lsp {mp} | R Documentation |
Least-Square Projection
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)
[Package mp version 0.4.1 Index]