find_algorithm

kmean_assignment_c

kmean_assignment_r

algorithm

<p><code>find_algorithm()</code> returns a function to assign k-means cluster.
<code>kmean_assignment_r()</code> wraps around <code><a rd-options="=kmeans" href="/link/kmeans()?package=partition&version=0.1.0&to=%3Dkmeans" data-mini-rdoc="=kmeans::kmeans()">kmeans()</a></code> to pull the correct
assignments.</p>

internal

A fast and flexible framework for agglomerative partitioning. 'partition' uses an approach
called Direct-Measure-Reduce to create new variables that maintain the
user-specified minimum level of information. Each reduced variable is also interpretable:
the original variables map to one and only one variable in the reduced data set. 'partition'
is flexible, as well: how variables are selected to reduce, how information loss is measured,
and the way data is reduced can all be customized.

Malcolm Barrett

partition

Agglomerative Partitioning Framework for Dimension Reduction

Joshua Millstein

find_algorithm function

<p><code>find_algorithm()</code> returns a function to assign k-means cluster.
<code>kmean_assignment_r()</code> wraps around <code><a rd-options='=kmeans' href='kmeans()'>kmeans()</a></code> to pull the correct
assignments.</p>

Which kmeans algorithm to use? — find_algorithm

Which kmeans algorithm to use?

find_algorithm: Which kmeans algorithm to use?

Description

Usage

Arguments

Value