Calculates the Correlation-Adjusted (marginal) coRrelation scores (short CAR scores) implemented in care::carscore() in package care. The CAR scores for a set of features are defined as the correlations between the target and the decorrelated features. The filter returns the absolute value of the calculated scores.

Argument verbose defaults to FALSE.

## Super class

mlr3filters::Filter -> FilterCarScore

## Methods

### Public methods

Inherited methods

### Method new()

Create a FilterCarScore object.

### Method clone()

The objects of this class are cloneable with this method.

FilterCarScore$clone(deep = FALSE) #### Arguments deep Whether to make a deep clone. ## Examples if (requireNamespace("care")) { task = mlr3::tsk("mtcars") filter = flt("carscore") filter$calculate(task)
filter$param_set$values = list("diagonal" = TRUE)
filter$calculate(task) head(as.data.table(filter), 3) } #> Estimating optimal shrinkage intensity lambda (correlation matrix): 0.0707 #> feature score #> 1: wt 0.8062818 #> 2: cyl 0.7918806 #> 3: disp 0.7875962 if (mlr3misc::require_namespaces(c("mlr3pipelines", "care", "rpart"), quietly = TRUE)) { task = mlr3::tsk("mtcars") # Note: filter.frac is selected randomly and should be tuned. graph = po("filter", filter = flt("carscore"), filter.frac = 0.5) %>>% po("learner", mlr3::lrn("regr.rpart")) graph$train(task)