Hendrik/xgboost
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

Support slicing tree model (#6302)

Browse Source 
This PR is meant the end the confusion around best_ntree_limit and unify model slicing. We have multi-class and random forests, asking users to understand how to set ntree_limit is difficult and error prone.

* Implement the save_best option in early stopping.

Co-authored-by: Philip Hyunsu Cho <chohyu01@cs.washington.edu>
This commit is contained in:
Jiaming Yuan
2020-11-03 02:27:39 -05:00
committed by GitHub
parent 29745c6df2
commit 2cc9662005
19 changed files with 550 additions and 37 deletions
Download Patch File Download Diff File Expand all files Collapse all files

7
tests/cpp/test_learner.cc
View File

@@ -118,7 +118,7 @@ TEST(Learner, Configuration) {
// eval_metric is not part of configuration
auto attr_names = learner->GetConfigurationArguments();
ASSERT_EQ(attr_names.size(), 1);
ASSERT_EQ(attr_names.size(), 1ul);
ASSERT_EQ(attr_names.find(emetric), attr_names.cend());
ASSERT_EQ(attr_names.at("foo"), "bar");
}
@@ -127,7 +127,7 @@ TEST(Learner, Configuration) {
std::unique_ptr<Learner> learner { Learner::Create({nullptr}) };
learner->SetParams({{"foo", "bar"}, {emetric, "auc"}, {emetric, "entropy"}, {emetric, "KL"}});
auto attr_names = learner->GetConfigurationArguments();
ASSERT_EQ(attr_names.size(), 1);
ASSERT_EQ(attr_names.size(), 1ul);
ASSERT_EQ(attr_names.at("foo"), "bar");
}
}
@@ -181,7 +181,7 @@ TEST(Learner, JsonModelIO) {
learner->SaveModel(&new_in);
ASSERT_TRUE(IsA<Object>(out["learner"]["attributes"]));
ASSERT_EQ(get<Object>(out["learner"]["attributes"]).size(), 1);
ASSERT_EQ(get<Object>(out["learner"]["attributes"]).size(), 1ul);
ASSERT_EQ(out, new_in);
}
}
@@ -333,5 +333,4 @@ TEST(Learner, Seed) {
ASSERT_EQ(std::to_string(seed),
get<String>(config["learner"]["generic_param"]["seed"]));
}
} // namespace xgboost