Description Usage Arguments Details Value Author(s) See Also Examples
Build a vantage point tree in preparation for a nearestneighbors search.
1  buildVptree(X, transposed=FALSE, distance=c("Euclidean", "Manhattan"))

X 
A numeric matrix where rows correspond to data points and columns correspond to variables (i.e., dimensions). 
transposed 
Logical scalar indicating whether 
distance 
String specifying the type of distance to use. 
This function is automatically called by findVptree
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
.
A VptreeIndex 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 nearestneighbor search.
nodes
, a list containing four vectors of equal length describing the structure of the VP tree.
Each parallel element specifies a node.
The first integer vector specifies the column index of data
of the current node.
The second integer vector specifies the column index of the left child of the current node,
The third integer vector specifies the column index of the right child of the current node.
The fourth numeric vector specifies the radius of the current node.
All indices here are zerobased, with child values set to 1 for leaf nodes.
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.
Aaron Lun
See VptreeIndex
for details on the output class.
See findVptree
and queryVptree
for dependent functions.
1 2 3  Y < matrix(rnorm(100000), ncol=20)
out < buildVptree(Y)
out

class: VptreeIndex
dim: 5000 20
distance: Euclidean
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