| HclustParam-class | R Documentation |
Run the base hclust function on a distance matrix within clusterRows.
HclustParam(
clust.fun = NULL,
metric = NULL,
dist.fun = NULL,
method = NULL,
cut.fun = NULL,
cut.dynamic = FALSE,
cut.height = NULL,
cut.number = NULL,
cut.params = list(),
...
)
## S4 method for signature 'ANY,HclustParam'
clusterRows(x, BLUSPARAM, full = FALSE)
clust.fun |
Function specifying the function to use to do the clustering.
The function should apply a hierarchical clustering algorithm and take a data matrix as input.
If |
metric |
String specifying the distance metric to use in |
dist.fun |
Function specifying the function to use to compute the distance matrix.
The function should accept a data matrix and a |
method |
String specifying the agglomeration method to use in |
cut.fun |
Function specifying the method to use to cut the dendrogram.
The first argument of this function should be the output of |
cut.dynamic |
Logical scalar indicating whether a dynamic tree cut should be performed using the dynamicTreeCut package. |
cut.height, cut.number |
Deprecated, use |
cut.params |
Further arguments to pass to |
... |
Deprecated, more arguments to add to |
x |
A numeric matrix-like object where rows represent observations and columns represent variables. |
BLUSPARAM |
A HclustParam object. |
full |
Logical scalar indicating whether the hierarchical clustering statistics should be returned. |
To modify an existing HclustParam object x,
users can simply call x[[i]] or x[[i]] <- value where i is any argument used in the constructor.
If cut.fun=NULL, cut.dynamic=FALSE and cut.params does not have h or k,
clusterRows will automatically set h to half the tree height when calling cutree.
The HclustParam constructor will return a HclustParam object with the specified parameters.
The clusterRows method will return a factor of length equal to nrow(x) containing the cluster assignments.
If full=TRUE, a list is returned with clusters (the factor, as above) and objects
(a list containing dist, the distance matrix; and hclust, the output of hclust).
Aaron Lun
dist, hclust and cutree, which actually do all the heavy lifting.
cutreeDynamic, for an alternative tree cutting method to use in cut.fun.
clusterRows(iris[,1:4], HclustParam())
clusterRows(iris[,1:4], HclustParam(method="ward.D2"))
clusterRows(iris[,1:4], HclustParam(metric = "canberra", dist.fun = vegan::vegdist))
clusterRows(iris[,1:4], HclustParam(clust.fun=fastcluster::hclust))
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