PipeOpAmelia {NADIA} | R Documentation |
PipeOpAmelia
Description
Implements EMB methods as mlr3 pipeline more about Amelia autotune_Amelia
or https://cran.r-project.org/package=Amelia
Input and Output Channels
Input and output channels are inherited from PipeOpImpute
.
Parameters
The parameters include inherited from ['PipeOpImpute'], as well as:
-
id
::character(1)
Identifier of resulting object, default"imput_Amelia"
. -
m
::integer(1)
Number of datasets generated by Amelia, default3
. -
polytime
::integer(1)
Integer between 0 and 3 indicating what power of polynomial should be included in the imputation model to account for the effects of time. A setting of 0 would indicate constant levels, 1 would indicate linear time effects, 2 would indicate squared effects, and 3 would indicate cubic time effects, defaultNULL
. -
splinetime
::integer(1)
Integer value of 0 or greater to control cubic smoothing splines of time. Values between 0 and 3 create a simple polynomial of time (identical to the polytime argument). Values k greater than 3 create a spline with an additional k-3 knotpoints, defaultNULL
. -
intercs
::logical(1)
Variable indicating if the time effects of polytime should vary across the cross-section, defaultFALSE
. -
empir
::double(1)
Number indicating level of the empirical (or ridge) prior. This prior shrinks the covariances of the data, but keeps the means and variances the same for problems of high missingness, small N's or large correlations among the variables. Should be kept small, perhaps 0.5 to 1 percent of the rows of the data; a reasonable upper bound is around 10 percent of the rows of the data. If empir is not set, empir=nrow(df)*0.015, defaultNULL
. -
parallel
::double(1)
If true parallel calculation is used, defaultTRUE
. -
out_fill
::character(1)
Output log file location. If file already exists log message will be added. If NULL no log will be produced, defaultNULL
.
Super classes
mlr3pipelines::PipeOp
-> mlr3pipelines::PipeOpImpute
-> Amelia_imputation
Methods
Public methods
Inherited methods
Method new()
Usage
PipeOpAmelia$new( id = "impute_Amelia_B", polytime = NULL, splinetime = NULL, intercs = FALSE, empir = NULL, m = 3, parallel = TRUE, out_file = NULL )
Method clone()
The objects of this class are cloneable with this method.
Usage
PipeOpAmelia$clone(deep = FALSE)
Arguments
deep
Whether to make a deep clone.
Examples
# Using debug learner for example purpose
graph <- PipeOpAmelia$new() %>>% LearnerClassifDebug$new()
graph_learner <- GraphLearner$new(graph)
graph_learner$param_set$values$impute_Amelia_B.parallel <- FALSE
resample(tsk("pima"), graph_learner, rsmp("cv", folds = 3))