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fix typos #361

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merged 1 commit into from
Mar 26, 2017
Merged

fix typos #361

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6 changes: 3 additions & 3 deletions src/boosting/boosting.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -48,11 +48,11 @@ Boosting* Boosting::CreateBoosting(const std::string& type, const char* filename
} else if (type == std::string("goss")) {
ret.reset(new GOSS());
} else {
Log::Fatal("unknow boosting type %s", type.c_str());
Log::Fatal("unknown boosting type %s", type.c_str());
}
LoadFileToBoosting(ret.get(), filename);
} else {
Log::Fatal("unknow submodel type in model file %s", filename);
Log::Fatal("unknown submodel type in model file %s", filename);
}
return ret.release();
}
Expand All @@ -64,7 +64,7 @@ Boosting* Boosting::CreateBoosting(const char* filename) {
if (type == std::string("tree")) {
ret.reset(new GBDT());
} else {
Log::Fatal("unknow submodel type in model file %s", filename);
Log::Fatal("unknown submodel type in model file %s", filename);
}
LoadFileToBoosting(ret.get(), filename);
return ret.release();
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4 changes: 2 additions & 2 deletions src/boosting/dart.hpp
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Expand Up @@ -84,7 +84,7 @@ class DART: public GBDT {
void DroppingTrees() {
drop_index_.clear();
bool is_skip = random_for_drop_.NextFloat() < gbdt_config_->skip_drop;
// select dropping tree indexes based on drop_rate and tree weights
// select dropping tree indices based on drop_rate and tree weights
if (!is_skip) {
double drop_rate = gbdt_config_->drop_rate;
if (!gbdt_config_->uniform_drop) {
Expand Down Expand Up @@ -180,7 +180,7 @@ class DART: public GBDT {
std::vector<double> tree_weight_;
/*! \brief sum weights of all trees */
double sum_weight_;
/*! \brief The indexes of dropping trees */
/*! \brief The indices of dropping trees */
std::vector<int> drop_index_;
/*! \brief Random generator, used to select dropping trees */
Random random_for_drop_;
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2 changes: 1 addition & 1 deletion src/boosting/gbdt.cpp
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Expand Up @@ -370,7 +370,7 @@ bool GBDT::TrainOneIter(const score_t* gradient, const score_t* hessian, bool is
#ifdef TIMETAG
start_time = std::chrono::steady_clock::now();
#endif
std::unique_ptr<Tree> new_tree(new Tree(2));
std::unique_ptr<Tree> new_tree;
// train a new tree
new_tree.reset(tree_learner_->Train(gradient + curr_class * num_data_, hessian + curr_class * num_data_));
#ifdef TIMETAG
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4 changes: 1 addition & 3 deletions src/boosting/gbdt.h
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Expand Up @@ -26,11 +26,10 @@ class GBDT: public Boosting {
~GBDT();
/*!
* \brief Initialization logic
* \param config Config for boosting
* \param gbdt_config Config for boosting
* \param train_data Training data
* \param object_function Training objective function
* \param training_metrics Training metrics
* \param output_model_filename Filename of output model
*/
void Init(const BoostingConfig* gbdt_config, const Dataset* train_data, const ObjectiveFunction* object_function,
const std::vector<const Metric*>& training_metrics)
Expand Down Expand Up @@ -267,7 +266,6 @@ class GBDT: public Boosting {
std::string OutputMetric(int iter);
/*!
* \brief Calculate feature importances
* \param last_iter Last tree use to calculate
*/
std::vector<std::pair<size_t, std::string>> FeatureImportance() const;
/*! \brief current iteration */
Expand Down