A simple mlr3misc::Dictionary storing objects of class Filter.
Each Filter has an associated help page, see mlr_filters_[id].
This dictionary can get populated with additional filters by add-on packages.
For a more convenient way to retrieve and construct filters, see flt().
Format
R6::R6Class object
Usage
See mlr3misc::Dictionary.
See also
Other Filter:
Filter,
mlr_filters_anova,
mlr_filters_auc,
mlr_filters_boruta,
mlr_filters_carscore,
mlr_filters_carsurvscore,
mlr_filters_cmim,
mlr_filters_correlation,
mlr_filters_disr,
mlr_filters_find_correlation,
mlr_filters_importance,
mlr_filters_information_gain,
mlr_filters_jmi,
mlr_filters_jmim,
mlr_filters_kruskal_test,
mlr_filters_mim,
mlr_filters_mrmr,
mlr_filters_njmim,
mlr_filters_performance,
mlr_filters_permutation,
mlr_filters_relief,
mlr_filters_selected_features,
mlr_filters_univariate_cox,
mlr_filters_variance
Examples
mlr_filters$keys()
#> [1] "anova" "auc" "boruta"
#> [4] "carscore" "carsurvscore" "cmim"
#> [7] "correlation" "disr" "ensemble"
#> [10] "find_correlation" "importance" "information_gain"
#> [13] "jmi" "jmim" "kruskal_test"
#> [16] "mim" "mrmr" "njmim"
#> [19] "performance" "permutation" "relief"
#> [22] "selected_features" "univariate_cox" "variance"
as.data.table(mlr_filters)
#> Error in assert_list(filters, types = "Filter", min.len = 1): argument "filters" is missing, with no default
mlr_filters$get("mim")
#>
#> ── <FilterMIM> mim: Mutual Information Maximization ────────────────────────────
#> • Task Types: classif and regr
#> • Properties: -
#> • Task Properties:
#> • Packages: praznik
#> • Feature types: integer, numeric, factor, and ordered
flt("anova")
#>
#> ── <FilterAnova> anova: ANOVA F-Test ───────────────────────────────────────────
#> • Task Types: classif
#> • Properties: -
#> • Task Properties:
#> • Packages: stats
#> • Feature types: integer and numeric