Looks if the nominal or character columns are equally distributed according to the entropy and taking into account the independence between batches. If any column is different in each row it is assumed to be the sample names and thus omitted.

evaluate_entropy(i, pheno)

Arguments

i

list of numeric indices of the data.frame

pheno

Data.frame with information about the samples

Value

Value to minimize

See also

Other functions to evaluate samples: evaluate_independence(), evaluate_index(), evaluate_mad(), evaluate_mean(), evaluate_na(), evaluate_orig(), evaluate_sd()

Other functions to evaluate categories: evaluate_independence(), evaluate_na()

Examples

data(survey, package = "MASS") index <- design(survey[, c("Sex", "Smoke", "Age")], size_subset = 50, iterations = 50) # Note that numeric columns will be omitted: evaluate_entropy(index, survey[, c("Sex", "Smoke", "Age")])
#> Sex Smoke #> 0.005981625 0.449097304