Skip to content

GitLab

Commit 2051223b authored by guolinke's avatar guolinke
Browse files

better naming

parent 77d92b7c
Hide whitespace changes
Inline Side-by-side
Showing with 17 additions and 17 deletions
src/treelearner/feature_histogram.hpp
View file @ 2051223b
......@@ -149,12 +149,12 @@ class FeatureHistogram {
double min_gain_shift =
BeforeNumercal<USE_RAND, USE_L1, USE_MAX_OUTPUT>(
sum_gradient, sum_hessian, output, &rand_threshold);
FindBestThresholdSequence<USE_RAND, USE_MC, USE_L1,
USE_MAX_OUTPUT, true, true, false>(
FindBestThresholdSequentially<USE_RAND, USE_MC, USE_L1,
USE_MAX_OUTPUT, true, true, false>(
sum_gradient, sum_hessian, num_data, constraints,
min_gain_shift, output, rand_threshold);
FindBestThresholdSequence<USE_RAND, USE_MC, USE_L1,
USE_MAX_OUTPUT, false, true, false>(
FindBestThresholdSequentially<USE_RAND, USE_MC, USE_L1,
USE_MAX_OUTPUT, false, true, false>(
sum_gradient, sum_hessian, num_data, constraints,
min_gain_shift, output, rand_threshold);
};
......@@ -166,12 +166,12 @@ class FeatureHistogram {
double min_gain_shift =
BeforeNumercal<USE_RAND, USE_L1, USE_MAX_OUTPUT>(
sum_gradient, sum_hessian, output, &rand_threshold);
FindBestThresholdSequence<USE_RAND, USE_MC, USE_L1,
USE_MAX_OUTPUT, true, false, true>(
FindBestThresholdSequentially<USE_RAND, USE_MC, USE_L1,
USE_MAX_OUTPUT, true, false, true>(
sum_gradient, sum_hessian, num_data, constraints,
min_gain_shift, output, rand_threshold);
FindBestThresholdSequence<USE_RAND, USE_MC, USE_L1,
USE_MAX_OUTPUT, false, false, true>(
FindBestThresholdSequentially<USE_RAND, USE_MC, USE_L1,
USE_MAX_OUTPUT, false, false, true>(
sum_gradient, sum_hessian, num_data, constraints,
min_gain_shift, output, rand_threshold);
};
......@@ -185,8 +185,8 @@ class FeatureHistogram {
double min_gain_shift =
BeforeNumercal<USE_RAND, USE_L1, USE_MAX_OUTPUT>(
sum_gradient, sum_hessian, output, &rand_threshold);
FindBestThresholdSequence<USE_RAND, USE_MC, USE_L1,
USE_MAX_OUTPUT, true, false, false>(
FindBestThresholdSequentially<USE_RAND, USE_MC, USE_L1,
USE_MAX_OUTPUT, true, false, false>(
sum_gradient, sum_hessian, num_data, constraints,
min_gain_shift, output, rand_threshold);
};
......@@ -198,8 +198,8 @@ class FeatureHistogram {
double min_gain_shift =
BeforeNumercal<USE_RAND, USE_L1, USE_MAX_OUTPUT>(
sum_gradient, sum_hessian, output, &rand_threshold);
FindBestThresholdSequence<USE_RAND, USE_MC, USE_L1,
USE_MAX_OUTPUT, true, false, false>(
FindBestThresholdSequentially<USE_RAND, USE_MC, USE_L1,
USE_MAX_OUTPUT, true, false, false>(
sum_gradient, sum_hessian, num_data, constraints,
min_gain_shift, output, rand_threshold);
output->default_left = false;
......@@ -769,11 +769,11 @@ class FeatureHistogram {
template <bool USE_RAND, bool USE_MC, bool USE_L1, bool USE_MAX_OUTPUT,
bool REVERSE, bool SKIP_DEFAULT_BIN, bool NA_AS_MISSING>
void FindBestThresholdSequence(double sum_gradient, double sum_hessian,
data_size_t num_data,
const ConstraintEntry& constraints,
double min_gain_shift, SplitInfo* output,
int rand_threshold) {
void FindBestThresholdSequentially(double sum_gradient, double sum_hessian,
data_size_t num_data,
const ConstraintEntry& constraints,
double min_gain_shift, SplitInfo* output,
int rand_threshold) {
const int8_t offset = meta_->offset;
double best_sum_left_gradient = NAN;
double best_sum_left_hessian = NAN;
......
Markdown is supported
0% or .
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment