Locally linear embedding (LLE) is an extension of PCA, which reduces data that lies on a manifold embedded in a high dimensional space into a low dimensional space. In contrast to ISOMAP, which is a global approach for nonlinear dimension reduction, LLE is a local approach that employs a linear combination of the k-nearest neighbor to preserve local properties of data. In this recipe, we will give a short introduction of how to use LLE on an s-curve data.
In this recipe, we will use digit data from lle_scurve_data
within the lle
package as our input source.
Perform the following steps to perform nonlinear dimension reduction with LLE:
First, you need to install and load the package,
lle
:> install.packages("lle") > library(lle)
You can then load
ll_scurve_data
fromlle
:> data( lle_scurve_data )
Next, perform
lle
onlle_scurve_data
:> X = lle_scurve_data > results = lle( X=X , m...