basis_onpp: The basis of Orthogonal Neighborhood Preserving Projection...

In spinifex: Manual Tours, Manual Control of Dynamic Projections of Numeric Multivariate Data

The basis of Orthogonal Neighborhood Preserving Projection (OLPP)

Description

Orthogonal Neighborhood Preserving Projection (ONPP) is an unsupervised linear dimension reduction method. It constructs a weighted data graph from LLE method. Also, it develops LPP method by preserving the structure of local neighborhoods. For the more details on type see Rdimtools::aux.graphnbd().

Usage

basis_onpp(data, d = 2, type = c("knn", sqrt(nrow(data))))

Arguments

data	Numeric matrix or data.frame of the observations, coerced to matrix.
d	Number of dimensions in the projection space.
type	A vector specifying the neighborhood graph construction. Expects; c("knn", k), c("enn", radius), or c("proportion",ratio). Defaults to c("knn", sqrt(nrow(data))), nearest neighbors equal to the square root of observations.

Value

Orthogonal matrix basis that distinguishes the levels of class based on local and non-local variation as weighted against the neighborhood graph.

References

He X (2005). Locality Preserving Projections. PhD Thesis, University of Chicago, Chicago, IL, USA.

See Also

Rdimtools::do.onpp

Rdimtools::aux.graphnbd for details on type.

Other basis producing functions: basis_guided(), basis_half_circle(), basis_odp(), basis_olda(), basis_pca()

Examples

dat  <- scale_sd(wine[, 2:6])
basis_onpp(data = dat)

spinifex documentation built on March 31, 2022, 9:06 a.m.