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Calls mboost::blackboost from package mboost.

Details

distr prediction made by mboost::survFit().

Dictionary

This Learner can be instantiated via the dictionary mlr_learners or with the associated sugar function lrn():

mlr_learners$get("surv.blackboost")
lrn("surv.blackboost")

Meta Information

  • Task type: “surv”

  • Predict Types: “distr”, “crank”, “lp”

  • Feature Types: “integer”, “numeric”, “factor”

  • Required Packages: mlr3extralearners, mboost, pracma

Parameters

IdTypeDefaultLevelsRange
familycharactercoxphcoxph, weibull, loglog, lognormal, gehan, cindex, custom\((-\infty, \infty)\)
custom.familylist-\((-\infty, \infty)\)
nuirangelist0, 100\((-\infty, \infty)\)
offsetlist-\((-\infty, \infty)\)
centerlogicalTRUETRUE, FALSE\((-\infty, \infty)\)
mstopinteger100\([0, \infty)\)
nunumeric0.1\([0, 1]\)
riskcharacter-inbag, oobag, none\((-\infty, \infty)\)
stopinternlogicalFALSETRUE, FALSE\((-\infty, \infty)\)
tracelogicalFALSETRUE, FALSE\((-\infty, \infty)\)
oobweightslist-\((-\infty, \infty)\)
teststatcharacterquadraticquadratic, maximum\((-\infty, \infty)\)
splitstatcharacterquadraticquadratic, maximum\((-\infty, \infty)\)
splittestlogicalFALSETRUE, FALSE\((-\infty, \infty)\)
testtypecharacterBonferroniBonferroni, MonteCarlo, Univariate, Teststatistic\((-\infty, \infty)\)
maxptsinteger25000\([1, \infty)\)
absepsnumeric0.001\((-\infty, \infty)\)
relepsnumeric0\((-\infty, \infty)\)
nmaxlist-\((-\infty, \infty)\)
alphanumeric0.05\([0, 1]\)
mincriterionnumeric0.95\([0, 1]\)
logmincriterionnumeric-0.05129329\((-\infty, 0]\)
minsplitinteger20\([0, \infty)\)
minbucketinteger7\([0, \infty)\)
minprobnumeric0.01\([0, 1]\)
stumplogicalFALSETRUE, FALSE\((-\infty, \infty)\)
lookaheadlogicalFALSETRUE, FALSE\((-\infty, \infty)\)
MIAlogicalFALSETRUE, FALSE\((-\infty, \infty)\)
nresampleinteger9999\([1, \infty)\)
tolnumeric1.490116e-08\([0, \infty)\)
maxsurrogateinteger0\([0, \infty)\)
mtryinteger-\([0, \infty)\)
maxdepthinteger-\([0, \infty)\)
multiwaylogicalFALSETRUE, FALSE\((-\infty, \infty)\)
splittryinteger2\([1, \infty)\)
intersplitlogicalFALSETRUE, FALSE\((-\infty, \infty)\)
majoritylogicalFALSETRUE, FALSE\((-\infty, \infty)\)
caseweightslogicalTRUETRUE, FALSE\((-\infty, \infty)\)
sigmanumeric0.1\([0, 1]\)
ipcwlist1\((-\infty, \infty)\)
na.actionlistfunction (object, ...) , UseMethod("na.omit")\((-\infty, \infty)\)

References

Bühlmann P, Yu B (2003). “Boosting With the L2 Loss.” Journal of the American Statistical Association, 98(462), 324–339. doi: 10.1198/016214503000125

See also

Author

RaphaelS1

Super classes

mlr3::Learner -> mlr3proba::LearnerSurv -> LearnerSurvBlackBoost

Methods

Inherited methods


Method new()

Creates a new instance of this R6 class.

Usage


Method clone()

The objects of this class are cloneable with this method.

Usage

LearnerSurvBlackBoost$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Examples

if (requireNamespace("mboost", quietly = TRUE) && requireNamespace("pracma", quietly = TRUE)) {
  learner = mlr3::lrn("surv.blackboost")
  print(learner)

  # available parameters:
  learner$param_set$ids()
}
#> <LearnerSurvBlackBoost:surv.blackboost>
#> * Model: -
#> * Parameters: family=coxph
#> * Packages: mlr3, mlr3extralearners, mboost, pracma
#> * Predict Type: distr
#> * Feature types: integer, numeric, factor
#> * Properties: weights
#>  [1] "family"          "custom.family"   "nuirange"        "offset"         
#>  [5] "center"          "mstop"           "nu"              "risk"           
#>  [9] "stopintern"      "trace"           "oobweights"      "teststat"       
#> [13] "splitstat"       "splittest"       "testtype"        "maxpts"         
#> [17] "abseps"          "releps"          "nmax"            "alpha"          
#> [21] "mincriterion"    "logmincriterion" "minsplit"        "minbucket"      
#> [25] "minprob"         "stump"           "lookahead"       "MIA"            
#> [29] "nresample"       "tol"             "maxsurrogate"    "mtry"           
#> [33] "maxdepth"        "multiway"        "splittry"        "intersplit"     
#> [37] "majority"        "caseweights"     "sigma"           "ipcw"           
#> [41] "na.action"