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 |