nutrient

The data set contains the measurements of nutrients in several types
 of meat, fish and fowl.

datasets

The main function kcca implements a general framework for
k-centroids cluster analysis supporting arbitrary distance
measures and centroid computation. Further cluster methods
include hard competitive learning, neural gas, and QT
clustering. There are numerous visualization methods for
cluster results (neighborhood graphs, convex cluster hulls,
barcharts of centroids, ...), and bootstrap methods for the
analysis of cluster stability.

Friedrich Leisch

flexclust

Flexible Cluster Algorithms

Evgenia Dimitriadou

nutrient function

A data frame with 27 observations on the following 5 variables.<dl class="dl-horizontal">
 <dt>energy:</dt><dd>food energy (calories)</dd>
 <dt>protein:</dt><dd>protein (grams)</dd>
 <dt>fat:</dt><dd>fat (grams)</dd>
 <dt>calcium:</dt><dd>calcium (milli grams)</dd>
 <dt>iron:</dt><dd>iron (milli grams)</dd>
 </dl>

Format

Nutrients in Meat, Fish and Fowl — nutrient

A data frame with 27 observations on the following 5 variables.<dl class='dl-horizontal'>
 <dt>energy:</dt><dd>food energy (calories)</dd>
 <dt>protein:</dt><dd>protein (grams)</dd>
 <dt>fat:</dt><dd>fat (grams)</dd>
 <dt>calcium:</dt><dd>calcium (milli grams)</dd>
 <dt>iron:</dt><dd>iron (milli grams)</dd>
 </dl>

nutrient: Nutrients in Meat, Fish and Fowl

Description

Usage

Arguments

Format

References