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Fix continue training in CLI

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This commit is contained in:
tqchen
2016-03-10 12:42:54 -08:00
parent 845f80ec22
commit 96b17971ac
3 changed files with 17 additions and 11 deletions
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16
src/learner.cc
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@@ -14,6 +14,7 @@
#include <limits>
#include <iomanip>
#include "./common/io.h"
#include "./common/common.h"
#include "./common/random.h"
namespace xgboost {
@@ -27,13 +28,6 @@ Learner::Dump2Text(const FeatureMap& fmap, int option) const {
return gbm_->Dump2Text(fmap, option);
}
// simple routine to convert any data to string
template<typename T>
inline std::string ToString(const T& data) {
std::ostringstream os;
os << data;
return os.str();
}
/*! \brief training parameter for regression */
struct LearnerModelParam
@@ -192,7 +186,7 @@ class LearnerImpl : public Learner {
common::GlobalRandom().seed(tparam.seed);
// set number of features correctly.
cfg_["num_feature"] = ToString(mparam.num_feature);
cfg_["num_feature"] = common::ToString(mparam.num_feature);
if (gbm_.get() != nullptr) {
gbm_->Configure(cfg_.begin(), cfg_.end());
}
@@ -252,13 +246,13 @@ class LearnerImpl : public Learner {
attributes_ = std::map<std::string, std::string>(
attr.begin(), attr.end());
}
if (metrics_.size() == 0) {
metrics_.emplace_back(Metric::Create(obj_->DefaultEvalMetric()));
}
this->base_score_ = mparam.base_score;
gbm_->ResetPredBuffer(pred_buffer_size_);
cfg_["num_class"] = ToString(mparam.num_class);
cfg_["num_class"] = common::ToString(mparam.num_class);
cfg_["num_feature"] = common::ToString(mparam.num_feature);
obj_->Configure(cfg_.begin(), cfg_.end());
}
@@ -395,7 +389,7 @@ class LearnerImpl : public Learner {
}
// setup
cfg_["num_feature"] = ToString(mparam.num_feature);
cfg_["num_feature"] = common::ToString(mparam.num_feature);
CHECK(obj_.get() == nullptr && gbm_.get() == nullptr);
obj_.reset(ObjFunction::Create(name_obj_));
gbm_.reset(GradientBooster::Create(name_gbm_));