[1] Clustering with Euclidean Data

dpmeans()

DP-Means Clustering

gmm()

Finite Gaussian Mixture Model

gmm03F()

Ensemble of Gaussian Mixtures with Random Projection

gmm11R()

Regularized GMM by Ruan et al. (2011)

gmm16G()

Weighted GMM by Gebru et al. (2016)

kmeans()

K-Means Clustering

kmeans18B()

K-Means Clustering with Lightweight Coreset

kmeanspp()

K-Means++ Clustering

sc05Z()

Spectral Clustering by Zelnik-Manor and Perona (2005)

sc09G()

Spectral Clustering by Gu and Wang (2009)

sc10Z()

Spectral Clustering by Zhang et al. (2010)

sc11Y()

Spectral Clustering by Yang et al. (2011)

sc12L()

Spectral Clustering by Li and Guo (2012)

scNJW()

Spectral Clustering by Ng, Jordan, and Weiss (2002)

scSM()

Spectral Clustering by Shi and Malik (2000)

scUL()

Spectral Clustering with Unnormalized Laplacian

[2] Clustering with Functional Data

funhclust()

Functional Hierarchical Clustering

funkmeans03A()

Functional K-Means Clustering by Abraham et al. (2003)

[3] Clustering with Spherical Data

gskmeans()

Geodesic Spherical K-Means

spkmeans()

Spherical K-Means Clustering

[4] Clustering with Empirical Distributions

ephclust()

Hierarchical Agglomerative Clustering for Empirical Distributions

[5] Subspace Clustering

EKSS()

Ensembles of K-Subspaces

LRR()

Low-Rank Representation

LRSC()

Low-Rank Subspace Clustering

LSR()

Least Squares Regression

MSM()

Bayesian Mixture of Subspaces of Different Dimensions

SSC()

Sparse Subspace Clustering

SSQP()

Subspace Segmentation via Quadratic Programming

predict(<MSM>)

S3 method to predict class label of new data with 'MSM' object

[6] Measures : Clustering Validity/Quality Index

quality.CH()

(+) CH index

quality.sil()

(+) Silhouette Index

[7] Measures : Comparing Two Clusterings

compare.adjrand()

(+) Adjusted Rand Index

compare.rand()

(+) Rand Index

[8] Learning with Multiple Clusterings

pcm()

Compute Pairwise Co-occurrence Matrix

psm()

Compute Posterior Similarity Matrix

[9] Data : Loaded and Generators

gen3S()

Generate from Three 5-dimensional Subspaces in 200-dimensional space.

genDONUTS()

Generate Nested Donuts

genLP()

Generate Line and Plane Example with Fixed Number of Components

genSMILEY()

Generate SMILEY Data

household

Load 'household' data