sparse_random_projection: Reduce the dimensionality of a population using sparse random...

In cytominer: Methods for Image-Based Cell Profiling

Description

sparse_random_projection reduces the dimensionality of a population by projecting the original data with a sparse random matrix. Generally more efficient and faster to compute than a Gaussian random projection matrix, while providing similar embedding quality.

Usage

sparse_random_projection(population, variables, n_components)

Arguments

population	tbl with grouping (metadata) and observation variables.
variables	character vector specifying observation variables.
n_components	size of the projected feature space.

Value

Dimensionality reduced population.

Examples

population <- tibble::tibble(
  Metadata_Well = c("A01", "A02", "B01", "B02"),
  AreaShape_Area_DNA = c(10, 12, 7, 7),
  AreaShape_Length_DNA = c(2, 3, 1, 5),
  Intensity_DNA = c(8, 20, 12, 32),
  Texture_DNA = c(5, 2, 43, 13)
)
variables <- c("AreaShape_Area_DNA", "AreaShape_Length_DNA", "Intensity_DNA", "Texture_DNA")
sparse_random_projection(population, variables, 2)

cytominer documentation built on July 8, 2020, 5:08 p.m.