Package index • cluster

All functions

agnes(): Agglomerative Nesting (Hierarchical Clustering)
agnes.object: Agglomerative Nesting (AGNES) Object
agriculture: European Union Agricultural Workforces
animals: Attributes of Animals
bannerplot(): Plot Banner (of Hierarchical Clustering)
chorSub: Subset of C-horizon of Kola Data
clara(): Clustering Large Applications
clara.object: Clustering Large Applications (CLARA) Object
clusGap() maxSE() print(<clusGap>) plot(<clusGap>): Gap Statistic for Estimating the Number of Clusters
clusplot(<default>): Bivariate Cluster Plot (clusplot) Default Method
clusplot(): Bivariate Cluster Plot (of a Partitioning Object)
coefHier() coef.hclust() coef(<hclust>) coef(<twins>): Agglomerative / Divisive Coefficient for 'hclust' Objects
daisy(): Dissimilarity Matrix Calculation
diana(): DIvisive ANAlysis Clustering
dissimilarity.object: Dissimilarity Matrix Object
ellipsoidhull() print(<ellipsoid>): Compute the Ellipsoid Hull or Spanning Ellipsoid of a Point Set
fanny(): Fuzzy Analysis Clustering
fanny.object: Fuzzy Analysis (FANNY) Object
flower: Flower Characteristics
lower.to.upper.tri.inds() upper.to.lower.tri.inds(): Permute Indices for Triangular Matrices
medoids(): Compute pam-consistent Medoids from Clustering
mona(): MONothetic Analysis Clustering of Binary Variables
mona.object: Monothetic Analysis (MONA) Object
pam(): Partitioning Around Medoids
pam.object: Partitioning Around Medoids (PAM) Object
partition partition.object: Partitioning Object
plantTraits: Plant Species Traits Data
plot(<agnes>): Plots of an Agglomerative Hierarchical Clustering
plot(<diana>): Plots of a Divisive Hierarchical Clustering
plot(<mona>): Banner of Monothetic Divisive Hierarchical Clusterings
plot(<partition>): Plot of a Partition of the Data Set
pltree(): Plot Clustering Tree of a Hierarchical Clustering
pluton: Isotopic Composition Plutonium Batches
predict.ellipsoid() predict(<ellipsoid>) ellipsoidPoints(): Predict Method for Ellipsoid Objects
print(<agnes>): Print Method for AGNES Objects
print(<clara>): Print Method for CLARA Objects
print(<diana>): Print Method for DIANA Objects
print(<dissimilarity>) summary(<dissimilarity>) print(<summary.dissimilarity>): Print and Summary Methods for Dissimilarity Objects
print(<fanny>) summary(<fanny>) print(<summary.fanny>): Print and Summary Methods for FANNY Objects
print(<mona>): Print Method for MONA Objects
print(<pam>): Print Method for PAM Objects
ruspini: Ruspini Data
silhouette() sortSilhouette() summary(<silhouette>) plot(<silhouette>): Compute or Extract Silhouette Information from Clustering
sizeDiss(): Sample Size of Dissimilarity Like Object
summary(<agnes>) print(<summary.agnes>): Summary Method for 'agnes' Objects
summary(<clara>) print(<summary.clara>): Summary Method for 'clara' Objects
summary(<diana>) print(<summary.diana>): Summary Method for 'diana' Objects
summary(<mona>) print(<summary.mona>): Summary Method for 'mona' Objects
summary(<pam>) print(<summary.pam>): Summary Method for PAM Objects
twins.object twins: Hierarchical Clustering Object
volume(): Compute the Volume (of an Ellipsoid)
votes.repub: Votes for Republican Candidate in Presidential Elections
xclara: Bivariate Data Set with 3 Clusters