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michaelgsharpmichaelgsharp
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Updates LightGBM from 2.X.X to 3.X.X (#6880)
* updated lightGBM version * finished LightGBM baseline update * removed accidental enums * Fixed LightGBM Test * fixed lightgbm * fixed version * fixed test with LightGBM * fixed test result
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‎eng/Versions.props

+3-3
Original file line numberDiff line numberDiff line change
@@ -24,7 +24,7 @@
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<SystemConfigurationConfigurationManagerVersion>6.0.1</SystemConfigurationConfigurationManagerVersion>
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<SystemIOFileSystemAccessControl>4.5.0</SystemIOFileSystemAccessControl>
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<SystemMemoryVersion>4.5.5</SystemMemoryVersion>
27-
<SystemNumericsTensorsVersion>8.0.0-rtm.23523.3</SystemNumericsTensorsVersion>
27+
<SystemNumericsTensorsVersion>8.0.0</SystemNumericsTensorsVersion>
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<SystemReflectionEmitLightweightVersion>4.3.0</SystemReflectionEmitLightweightVersion>
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<SystemReflectionEmitVersion>4.3.0</SystemReflectionEmitVersion>
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<SystemRuntimeCompilerServicesUnsafeVersion>6.0.0</SystemRuntimeCompilerServicesUnsafeVersion>
@@ -35,7 +35,7 @@
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<!-- Other product dependencies -->
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<ApacheArrowVersion>11.0.0</ApacheArrowVersion>
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<GoogleProtobufVersion>3.19.6</GoogleProtobufVersion>
38-
<LightGBMVersion>2.3.1</LightGBMVersion>
38+
<LightGBMVersion>3.3.5</LightGBMVersion>
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<MicrosoftCodeAnalysisAnalyzersVersion>3.3.0</MicrosoftCodeAnalysisAnalyzersVersion>
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<MicrosoftCodeAnalysisCSharpVersion>3.9.0</MicrosoftCodeAnalysisCSharpVersion>
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<MicrosoftDotNetInteractiveVersion>1.0.0-beta.23509.3</MicrosoftDotNetInteractiveVersion>
@@ -88,7 +88,7 @@
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<MicrosoftMLTensorFlowTestModelsVersion>0.0.13-test</MicrosoftMLTensorFlowTestModelsVersion>
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<MicrosoftMLTestDatabasesVersion>0.0.6-test</MicrosoftMLTestDatabasesVersion>
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<MicrosoftMLTestModelsVersion>0.0.7-test</MicrosoftMLTestModelsVersion>
91-
<SystemDataSqlClientVersion>4.6.1</SystemDataSqlClientVersion>
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<SystemDataSqlClientVersion>4.8.5</SystemDataSqlClientVersion>
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<SystemDataSQLiteCoreVersion>1.0.118</SystemDataSQLiteCoreVersion>
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<XunitCombinatorialVersion>1.2.7</XunitCombinatorialVersion>
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<XUnitVersion>2.4.2</XUnitVersion>

‎src/Microsoft.ML.LightGbm/WrappedLightGbmBooster.cs

+2-2
Original file line numberDiff line numberDiff line change
@@ -80,14 +80,14 @@ internal unsafe string GetModelString()
8080
byte[] buffer = new byte[bufLen];
8181
int size = 0;
8282
fixed (byte* ptr = buffer)
83-
LightGbmInterfaceUtils.Check(WrappedLightGbmInterface.BoosterSaveModelToString(Handle, 0, BestIteration, bufLen, ref size, ptr));
83+
LightGbmInterfaceUtils.Check(WrappedLightGbmInterface.BoosterSaveModelToString(Handle, 0, BestIteration, 0, bufLen, ref size, ptr));
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// If buffer size is not enough, reallocate buffer and get again.
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if (size > bufLen)
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{
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bufLen = size;
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buffer = new byte[bufLen];
8989
fixed (byte* ptr = buffer)
90-
LightGbmInterfaceUtils.Check(WrappedLightGbmInterface.BoosterSaveModelToString(Handle, 0, BestIteration, bufLen, ref size, ptr));
90+
LightGbmInterfaceUtils.Check(WrappedLightGbmInterface.BoosterSaveModelToString(Handle, 0, BestIteration, 0, bufLen, ref size, ptr));
9191
}
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byte[] content = new byte[size];
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Array.Copy(buffer, content, size);

‎src/Microsoft.ML.LightGbm/WrappedLightGbmInterface.cs

+2-1
Original file line numberDiff line numberDiff line change
@@ -190,6 +190,7 @@ public static extern int BoosterCreate(SafeDataSetHandle trainset,
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public static extern unsafe int BoosterSaveModelToString(SafeBoosterHandle handle,
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int startIteration,
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int numIteration,
193+
int featureImportanceType,
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int bufferLen,
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ref int outLen,
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byte* outStr);
@@ -213,7 +214,7 @@ public static extern unsafe int BoosterGetEval(SafeBoosterHandle handle, int dat
213214
#region API predict
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[DllImport(DllName, EntryPoint = "LGBM_BoosterPredictForMat", CallingConvention = CallingConvention.StdCall)]
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public static extern unsafe int BoosterPredictForMat(SafeBoosterHandle handle, IntPtr data, CApiDType dataType, int nRow, int nCol, int isRowMajor,
216-
int predictType, int numIteration, [MarshalAs(UnmanagedType.LPStr)] string parameters, ref int outLen, double* outResult);
217+
int predictType, int startIteration, int numIteration, [MarshalAs(UnmanagedType.LPStr)] string parameters, ref int outLen, double* outResult);
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#endregion
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#region API parallel

‎test/BaselineOutput/Common/FeatureContribution/LightGbmBinary.tsv

+4-4
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@@ -12,7 +12,7 @@
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#@ col=FeatureContributions:R4:32-37
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#@ col=FeatureContributions:R4:38-43
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#@ }
15-
950 757 692 720 297 7515 1 1 950 757 692 720 297 7515 0.956696868 0.760804 0.7872582 0.754716933 0.297893673 0.7578661 0.0871070847 0.116535939 0 0 0 1 18 4:-1 10:-0.0126099735 11:1 16:-0.262451649 17:20.81302
16-
459 961 0 659 274 2147 0 0 459 961 0 659 274 2147 0.462235659 0.965829134 0 0.690775633 0.27482447 0.21651876 24 1:1 6:-0.0739851445 9:-0.0561627634 11:-1 13:0.103110082 17:-1 19:2.238687 23:-21.7116222
17-
672 275 0 65 195 9818 1 1 672 275 0 65 195 9818 0.6767372 0.2763819 0 0.06813417 0.195586756 0.990116954 24 0:0.09341861 5:1 7:-0.99999994 10:-0.267225862 13:-0.0506075844 17:1 19:-0.9821341 23:19.4068565
18-
186 301 0 681 526 1456 0 0 186 301 0 681 526 1456 0.187311172 0.302512556 0 0.713836432 0.527582765 0.1468334 24 4:1 6:-0.0786664 9:-0.05971634 11:-1 16:0.0128529193 17:-1 22:0.262451649 23:-20.4196148
15+
950 757 692 720 297 7515 1 1 950 757 692 720 297 7515 0.95669687 0.760804 0.7872582 0.75471693 0.29789367 0.7578661 0.048468035 0.15627365 0 0 0 1 18 3:-1 4:-0.86065125 9:-0.008285429 11:1 15:-0.1600628 17:19.318588
16+
459 961 0 659 274 2147 0 0 459 961 0 659 274 2147 0.46223566 0.96582913 0 0.69077563 0.27482447 0.21651876 24 1:1 6:-0.10307922 9:-0.03593468 11:-0.99999994 13:0.069840066 17:-0.99999994 19:1.518843 23:-21.747446
17+
672 275 0 65 195 9818 1 1 672 275 0 65 195 9818 0.6767372 0.2763819 0 0.06813417 0.19558676 0.99011695 0.051555283 0 0 0.008813183 0 1 18 1:-1 4:-0.08602048 7:-0.08817758 11:1 13:-1.6014589 17:18.161747
18+
186 301 0 681 526 1456 0 0 186 301 0 681 526 1456 0.18731117 0.30251256 0 0.71383643 0.52758276 0.1468334 24 4:1 6:-0.13100865 7:-0.05215903 11:-1 16:0.006898874 17:-1 22:0.13775826 23:-19.968224

‎test/BaselineOutput/Common/FeatureContribution/LightGbmRanking.tsv

+4-4
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@@ -13,7 +13,7 @@
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#@ col=FeatureContributions:R4:33-38
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#@ col=FeatureContributions:R4:39-44
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#@ }
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950 757 692 720 297 7515 4 1 0 950 757 692 720 297 7515 0.956696868 0.760804 0.7872582 0.754716933 0.297893673 0.7578661 24 3:0.383134037 5:1 6:-0.9192525 10:-1 16:-0.2646893 17:1 22:-0.5723001 23:2.162158
17-
459 961 0 659 274 2147 1 1 0 459 961 0 659 274 2147 0.462235659 0.965829134 0 0.690775633 0.27482447 0.21651876 1 0.164955541 0 0.08735034 0 0 18 5:-1 6:0.110308476 11:-1 12:1.25388193 17:-11.36705
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672 275 0 65 195 9818 4 1 0 672 275 0 65 195 9818 0.6767372 0.2763819 0 0.06813417 0.195586756 0.990116954 24 0:0.0193515085 5:1 9:-0.902932465 10:-0.99999994 16:-0.1030465 17:1 22:-0.7474492 23:7.253514
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186 301 0 681 526 1456 0 1 0 186 301 0 681 526 1456 0.187311172 0.302512556 0 0.713836432 0.527582765 0.1468334 24 3:0.99999994 6:-0.0397184677 7:-0.0161588676 11:-1 15:0.008556744 17:-1 21:0.109527007 23:-12.8000793
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950 757 692 720 297 7515 4 1 0 950 757 692 720 297 7515 0.95669687 0.760804 0.7872582 0.75471693 0.29789367 0.7578661 0.18475686 0.19982447 0 0 0 1 18 3:-0.12083593 4:-1 10:-0.16583169 11:1 16:-0.2693773 17:1.6244018
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459 961 0 659 274 2147 1 1 0 459 961 0 659 274 2147 0.46223566 0.96582913 0 0.69077563 0.27482447 0.21651876 24 0:1 7:-0.021717148 9:-0.029168284 11:-1 12:0.09023979 17:-1 18:1.0248182 23:-11.35661
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672 275 0 65 195 9818 4 1 0 672 275 0 65 195 9818 0.6767372 0.2763819 0 0.06813417 0.19558676 0.99011695 0.036158063 0 0 0 0 1 0 -1 0 -0.50675523 -0.4690159 0 12 1:-0.06919657 5:1 7:-0.57434577 11:8.300206
19+
186 301 0 681 526 1456 0 1 0 186 301 0 681 526 1456 0.18731117 0.30251256 0 0.71383643 0.52758276 0.1468334 24 0:0.81803715 1:1 9:-0.027629191 11:-0.99999994 13:0.02057122 17:-0.99999994 19:0.24663319 23:-11.989234

‎test/BaselineOutput/Common/FeatureContribution/LightGbmRegressionWithCategoricalSplit.tsv

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@@ -23,7 +23,7 @@
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#@ col=FeatureContributions:R4:47-55
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#@ col=FeatureContributions:R4:56-64
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#@ }
26-
CMT 1 1 0.7088812 1271 1.64874518 3.8 1.0118916 CRD 17.5 17.5 0 1 0 1 0 0 1 0 0 1 1 0 1 0 0 0.7088812 1.64874518 1.0118916 36 4:0.107879594 7:0.725665748 8:1 15:-1 24:-0.0418495 26:1 33:-0.370121539 35:8.844109
27-
CMT 1 1 0.7088812 474 0.6148743 1.5 0.3994309 CRD 8 8 0 1 0 1 0 0 1 0 0 1 1 0 1 0 0 0.7088812 0.6148743 0.3994309 36 4:1 15:-0.0364986733 16:-0.847436965 17:-1 22:0.011381451 26:-1 31:0.115415707 35:-10.1406841
28-
CMT 1 1 0.7088812 637 0.8263184 1.4 0.372802168 CRD 8.5 8.5 0 1 0 1 0 0 1 0 0 1 1 0 1 0 0 0.7088812 0.8263184 0.372802168 36 4:1 15:-0.0366709046 16:-0.5593253 17:-1 22:0.0182117485 26:-1 31:0.183812216 35:-10.0930576
29-
CMT 1 1 0.7088812 181 0.234793767 0.6 0.159772366 CSH 4.5 4.5 0 1 0 1 0 1 0 1 0 1 1 0 0 1 0 0.7088812 0.234793767 0.159772366 36 6:1 13:-0.293414325 16:-0.7202999 17:-1 24:0.0291313324 26:-1 33:0.33991462 35:-11.6683512
26+
CMT 1 1 0.7088812 1271 1.6487452 3.8 1.0118916 CRD 17.5 17.5 0 1 0 1 0 0 1 0 0 1 1 0 1 0 0 0.7088812 1.6487452 1.0118916 36 4:0.09394213 7:0.71750724 8:1 26:1 35:9.400241
27+
CMT 1 1 0.7088812 474 0.6148743 1.5 0.3994309 CRD 8 8 0 1 0 1 0 0 1 0 0 1 1 0 1 0 0 0.7088812 0.6148743 0.3994309 36 4:1 12:-0.15849221 16:-0.80323946 17:-1 22:0.24369338 26:-1 31:2.1028545 35:-8.6291
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CMT 1 1 0.7088812 637 0.8263184 1.4 0.37280217 CRD 8.5 8.5 0 1 0 1 0 0 1 0 0 1 1 0 1 0 0 0.7088812 0.8263184 0.37280217 36 4:1 12:-0.15364607 16:-0.37586385 17:-1 22:0.22522934 26:-1 31:1.9944918 35:-8.855382
29+
CMT 1 1 0.7088812 181 0.23479377 0.6 0.15977237 CSH 4.5 4.5 0 1 0 1 0 1 0 1 0 1 1 0 0 1 0 0.7088812 0.23479377 0.15977237 36 3:1 13:-0.8467557 16:-0.7164732 17:-1 21:0.8161843 26:-1 30:8.588971 35:-10.523323

‎test/BaselineOutput/Common/LightGBM/LightGBMDart-CV-breast-cancer.dart-out.txt

+23-23
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@@ -12,42 +12,42 @@ Confusion table
1212
||======================
1313
PREDICTED || positive | negative | Recall
1414
TRUTH ||======================
15-
positive || 124 | 10 | 0.9254
15+
positive || 125 | 9 | 0.9328
1616
negative || 9 | 219 | 0.9605
1717
||======================
18-
Precision || 0.9323 | 0.9563 |
19-
OVERALL 0/1 ACCURACY: 0.947514
20-
LOG LOSS/instance: 0.303740
18+
Precision || 0.9328 | 0.9605 |
19+
OVERALL 0/1 ACCURACY: 0.950276
20+
LOG LOSS/instance: 0.298701
2121
Test-set entropy (prior Log-Loss/instance): 0.950799
22-
LOG-LOSS REDUCTION (RIG): 0.680543
23-
AUC: 0.984944
22+
LOG-LOSS REDUCTION (RIG): 0.685843
23+
AUC: 0.985271
2424
TEST POSITIVE RATIO: 0.3175 (107.0/(107.0+230.0))
2525
Confusion table
2626
||======================
2727
PREDICTED || positive | negative | Recall
2828
TRUTH ||======================
29-
positive || 97 | 10 | 0.9065
30-
negative || 10 | 220 | 0.9565
29+
positive || 99 | 8 | 0.9252
30+
negative || 8 | 222 | 0.9652
3131
||======================
32-
Precision || 0.9065 | 0.9565 |
33-
OVERALL 0/1 ACCURACY: 0.940653
34-
LOG LOSS/instance: 0.297583
32+
Precision || 0.9252 | 0.9652 |
33+
OVERALL 0/1 ACCURACY: 0.952522
34+
LOG LOSS/instance: 0.288593
3535
Test-set entropy (prior Log-Loss/instance): 0.901650
36-
LOG-LOSS REDUCTION (RIG): 0.669957
37-
AUC: 0.991833
36+
LOG-LOSS REDUCTION (RIG): 0.679928
37+
AUC: 0.992950
3838

3939
OVERALL RESULTS
4040
---------------------------------------
41-
AUC: 0.988388 (0.0034)
42-
Accuracy: 0.944083 (0.0034)
43-
Positive precision: 0.919436 (0.0129)
44-
Positive recall: 0.915958 (0.0094)
45-
Negative precision: 0.956427 (0.0001)
46-
Negative recall: 0.958524 (0.0020)
47-
Log-loss: 0.300661 (0.0031)
48-
Log-loss reduction: 0.675250 (0.0053)
49-
F1 Score: 0.917691 (0.0111)
50-
AUPRC: 0.972137 (0.0107)
41+
AUC: 0.989111 (0.0038)
42+
Accuracy: 0.951399 (0.0011)
43+
Positive precision: 0.929035 (0.0038)
44+
Positive recall: 0.929035 (0.0038)
45+
Negative precision: 0.962872 (0.0023)
46+
Negative recall: 0.962872 (0.0023)
47+
Log-loss: 0.293647 (0.0051)
48+
Log-loss reduction: 0.682885 (0.0030)
49+
F1 Score: 0.929035 (0.0038)
50+
AUPRC: 0.973375 (0.0114)
5151

5252
---------------------------------------
5353
Physical memory usage(MB): %Number%

‎test/BaselineOutput/Common/LightGBM/LightGBMDart-CV-breast-cancer.dart-rp.txt

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@@ -1,4 +1,4 @@
11
LightGBM
22
AUC Accuracy Positive precision Positive recall Negative precision Negative recall Log-loss Log-loss reduction F1 Score AUPRC /iter /lr /nl /mil /booster /nt Learner Name Train Dataset Test Dataset Results File Run Time Physical Memory Virtual Memory Command Line Settings
3-
0.988388 0.944083 0.919436 0.915958 0.956427 0.958524 0.300661 0.67525 0.917691 0.972137 10 0.2 20 10 dart 1 LightGBM %Data% %Output% 99 0 0 maml.exe CV tr=LightGBM{nt=1 iter=10 booster=dart lr=0.2 mil=10 nl=20} threads=- cache=- dout=%Output% loader=Text{sparse- col=Attr:TX:6 col=Label:0 col=Features:1-5,6,7-9} data=%Data% seed=1 /iter:10;/lr:0.2;/nl:20;/mil:10;/booster:dart;/nt:1
3+
0.989111 0.951399 0.929035 0.929035 0.962872 0.962872 0.293647 0.682885 0.929035 0.973375 10 0.2 20 10 dart 1 LightGBM %Data% %Output% 99 0 0 maml.exe CV tr=LightGBM{nt=1 iter=10 booster=dart lr=0.2 mil=10 nl=20} threads=- cache=- dout=%Output% loader=Text{sparse- col=Attr:TX:6 col=Label:0 col=Features:1-5,6,7-9} data=%Data% seed=1 /iter:10;/lr:0.2;/nl:20;/mil:10;/booster:dart;/nt:1
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