Performs a normalization of data, i.e., it scales all numeric variables in
the range 0 - 1. This is a special case of change_scale()
.
normalize(x, ...)# S3 method for numeric
normalize(x, include_bounds = TRUE, verbose = TRUE, ...)
# S3 method for grouped_df
normalize(
x,
select = NULL,
exclude = NULL,
include_bounds = TRUE,
verbose = TRUE,
...
)
# S3 method for data.frame
normalize(
x,
select = NULL,
exclude = NULL,
include_bounds = TRUE,
verbose = TRUE,
...
)
Object.
Arguments passed to or from other methods.
Logical, if TRUE
, return value may include 0
and 1. If FALSE
, the return value is compressed, using the formula
(x * (n - 1) + 0.5) / n
(Smithson and Verkuilen 2006), to
avoid zeros and ones in the normalized variables. This can be useful in
case of beta-regression, where the response variable is not allowed to
include zeros and ones.
Toggle warnings on or off.
Character vector of column names. If NULL
(the default), all
variables will be selected.
Character vector of column names to be excluded from selection.
A normalized object.
Smithson M, Verkuilen J (2006). A Better Lemon Squeezer? Maximum-Likelihood Regression with Beta-Distributed Dependent Variables. Psychological Methods, 11(1), 54<U+2013>71.
# NOT RUN {
normalize(c(0, 1, 5, -5, -2))
normalize(c(0, 1, 5, -5, -2), include_bounds = FALSE)
head(normalize(iris))
# }
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