt>
<dd>Maximum heart rate achieved (numerical).</dd> <dt>exang</dt>
<dd>Exercise induced angina (logical).</dd> <dt>oldpeak</dt>
<dd>ST depression induced by exercise relative to
 rest (numerical).</dd> <dt>slope</dt>
<dd>The slope of the peak exercise ST segment: (1) upsloping,
 (2) flat, (3) downsloping (categorical).</dd> <dt>ca</dt>
<dd>Number of major vessels (0-3) colored by flourosopy (numerical).</dd> <dt>thal</dt>
<dd>(3) normal, (6) fixed defect, (7) reversable defect
 (categorical).</dd> <dt>class</dt>
<dd>Diagonosis of heart disease (4 classes). It can be 2 classes
 by setting 0 for 0 values and 1 for non-0 values.</dd>
</dl>

Format

Heart Disease data set — heart

A data frame with 297 rows and 14 variables:<dl>
 <dt>age</dt>
<dd>Age in years (numerical).</dd>

 <dt>sex</dt>
<dd>Sex: 1 = male, 0 = female (logical).</dd>

 <dt>cp</dt>
<dd>Four chest pain types: (1) typical angina, (2) atypical angina
 (3)non-anginal pain, (4) asymptomatic (categorical).</dd>

 <dt>trestbps</dt>
<dd>Resting blood pressure (in mm Hg on admission to
 the hospital) (numerical).</dd>

 <dt>chol</dt>
<dd>Serum cholestoral in mg/dl (numerical).</dd>

 <dt>fbs</dt>
<dd>Fasting blood sugar more than 120 mg/dl (logical).</dd>

 <dt>restecg</dt>
<dd>Resting electrocardiographic results: (0) normal,
 (1) having ST-T wave abnormality, (2) showing probable or definite
 left ventricular hypertrophy by Estes' criteria (categorical).</dd>

 <dt>thalach</dt>
<dd>Maximum heart rate achieved (numerical).</dd>

 <dt>exang</dt>
<dd>Exercise induced angina (logical).</dd>

 <dt>oldpeak</dt>
<dd>ST depression induced by exercise relative to
 rest (numerical).</dd>

 <dt>slope</dt>
<dd>The slope of the peak exercise ST segment: (1) upsloping,
 (2) flat, (3) downsloping (categorical).</dd>

 <dt>ca</dt>
<dd>Number of major vessels (0-3) colored by flourosopy (numerical).</dd>

 <dt>thal</dt>
<dd>(3) normal, (6) fixed defect, (7) reversable defect
 (categorical).</dd>

 <dt>class</dt>
<dd>Diagonosis of heart disease (4 classes). It can be 2 classes
 by setting 0 for 0 values and 1 for non-0 values.</dd>


</dl>

heart: Heart Disease data set

Description

Usage

Arguments

Format

References