nystrom_embedding: Nystrom method for out-of-sample embedding

In bbuchsbaum/multivarious: Extensible Data Structures for Multivariate Analysis

Nystrom method for out-of-sample embedding

Description

Approximate the embedding of a new data point using the Nystrom method, which is particularly useful for large datasets and data-dependent embedding spaces, such as multidimensional scaling (MDS).

Usage

nystrom_embedding(
  new_data,
  landmark_data,
  kernel_function,
  eigenvectors,
  eigenvalues,
  ...
)

Arguments

new_data	A matrix or data frame containing the new data points to be projected.
landmark_data	A matrix or data frame containing the landmark data points used for approximation.
kernel_function	A function used to compute the kernel matrix (e.g., a distance function for MDS).
eigenvectors	A matrix containing the eigenvectors obtained from the eigendecomposition of the kernel matrix between the landmark points.
eigenvalues	A vector containing the eigenvalues obtained from the eigendecomposition of the kernel matrix between the landmark points.
...	Additional arguments passed to the kernel_function.

Value

A matrix containing the approximate embedding of the new_data in the data-dependent space.

bbuchsbaum/multivarious documentation built on April 15, 2024, 3:33 a.m.