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tianlh
LightGBM-DCU
Commits
2051223b
"python-package/vscode:/vscode.git/clone" did not exist on "80662618996431c222e6c92cbba7e784f8a935cd"
Commit
2051223b
authored
Mar 05, 2020
by
guolinke
Browse files
better naming
parent
77d92b7c
Changes
1
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1 changed file
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17 additions
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17 deletions
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-17
src/treelearner/feature_histogram.hpp
src/treelearner/feature_histogram.hpp
+17
-17
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src/treelearner/feature_histogram.hpp
View file @
2051223b
...
@@ -149,11 +149,11 @@ class FeatureHistogram {
...
@@ -149,11 +149,11 @@ class FeatureHistogram {
double
min_gain_shift
=
double
min_gain_shift
=
BeforeNumercal
<
USE_RAND
,
USE_L1
,
USE_MAX_OUTPUT
>
(
BeforeNumercal
<
USE_RAND
,
USE_L1
,
USE_MAX_OUTPUT
>
(
sum_gradient
,
sum_hessian
,
output
,
&
rand_threshold
);
sum_gradient
,
sum_hessian
,
output
,
&
rand_threshold
);
FindBestThresholdSequen
ce
<
USE_RAND
,
USE_MC
,
USE_L1
,
FindBestThresholdSequen
tially
<
USE_RAND
,
USE_MC
,
USE_L1
,
USE_MAX_OUTPUT
,
true
,
true
,
false
>
(
USE_MAX_OUTPUT
,
true
,
true
,
false
>
(
sum_gradient
,
sum_hessian
,
num_data
,
constraints
,
sum_gradient
,
sum_hessian
,
num_data
,
constraints
,
min_gain_shift
,
output
,
rand_threshold
);
min_gain_shift
,
output
,
rand_threshold
);
FindBestThresholdSequen
ce
<
USE_RAND
,
USE_MC
,
USE_L1
,
FindBestThresholdSequen
tially
<
USE_RAND
,
USE_MC
,
USE_L1
,
USE_MAX_OUTPUT
,
false
,
true
,
false
>
(
USE_MAX_OUTPUT
,
false
,
true
,
false
>
(
sum_gradient
,
sum_hessian
,
num_data
,
constraints
,
sum_gradient
,
sum_hessian
,
num_data
,
constraints
,
min_gain_shift
,
output
,
rand_threshold
);
min_gain_shift
,
output
,
rand_threshold
);
...
@@ -166,11 +166,11 @@ class FeatureHistogram {
...
@@ -166,11 +166,11 @@ class FeatureHistogram {
double
min_gain_shift
=
double
min_gain_shift
=
BeforeNumercal
<
USE_RAND
,
USE_L1
,
USE_MAX_OUTPUT
>
(
BeforeNumercal
<
USE_RAND
,
USE_L1
,
USE_MAX_OUTPUT
>
(
sum_gradient
,
sum_hessian
,
output
,
&
rand_threshold
);
sum_gradient
,
sum_hessian
,
output
,
&
rand_threshold
);
FindBestThresholdSequen
ce
<
USE_RAND
,
USE_MC
,
USE_L1
,
FindBestThresholdSequen
tially
<
USE_RAND
,
USE_MC
,
USE_L1
,
USE_MAX_OUTPUT
,
true
,
false
,
true
>
(
USE_MAX_OUTPUT
,
true
,
false
,
true
>
(
sum_gradient
,
sum_hessian
,
num_data
,
constraints
,
sum_gradient
,
sum_hessian
,
num_data
,
constraints
,
min_gain_shift
,
output
,
rand_threshold
);
min_gain_shift
,
output
,
rand_threshold
);
FindBestThresholdSequen
ce
<
USE_RAND
,
USE_MC
,
USE_L1
,
FindBestThresholdSequen
tially
<
USE_RAND
,
USE_MC
,
USE_L1
,
USE_MAX_OUTPUT
,
false
,
false
,
true
>
(
USE_MAX_OUTPUT
,
false
,
false
,
true
>
(
sum_gradient
,
sum_hessian
,
num_data
,
constraints
,
sum_gradient
,
sum_hessian
,
num_data
,
constraints
,
min_gain_shift
,
output
,
rand_threshold
);
min_gain_shift
,
output
,
rand_threshold
);
...
@@ -185,7 +185,7 @@ class FeatureHistogram {
...
@@ -185,7 +185,7 @@ class FeatureHistogram {
double
min_gain_shift
=
double
min_gain_shift
=
BeforeNumercal
<
USE_RAND
,
USE_L1
,
USE_MAX_OUTPUT
>
(
BeforeNumercal
<
USE_RAND
,
USE_L1
,
USE_MAX_OUTPUT
>
(
sum_gradient
,
sum_hessian
,
output
,
&
rand_threshold
);
sum_gradient
,
sum_hessian
,
output
,
&
rand_threshold
);
FindBestThresholdSequen
ce
<
USE_RAND
,
USE_MC
,
USE_L1
,
FindBestThresholdSequen
tially
<
USE_RAND
,
USE_MC
,
USE_L1
,
USE_MAX_OUTPUT
,
true
,
false
,
false
>
(
USE_MAX_OUTPUT
,
true
,
false
,
false
>
(
sum_gradient
,
sum_hessian
,
num_data
,
constraints
,
sum_gradient
,
sum_hessian
,
num_data
,
constraints
,
min_gain_shift
,
output
,
rand_threshold
);
min_gain_shift
,
output
,
rand_threshold
);
...
@@ -198,7 +198,7 @@ class FeatureHistogram {
...
@@ -198,7 +198,7 @@ class FeatureHistogram {
double
min_gain_shift
=
double
min_gain_shift
=
BeforeNumercal
<
USE_RAND
,
USE_L1
,
USE_MAX_OUTPUT
>
(
BeforeNumercal
<
USE_RAND
,
USE_L1
,
USE_MAX_OUTPUT
>
(
sum_gradient
,
sum_hessian
,
output
,
&
rand_threshold
);
sum_gradient
,
sum_hessian
,
output
,
&
rand_threshold
);
FindBestThresholdSequen
ce
<
USE_RAND
,
USE_MC
,
USE_L1
,
FindBestThresholdSequen
tially
<
USE_RAND
,
USE_MC
,
USE_L1
,
USE_MAX_OUTPUT
,
true
,
false
,
false
>
(
USE_MAX_OUTPUT
,
true
,
false
,
false
>
(
sum_gradient
,
sum_hessian
,
num_data
,
constraints
,
sum_gradient
,
sum_hessian
,
num_data
,
constraints
,
min_gain_shift
,
output
,
rand_threshold
);
min_gain_shift
,
output
,
rand_threshold
);
...
@@ -769,7 +769,7 @@ class FeatureHistogram {
...
@@ -769,7 +769,7 @@ class FeatureHistogram {
template
<
bool
USE_RAND
,
bool
USE_MC
,
bool
USE_L1
,
bool
USE_MAX_OUTPUT
,
template
<
bool
USE_RAND
,
bool
USE_MC
,
bool
USE_L1
,
bool
USE_MAX_OUTPUT
,
bool
REVERSE
,
bool
SKIP_DEFAULT_BIN
,
bool
NA_AS_MISSING
>
bool
REVERSE
,
bool
SKIP_DEFAULT_BIN
,
bool
NA_AS_MISSING
>
void
FindBestThresholdSequen
ce
(
double
sum_gradient
,
double
sum_hessian
,
void
FindBestThresholdSequen
tially
(
double
sum_gradient
,
double
sum_hessian
,
data_size_t
num_data
,
data_size_t
num_data
,
const
ConstraintEntry
&
constraints
,
const
ConstraintEntry
&
constraints
,
double
min_gain_shift
,
SplitInfo
*
output
,
double
min_gain_shift
,
SplitInfo
*
output
,
...
...
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