Reduce the dimensionality of a population using sparse random projection.

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.

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)
#> # A tibble: 4 x 3
#>   Metadata_Well    R1    R2
#>   <chr>         <dbl> <dbl>
#> 1 A01             -10     2
#> 2 A02             -12     3
#> 3 B01              -7     1
#> 4 B02              -7     5