countries

Socioeconomic data for the most populous countries.

datasets

Miscellaneous functions for classification and visualization,
e.g. regularized discriminant analysis, sknn() kernel-density naive Bayes,
an interface to 'svmlight' and stepclass() wrapper variable selection
for supervised classification, partimat() visualization of classification rules
and shardsplot() of cluster results as well as kmodes() clustering for categorical data,
corclust() variable clustering, variable extraction from different variable clustering models
and weight of evidence preprocessing.

Uwe Ligges

klaR

Classification and Visualization

countries function

A data frame with 42 observations on the following 7 variables.<dl>
 <dt>Country</dt>
<dd>name of the country.</dd> <dt>Popul</dt>
<dd>population.</dd> <dt>PopDens</dt>
<dd>population density.</dd> <dt>GDPpp</dt>
<dd>GDP per inhabitant.</dd> <dt>LifeEx</dt>
<dd>mean life expectation</dd> <dt>InfMor</dt>
<dd>infant mortality</dd> <dt>Illit</dt>
<dd>illiteracy rate</dd> 
</dl>

Format

Socioeconomic data for the most populous countries. — countries

A data frame with 42 observations on the following 7 variables.<dl>
 <dt>Country</dt>
<dd>name of the country.</dd>

 <dt>Popul</dt>
<dd>population.</dd>

 <dt>PopDens</dt>
<dd>population density.</dd>

 <dt>GDPpp</dt>
<dd>GDP per inhabitant.</dd>

 <dt>LifeEx</dt>
<dd>mean life expectation</dd>

 <dt>InfMor</dt>
<dd>infant mortality</dd>

 <dt>Illit</dt>
<dd>illiteracy rate</dd>

 
</dl>

countries: Socioeconomic data for the most populous countries.

Description

Usage

Arguments

Format

Examples