buildKmknn: Pre-cluster points with k-means

In BiocNeighbors: Nearest Neighbor Detection for Bioconductor Packages

Description

Perform k-means clustering in preparation for a KMKNN nearest-neighbors search.

Usage

buildKmknn(X, transposed=FALSE, distance=c("Euclidean", "Manhattan"), ...)

Arguments

X	A numeric matrix where rows correspond to data points and columns correspond to variables (i.e., dimensions).
transposed	Logical scalar indicating whether X is transposed, i.e., rows are variables and columns are data points.
distance	String specifying the type of distance to use.
...	Further arguments to pass to kmeans.

Details

This function is automatically called by findKmknn and related functions. However, it can be called directly by the user to save time if multiple queries are to be performed to the same X.

Value

A KmknnIndex object containing:

• data, a numeric matrix with points in the columns and dimensions in the rows, i.e., transposed relative to the input. Points have also been reordered to improve data locality during the nearest-neighbor search. Specifically, points in the same cluster are contiguous and ordered by increasing distance from the cluster center.

• clusters, itself a list containing:

  • centers, a numeric matrix of cluster center coordinates where each column corresponds to a cluster.

  • info, another list of length equal to the number of clusters. Each entry corresponds to a column of centers (let's say cluster j) and is a list of length 2. The first element is the zero-index of the first cell in the output X that is assigned to j. The second element is the distance of each point in the cluster from the cluster center.

• order, an integer vector specifying how rows in X have been reordered in columns of data.

• NAMES, a character vector or NULL equal to rownames(X).

• distance, a string specifying the distance metric used.

Author(s)

Aaron Lun

See Also

See kmeans for optional arguments.

See KmknnIndex for details on the output class.

See findKmknn, queryKmknn and findNeighbors for dependent functions.

Examples

Y <- matrix(rnorm(100000), ncol=20)
out <- buildKmknn(Y)
out

BiocNeighbors documentation built on Dec. 9, 2020, 2:01 a.m.