do.lle {Rdimtools} | R Documentation |
Locally Linear Embedding
Description
Locally-Linear Embedding (LLE) was introduced approximately at the same time as Isomap.
Its idea was motivated to describe entire data manifold by making a chain of local patches
in that low-dimensional embedding should resemble the connectivity pattern of patches.
do.lle
also provides an automatic choice of regularization parameter based on an
optimality criterion suggested by authors.
Usage
do.lle(
X,
ndim = 2,
type = c("proportion", 0.1),
symmetric = "union",
weight = TRUE,
preprocess = c("null", "center", "scale", "cscale", "decorrelate", "whiten"),
regtype = FALSE,
regparam = 1
)
Arguments
X |
an |
ndim |
an integer-valued target dimension. |
type |
a vector of neighborhood graph construction. Following types are supported;
|
symmetric |
one of |
weight |
|
preprocess |
an additional option for preprocessing the data.
Default is "null". See also |
regtype |
|
regparam |
regularization parameter. |
Value
a named list containing
- Y
an
matrix whose rows are embedded observations.
- trfinfo
a list containing information for out-of-sample prediction.
- eigvals
a vector of eigenvalues from computation of embedding matrix.
Author(s)
Kisung You
References
Roweis ST (2000). “Nonlinear Dimensionality Reduction by Locally Linear Embedding.” Science, 290(5500), 2323–2326.
Examples
## generate swiss-roll data
set.seed(100)
X = aux.gensamples(n=100)
## 1. connecting 10% of data for graph construction.
output1 <- do.lle(X,ndim=2,type=c("proportion",0.10))
## 2. constructing 20%-connected graph
output2 <- do.lle(X,ndim=2,type=c("proportion",0.20))
## 3. constructing 50%-connected with bigger regularization parameter
output3 <- do.lle(X,ndim=2,type=c("proportion",0.5),regparam=10)
## Visualize three different projections
opar <- par(no.readonly=TRUE)
par(mfrow=c(1,3))
plot(output1$Y, main="5%")
plot(output2$Y, main="10%")
plot(output3$Y, main="50%+Binary")
par(opar)