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A simple 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().

Usage

mlr_filters

Format

R6Class object

Usage

See Dictionary.

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