mlr3filters (version 0.1.1)

FilterInformationGain: Information Gain Filter

Description

Information gain filter calling FSelectorRcpp::information_gain() in package FSelectorRcpp. Set parameter "type" to "gainratio" to calculate the gain ratio, or set to "symuncert" to calculate the symmetrical uncertainty (see FSelectorRcpp::information_gain()). Default is "infogain".

Argument equal defaults to FALSE for classification tasks, and to TRUE for regression tasks.

Format

R6::R6Class inheriting from Filter.

Construction

FilterInformationGain$new()
mlr_filters$get("information_gain")
flt("information_gain")

See Also

Dictionary of Filters: mlr_filters

Other Filter: FilterAUC, FilterAnova, FilterCMIM, FilterCarScore, FilterCorrelation, FilterDISR, FilterImportance, FilterJMIM, FilterJMI, FilterKruskalTest, FilterMIM, FilterMRMR, FilterNJMIM, FilterPerformance, FilterVariance, Filter, mlr_filters

Examples

# NOT RUN {
## InfoGain (default)
task = mlr3::tsk("pima")
filter = flt("information_gain")
filter$calculate(task)
head(filter$scores, 3)
as.data.table(filter)

## GainRatio

filterGR = flt("information_gain")
filterGR$param_set$values = list("type" = "gainratio")
filterGR$calculate(task)
head(as.data.table(filterGR), 3)
# }

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