maximize

ja-thomas · Apr 25, 2018 · b629639 · b629639
1 parent 385f3cd
commit b629639
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Showing 5 changed files with 4 additions and 8 deletions.
diff --git a/R/RLearner_classif_xgboost.custom.R b/R/RLearner_classif_xgboost.custom.R
@@ -4,8 +4,6 @@ makeRLearner.classif.xgboost.custom = function() {
     cl = "classif.xgboost.custom",
     package = "xgboost",
     par.set = makeParamSet(
-      # we pass all of what goes in 'params' directly to ... of xgboost
-      # makeUntypedLearnerParam(id = "params", default = list()),
       makeDiscreteLearnerParam(id = "booster", default = "gbtree", values = c("gbtree", "gblinear", "dart")),
       makeUntypedLearnerParam(id = "watchlist", default = NULL, tunable = FALSE),
       makeNumericLearnerParam(id = "eta", default = 0.3, lower = 0, upper = 1),
@@ -29,7 +27,6 @@ makeRLearner.classif.xgboost.custom = function() {
       makeNumericLearnerParam(id = "tweedie_variance_power", lower = 1, upper = 2, default = 1.5, requires = quote(objective == "reg:tweedie")),
       makeIntegerLearnerParam(id = "nthread", lower = 1L, tunable = FALSE),
       makeIntegerLearnerParam(id = "nrounds", default = 1L, lower = 1L),
-      # FIXME nrounds seems to have no default in xgboost(), if it has 1, par.vals is redundant
       makeUntypedLearnerParam(id = "feval", default = NULL, tunable = FALSE),
       makeIntegerLearnerParam(id = "verbose", default = 1L, lower = 0L, upper = 2L, tunable = FALSE),
       makeIntegerLearnerParam(id = "print_every_n", default = 1L, lower = 1L, tunable = FALSE,

diff --git a/R/RLearner_classif_xgboost.earlystop.R b/R/RLearner_classif_xgboost.earlystop.R
@@ -21,6 +21,7 @@ makeRLearner.classif.xgboost.earlystop = function() {
       makeIntegerLearnerParam(id = "early_stopping_rounds", default = 1, lower = 1L, tunable = FALSE),
       makeIntegerLearnerParam(id = "max.nrounds", default = 10^6L, lower = 1L, upper = 10^7L),
       makeUntypedLearnerParam(id = "early.stopping.data"),
+      makeLogicalLearnerParam(id = "maximize", default = NULL, special.vals = list(NULL), tunable = FALSE),
       makeNumericLearnerParam(id = "scale_pos_weight", lower = 0),
       makeIntegerLearnerParam(id = "nthread", lower = 1L, tunable = FALSE)
     ),

diff --git a/R/RLearner_regr_xgboost.custom.R b/R/RLearner_regr_xgboost.custom.R
@@ -4,8 +4,6 @@ makeRLearner.regr.xgboost.custom = function() {
     cl = "regr.xgboost.custom",
     package = "xgboost",
     par.set = makeParamSet(
-      # we pass all of what goes in 'params' directly to ... of xgboost
-      #makeUntypedLearnerParam(id = "params", default = list()),
       makeDiscreteLearnerParam(id = "booster", default = "gbtree", values = c("gbtree", "gblinear", "dart")),
       makeUntypedLearnerParam(id = "watchlist", default = NULL, tunable = FALSE),
       makeNumericLearnerParam(id = "eta", default = 0.3, lower = 0, upper = 1),
@@ -29,7 +27,6 @@ makeRLearner.regr.xgboost.custom = function() {
       makeNumericLearnerParam(id = "tweedie_variance_power", lower = 1, upper = 2, default = 1.5, requires = quote(objective == "reg:tweedie")),
       makeIntegerLearnerParam(id = "nthread", lower = 1L, tunable = FALSE),
       makeIntegerLearnerParam(id = "nrounds", default = 1L, lower = 1L),
-      # FIXME nrounds seems to have no default in xgboost(), if it has 1, par.vals is redundant
       makeUntypedLearnerParam(id = "feval", default = NULL, tunable = FALSE),
       makeIntegerLearnerParam(id = "verbose", default = 1L, lower = 0L, upper = 2L, tunable = FALSE),
       makeIntegerLearnerParam(id = "print_every_n", default = 1L, lower = 1L, tunable = FALSE,

diff --git a/R/RLearner_regr_xgboost.earlystop.R b/R/RLearner_regr_xgboost.earlystop.R
@@ -21,6 +21,7 @@ makeRLearner.regr.xgboost.earlystop = function() {
       makeIntegerLearnerParam(id = "early_stopping_rounds", default = 1, lower = 1L, tunable = FALSE),
       makeIntegerLearnerParam(id = "max.nrounds", default = 10^6L, lower = 1L, upper = 10^7L),
       makeUntypedLearnerParam(id = "early.stopping.data"),
+      makeLogicalLearnerParam(id = "maximize", default = NULL, special.vals = list(NULL), tunable = FALSE),
       makeIntegerLearnerParam(id = "nthread", lower = 1L, tunable = FALSE)
     ),
     properties = c("numerics", "weights", "missings"),

diff --git a/R/autoxgboost.R b/R/autoxgboost.R
@@ -113,7 +113,7 @@ autoxgboost = function(task, measure = NULL, control = NULL, iterations = 160L,
     }
 
     base.learner = makeLearner("classif.xgboost.earlystop", id = "classif.xgboost.earlystop", predict.type = predict.type,
-      eval_metric = eval_metric, objective = objective, early_stopping_rounds = early.stopping.rounds,
+      eval_metric = eval_metric, objective = objective, early_stopping_rounds = early.stopping.rounds, maximize = !measure$minimize,
       max.nrounds = max.nrounds, par.vals = pv)
 
   } else if (tt == "regr") {
@@ -122,7 +122,7 @@ autoxgboost = function(task, measure = NULL, control = NULL, iterations = 160L,
     eval_metric = "rmse"
 
     base.learner = makeLearner("regr.xgboost.earlystop", id = "regr.xgboost.earlystop",
-      eval_metric = eval_metric, objective = objective, early_stopping_rounds = early.stopping.rounds,
+      eval_metric = eval_metric, objective = objective, early_stopping_rounds = early.stopping.rounds, maximize = !measure$minimize,
       max.nrounds = max.nrounds, par.vals = pv)
 
   } else {