.defaultScalarArguments | Define the default arguments |
.defaultScalarArguments-method | Agglomerative nesting |
.defaultScalarArguments-method | Clustering Large Applications |
.defaultScalarArguments-method | Divisive analysis clustering |
.defaultScalarArguments-method | Hierarchical clustering |
.defaultScalarArguments-method | The HierarchicalParam class |
.defaultScalarArguments-method | Partitioning around medoids |
.defaultScalarArguments-method | Define the default arguments |
.extractScalarArguments | Define the default arguments |
.showScalarArguments | Define the default arguments |
AffinityParam | Affinity propogation |
AffinityParam-class | Affinity propogation |
AgnesParam | Agglomerative nesting |
AgnesParam-class | Agglomerative nesting |
approxSilhouette | Approximate silhouette width |
BlusterParam-class | The BlusterParam class |
bootstrapStability | Assess cluster stability by bootstrapping |
centers | The FixedNumberParam class |
centers-method | The FixedNumberParam class |
centers<- | The FixedNumberParam class |
centers<--method | The FixedNumberParam class |
ClaraParam | Clustering Large Applications |
ClaraParam-class | Clustering Large Applications |
clusterRMSD | Compute the RMSD per cluster |
clusterRows | Cluster rows of a matrix |
clusterRows-method | Affinity propogation |
clusterRows-method | Agglomerative nesting |
clusterRows-method | Clustering Large Applications |
clusterRows-method | Density-based clustering with DBSCAN |
clusterRows-method | Divisive analysis clustering |
clusterRows-method | Hierarchical clustering |
clusterRows-method | K-means clustering |
clusterRows-method | Mini-batch k-means clustering |
clusterRows-method | Graph-based clustering |
clusterRows-method | Partitioning around medoids |
clusterRows-method | Clustering with self-organizing maps |
clusterRows-method | Two step clustering with vector quantization |
clusterSweep | Clustering parameter sweeps |
compareClusterings | Compare pairs of clusterings |
DbscanParam | Density-based clustering with DBSCAN |
DbscanParam-class | Density-based clustering with DBSCAN |
DianaParam | Divisive analysis clustering |
DianaParam-class | Divisive analysis clustering |
FixedNumberParam-class | The FixedNumberParam class |
HclustParam | Hierarchical clustering |
HclustParam-class | Hierarchical clustering |
HierarchicalParam-class | The HierarchicalParam class |
KmeansParam | K-means clustering |
KmeansParam-class | K-means clustering |
KNNGraphParam | Graph-based clustering |
KNNGraphParam-class | Graph-based clustering |
linkClusters | Create a graph between different clusterings |
linkClustersMatrix | Create a graph between different clusterings |
makeKNNGraph | Build a nearest-neighbor graph |
makeSNNGraph | Build a nearest-neighbor graph |
MbkmeansParam | Mini-batch k-means clustering |
MbkmeansParam-class | Mini-batch k-means clustering |
mergeCommunities | Merge communities from graph-based clustering |
neighborPurity | Compute neighborhood purity |
neighborsToKNNGraph | Build a nearest-neighbor graph |
neighborsToSNNGraph | Build a nearest-neighbor graph |
nestedClusters | Map nested clusterings |
NNGraphParam | Graph-based clustering |
NNGraphParam-class | Graph-based clustering |
pairwiseModularity | Compute pairwise modularity |
pairwiseRand | Compute pairwise Rand indices |
PamParam | Partitioning around medoids |
PamParam-class | Partitioning around medoids |
show-method | Affinity propogation |
show-method | Agglomerative nesting |
show-method | The BlusterParam class |
show-method | Clustering Large Applications |
show-method | Density-based clustering with DBSCAN |
show-method | Divisive analysis clustering |
show-method | The FixedNumberParam class |
show-method | Hierarchical clustering |
show-method | The HierarchicalParam class |
show-method | K-means clustering |
show-method | Mini-batch k-means clustering |
show-method | Graph-based clustering |
show-method | Partitioning around medoids |
show-method | Clustering with self-organizing maps |
show-method | Two step clustering with vector quantization |
SNNGraphParam | Graph-based clustering |
SNNGraphParam-class | Graph-based clustering |
SomParam | Clustering with self-organizing maps |
SomParam-class | Clustering with self-organizing maps |
TwoStepParam | Two step clustering with vector quantization |
TwoStepParam-class | Two step clustering with vector quantization |
updateObject-method | Hierarchical clustering |
updateObject-method | K-means clustering |
[[-method | The BlusterParam class |
[[-method | Hierarchical clustering |
[[<--method | The BlusterParam class |