gpuHclust {gputools} | R Documentation |
This function performs clustering on a set of points. The distance between each pair of points should be calculated first using a function like 'gpuDist' or 'dist'.
gpuHclust(distances, method = "single")
distances |
a matrix of floating point numbers whose i, j entry represents the distance between point i and point j. To use this with the dist function, be sure to generate the whole matrix of distances, and wrap the output with 'as.matrix'. |
method |
a string representing the name of the clustering method to be applied to distances. Currently supported method names include "average", "centroid", "complete", "flexible", "flexible group", "mcquitty", "median", "single", "ward", and "wpgma". |
Copied from the native R function 'hclust' documentation. A list with the following components.
merge |
an n-1 by 2 matrix. Row i of 'merge' describes the merging of clusters at step i of the clustering. If an element j in the row is negative, then observation -j was merged at this stage. If j is positive then the merge was with the cluster formed at the (earlier) stage j of the algorithm. Thus negative entries in 'merge' indicate agglomerations of singletons, and positive entries indicate agglomerations of non-singletons. Copied from the native R function 'hclust' documentation. |
order |
a vector giving the permutation of the original observations suitable for plotting, in the sense that a cluster plot using this ordering and matrix 'merge' will not have crossings of the branches. |
height |
a set of n-1 non-decreasing real values. The clustering height: that is, the value of the criterion associated with the clustering 'method' for the particular agglomeration. |
hclust, gpuDistClust
numVectors <- 5 dimension <- 10 Vectors <- matrix(runif(numVectors*dimension), numVectors, dimension) distMat <- gpuDist(Vectors, "euclidean") gpuHclust(distMat, "single") gpuHclust(as.matrix(dist(Vectors)), "single")