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Tidy summarizes information about the components of a model. A model component might be a single term in a regression, a single hypothesis, a cluster, or a class. Exactly what tidy considers to be a model component varies cross models but is usually self-evident. If a model has several distinct types of components, you will need to specify which components to return.
# S3 method for dist
tidy(x, diagonal = attr(x, "Diag"), upper = attr(x, "Upper"), ...)
A dist
object returned from stats::dist()
.
Logical indicating whether or not to tidy the diagonal
elements of the distance matrix. Defaults to whatever was based to the
diag
argument of stats::dist()
.
Logical indicating whether or not to tidy the upper half of
the distance matrix. Defaults to whatever was based to the
upper
argument of stats::dist()
.
Additional arguments. Not used. Needed to match generic
signature only. Cautionary note: Misspelled arguments will be
absorbed in ...
, where they will be ignored. If the misspelled
argument has a default value, the default value will be used.
For example, if you pass conf.lvel = 0.9
, all computation will
proceed using conf.level = 0.95
. Additionally, if you pass
newdata = my_tibble
to an augment()
method that does not
accept a newdata
argument, it will use the default value for
the data
argument.
A tibble::tibble with one row for each pair of items in the distance matrix, with columns:
First item
Second item
Distance between items
If the distance matrix does not include an upper triangle and/or diagonal, the tidied version will not either.
Other stats tidiers:
tidy.density()
,
tidy.ftable()
# NOT RUN {
iris_dist <- dist(t(iris[, 1:4]))
iris_dist
tidy(iris_dist)
tidy(iris_dist, upper = TRUE)
tidy(iris_dist, diagonal = TRUE)
# }
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