cytominer (version 0.2.2)

svd_entropy: Feature importance based on data entropy.

Description

svd_entropy measures the contribution of each feature in decreasing the data entropy.

Usage

svd_entropy(variables, sample, cores = NULL)

Arguments

variables

character vector specifying observation variables.

sample

tbl containing sample used to estimate parameters.

cores

optional integer specifying number of CPU cores used for parallel computing using doParallel.

Value

data frame specifying the contribution of each feature in decreasing the data entropy. Higher values indicate more information.

Examples

# NOT RUN {
sample <- tibble::tibble(
  AreaShape_MinorAxisLength = c(10, 12, 15, 16, 8, 8, 7, 7, 13, 18),
  AreaShape_MajorAxisLength = c(35, 18, 22, 16, 9, 20, 11, 15, 18, 42),
  AreaShape_Area = c(245, 151, 231, 179, 50, 112, 53, 73, 164, 529)
)
variables <- c("AreaShape_MinorAxisLength", "AreaShape_MajorAxisLength", "AreaShape_Area")
svd_entropy(variables, sample, cores = 1)
# }