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flexclust (version 1.1-0)

Flexible Cluster Algorithms

Description

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.

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Version

Install

install.packages('flexclust')

Monthly Downloads

11,637

Version

1.1-0

License

GPL-2

Maintainer

Friedrich Leisch

Last Published

February 28th, 2025

Functions in flexclust (1.1-0)

barplot-methods

Barplot/chart Methods in Package `flexclust'

German Parliament Election Data

Compute pairwise distances between two data sets

Distance and Centroid Computation

Milk of Mammals

Stochastic QT Clustering

Plot a Random Tour

Achievement Test Scores for New Haven Schools

Run Flexclust Algorithms Repeatedly

Dentition of Mammals

Bootstrap Flexclust Algorithms

predict-methods

Predict Cluster Membership

Get Centroids from KCCA Object

Convex Clustering

Methods for Function plot in Package `flexclust'

Get Information on Fitted Flexclust Objects

Add Arrows for Projeted Axes to a Plot

K-Centroids Cluster Analysis

flexclustControl-class

Classes "flexclustControl" and "cclustControl"

Artificial Example with 4 Gaussians

Flexclust Color Palettes

Methods for Function image in Package `flexclust'

Methods for Function pairs in Package `flexclust'

Nutrients in Meat, Fish and Fowl

Convert S3 Partition Objects to KCCA

Cluster Similarity Matrix

Birth and Death Rates