This is the class that extracts random effects, specifically random intercepts and
random slopes, from functional columns. This PipeOp fits a linear mixed model, specifically
a random intercept and random slope model, using the lme4::lmer() function.
The target variable is the value of the functional feature which is regressed on the functional feature's argument
while subject id determines the grouping structure. After model estimation, the random effects are extracted and
assigned to the correct id.
The parameters are the parameters inherited from PipeOpTaskPreprocSimple.
The new names append _random_intercept and _random_slope to the corresponding column name of the
functional feature.
mlr3pipelines::PipeOp -> mlr3pipelines::PipeOpTaskPreproc -> mlr3pipelines::PipeOpTaskPreprocSimple -> PipeOpFDARandomEffect
new()Initializes a new instance of this Class
PipeOpFDARandomEffect$new(id = "fda.random_effect", param_vals = list())id(character(1)) Identifier of the operator, default is "fda.random_effect".
param_vals(named list()) List of hyperparameter settings, overwriting
default settings set during construction.
clone()The objects of this class are cloneable with this method.
PipeOpFDARandomEffect$clone(deep = FALSE)deepWhether to make a deep clone.
task = tsk("dti")
po_fre = po("fda.random_effect")
task_fre = po_fre$train(list(task))[[1L]]
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