# Probabilistic and Possibilistic Cluster Analysis

## Documentation for package ‘ppclust’ version 1.1.0

- DESCRIPTION file.
- User guides, package vignettes and other documentation.
- Package NEWS.

## Help Pages

ppclust-package | Probabilistic and Possibilistic Cluster Analysis
as.ppclust | Convert object to 'ppclust' class
comp.omega | Compute the possibilistic penalty argument for PCM
crisp | Crisp the fuzzy membership degrees
ekm | K-Means Clustering Using Different Seeding Techniques
fcm | Fuzzy C-Means Clustering
fcm2 | Type-2 Fuzzy C-Means Clustering
fpcm | Fuzzy Possibilistic C-Means Clustering
fpppcm | Fuzzy Possibilistic Product Partition C-Means Clustering
get.dmetrics | List the names of distance metrics
gg | Gath-Geva Clustering Algorithm
gk | Gustafson-Kessel Clustering
gkpfcm | Gustafson-Kessel Clustering Using PFCM
hcm | Hard C-Means Clustering
is.ppclust | Check the class of object for 'ppclust'
mfpcm | Modified Fuzzy Possibilistic C-Means Clustering
pca | Possibilistic Clustering Algorithm
pcm | Possibilistic C-Means Clustering
pcmr | Possibilistic C-Means Clustering with Repulsion
pfcm | Possibilistic Fuzzy C-Means Clustering Algorithm
plotcluster | Plot Clustering Results
ppclust2 | Convert 'ppclust' objects to the other types of cluster objects
summary.ppclust | Summarize the clustering results
upfc | Unsupervised Possibilistic Fuzzy C-Means Clustering Algorithm
x12 | Synthetic data set of two variables
x16 | Synthetic data set of two variables forming two clusters