Description Usage Arguments Details Value References Examples
step_vast
creates a specification of a recipe
step that will perform VAST scaling on the columns
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 | ## S3 method for class 'step_svast'
tidy(x, ...)
step_vast(
recipe,
...,
scaling = "autoscale",
role = NA,
trained = FALSE,
means = NULL,
sds = NULL,
cvs = NULL,
na_rm = TRUE,
skip = FALSE,
id = rand_id("vast")
)
## S3 method for class 'step_vast'
tidy(x, ...)
## S3 method for class 'step_xvast'
tidy(x, ...)
|
x |
A |
... |
One or more selector functions to choose which
variables are affected by the step. See |
scaling |
Either |
role |
Not used by this step since no new variables are created. |
means |
A named numeric vector of means. This
is |
sds |
A named numeric vector of stadard deviations. This
is |
cvs |
A named numeric vector of variation coeficients. This
is |
na_rm |
A logical value indicating whether |
Variable Stability (VAST) scaling preforms centering and scaling followed by a weighting of each variable by its variation coeficient.
The argument scaling
controls which scaling method should be used before
variable weighting. autoscale
will perform mean-centering and standard deviation
scaling while pareto
will scale by the square-root of the standard deviation.
An updated version of recipe
with the new step
added to the sequence of existing steps (if any). For the
tidy
method, a tibble with columns terms
(the
selectors or variables selected), value
(the
standard deviations and means), and statistic
for the type of value.
Keun H. C., Ebbels T. M. D., Antti H., Bollard M. E., Beckonert O., Holmes E., et al. (2003). Improved analysis of multivariate data by variable stability scaling: application to NMR-based metabolic profiling. Anal. Chim. Acta 490, 265–276 10.1016/S0003-2670(03)00094-1 https://www.sciencedirect.com/science/article/abs/pii/S0003267003000941
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