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" "find_correlation"
#> [10] "importance" "information_gain" "jmi"
#> [13] "jmim" "kruskal_test" "mim"
#> [16] "mrmr" "njmim" "performance"
#> [19] "permutation" "relief" "selected_features"
#> [22] "univariate_cox" "variance"
as.data.table(mlr_filters)
#> Key: <key>
#> key label
#> <char> <char>
#> 1: anova ANOVA F-Test
#> 2: auc Area Under the ROC Curve Score
#> 3: boruta Burota
#> 4: carscore Correlation-Adjusted coRrelation Score
#> 5: carsurvscore Correlation-Adjusted coRrelation Survival Score
#> 6: cmim Minimal Conditional Mutual Information Maximization
#> 7: correlation Correlation
#> 8: disr Double Input Symmetrical Relevance
#> 9: find_correlation Correlation-based Score
#> 10: importance Importance Score
#> 11: information_gain Information Gain
#> 12: jmi Joint Mutual Information
#> 13: jmim Minimal Joint Mutual Information Maximization
#> 14: kruskal_test Kruskal-Wallis Test
#> 15: mim Mutual Information Maximization
#> 16: mrmr Minimum Redundancy Maximal Relevancy
#> 17: njmim Minimal Normalised Joint Mutual Information Maximization
#> 18: performance Predictive Performance
#> 19: permutation Permutation Score
#> 20: relief RELIEF
#> 21: selected_features Embedded Feature Selection
#> 22: univariate_cox Univariate Cox Survival Score
#> 23: variance Variance
#> key label
#> task_types task_properties
#> <list> <list>
#> 1: classif
#> 2: classif twoclass
#> 3: regr,classif
#> 4: regr
#> 5: surv
#> 6: classif,regr
#> 7: regr
#> 8: classif,regr
#> 9: NA
#> 10: classif
#> 11: classif,regr
#> 12: classif,regr
#> 13: classif,regr
#> 14: classif
#> 15: classif,regr
#> 16: classif,regr
#> 17: classif,regr
#> 18: classif
#> 19: classif
#> 20: classif,regr
#> 21: classif
#> 22: surv
#> 23: NA
#> task_types task_properties
#> params
#> <list>
#> 1:
#> 2:
#> 3: pValue,mcAdj,maxRuns,doTrace,holdHistory,getImp,...
#> 4: lambda,diagonal,verbose
#> 5: maxIPCweight,denom
#> 6: threads
#> 7: use,method
#> 8: threads
#> 9: use,method
#> 10: method
#> 11: type,equal,discIntegers,threads
#> 12: threads
#> 13: threads
#> 14: na.action
#> 15: threads
#> 16: threads
#> 17: threads
#> 18: method
#> 19: standardize,nmc
#> 20: neighboursCount,sampleSize
#> 21: method
#> 22:
#> 23: na.rm
#> params
#> feature_types packages
#> <list> <list>
#> 1: integer,numeric stats
#> 2: integer,numeric mlr3measures
#> 3: integer,numeric Boruta
#> 4: logical,integer,numeric care
#> 5: integer,numeric carSurv,mlr3proba
#> 6: integer,numeric,factor,ordered praznik
#> 7: integer,numeric stats
#> 8: integer,numeric,factor,ordered praznik
#> 9: integer,numeric stats
#> 10: logical,integer,numeric,character,factor,ordered,... mlr3
#> 11: integer,numeric,factor,ordered FSelectorRcpp
#> 12: integer,numeric,factor,ordered praznik
#> 13: integer,numeric,factor,ordered praznik
#> 14: integer,numeric stats
#> 15: integer,numeric,factor,ordered praznik
#> 16: integer,numeric,factor,ordered praznik
#> 17: integer,numeric,factor,ordered praznik
#> 18: logical,integer,numeric,character,factor,ordered,... mlr3,mlr3measures
#> 19: logical,integer,numeric,character,factor,ordered,... mlr3,mlr3measures
#> 20: integer,numeric,factor,ordered FSelectorRcpp
#> 21: logical,integer,numeric,character,factor,ordered,... mlr3
#> 22: integer,numeric,logical survival
#> 23: integer,numeric stats
#> feature_types packages
mlr_filters$get("mim")
#> <FilterMIM:mim>: Mutual Information Maximization
#> Task Types: classif, regr
#> Properties: -
#> Task Properties: -
#> Packages: praznik
#> Feature types: integer, numeric, factor, ordered
flt("anova")
#> <FilterAnova:anova>: ANOVA F-Test
#> Task Types: classif
#> Properties: -
#> Task Properties: -
#> Packages: stats
#> Feature types: integer, numeric