lsp: Least-Square Projection

In mp: Multidimensional Projection Techniques

Description

Creates a q-dimensional representation of multidimensional data. Requires a subsample (sample.indices) and its qD representation (Ys).

Usage

lsp(X, sample.indices = NULL, Ys = NULL, k = 15, q = 2)

Arguments

X	A data frame or matrix.
sample.indices	The indices of data points in X used as subsamples. If not given, some rows from X will be randomly selected and Ys will be generated by calling forceScheme on them.
Ys	Initial kD configuration of the data subsamples (will be ignored if sample.indices is NULL).
k	Number of neighbors used to build the neighborhood graph.
q	The target dimensionality.

Value

The qD representation of the data.

References

F. V. Paulovich, L. Nonato, R. Minghim, and H. Levkowitz, Least-Square Projection: A fast high-precision multidimensional projection technique and its application to document mapping, vol. 14, no. 3, pp. 564-575.

Examples

# Iris example
emb <- lsp(iris[, 1:4])
plot(emb, col=iris$Species)

Example output

mp documentation built on May 1, 2019, 10:19 p.m.