plmp {mp} | R Documentation |
Part-Linear Multidimensional Projection
Description
Creates a k-dimensional representation of the data. As input, a subsample and its k-dimensional mapping (control points) are required. The method approximates the subsample mapping to a linear mapping and then applies the same mapping to all instances.
Usage
plmp(X, sample.indices = NULL, Ys = NULL, k = 2)
Arguments
X |
A dataframe or matrix representing the data. |
sample.indices |
The indices of subsamples used as control points. |
Ys |
The control points. |
k |
The target dimensionality. |
Value
The low-dimensional representation of the data.
References
Paulovich, F.V.; Silva, C.T.; Nonato, L.G., "Two-Phase Mapping for Projecting Massive Data Sets," Visualization and Computer Graphics, IEEE Transactions on , vol.16, no.6, pp.1281,1290, Nov.-Dec. 2010.
Examples
# Iris example
emb <- plmp(iris[,1:4])
plot(emb, col=iris$Species)
[Package mp version 0.4.1 Index]