Assuming that the fuzzy values are probabilities, calculates the probability of being of different sizes for a given set.
Usage
element_size(object, elements = NULL)
# S4 method for class 'TidySet'
element_size(object, elements = NULL)Methods (by class)
element_size(TidySet): Calculates the number of sets an element appears withlength_set()
See also
cardinality
Other sizes:
set_size()
Other methods:
TidySet-class,
activate(),
add_column(),
add_relation(),
arrange.TidySet(),
cartesian(),
complement(),
complement_element(),
complement_set(),
elements(),
filter.TidySet(),
group(),
group_by.TidySet(),
incidence(),
intersection(),
is.fuzzy(),
is_nested(),
move_to(),
mutate.TidySet(),
nElements(),
nRelations(),
nSets(),
name_elements<-(),
name_sets(),
name_sets<-(),
power_set(),
pull.TidySet(),
relations(),
remove_column(),
remove_element(),
remove_relation(),
remove_set(),
rename_elements(),
rename_set(),
select.TidySet(),
set_size(),
sets(),
subtract(),
union()
Examples
relations <- data.frame(
sets = c(rep("A", 5), "B", "C"),
elements = c(letters[seq_len(6)], letters[6]),
fuzzy = runif(7)
)
a <- tidySet(relations)
element_size(a)
#> elements size probability
#> 1 a 0 0.4400872
#> 2 a 1 0.5599128
#> 3 b 0 0.1429164
#> 4 b 1 0.8570836
#> 5 c 0 0.6151903
#> 6 c 1 0.3848097
#> 7 d 0 0.4720830
#> 8 d 1 0.5279170
#> 9 e 0 0.3993625
#> 10 e 1 0.6006375
#> 11 f 0 0.5243893
#> 12 f 1 0.3997999
#> 13 f 2 0.0758108
