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Update release test files
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‎test/BaselineOutput/SingleRelease/SDCA/BinarySDCA-SmoothedHinge-CV-breast-cancer-out.txt

Lines changed: 10 additions & 8 deletions
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@@ -3,12 +3,14 @@ Automatically adding a MinMax normalization transform, use 'norm=Warn' or 'norm=
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Using 1 thread to train.
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Warning: Skipped 8 instances with missing features/label during training
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Using model from last iteration.
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Training calibrator.
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Not training a calibrator because it is not needed.
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Warning: Data does not contain a probability column. Will not output the Log-loss column
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Automatically adding a MinMax normalization transform, use 'norm=Warn' or 'norm=No' to turn this behavior off.
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Using 1 thread to train.
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Warning: Skipped 8 instances with missing features/label during training
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Using model from last iteration.
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Training calibrator.
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Not training a calibrator because it is not needed.
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Warning: Data does not contain a probability column. Will not output the Log-loss column
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Warning: The predictor produced non-finite prediction values on 8 instances during testing. Possible causes: abnormal data or the predictor is numerically unstable.
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TEST POSITIVE RATIO: 0.3785 (134.0/(134.0+220.0))
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Confusion table
@@ -20,9 +22,9 @@ TRUTH ||======================
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||======================
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Precision || 0.9420 | 0.9815 |
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OVERALL 0/1 ACCURACY: 0.966102
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LOG LOSS/instance: 0.129889
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LOG LOSS/instance: NaN
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Test-set entropy (prior Log-Loss/instance): 0.956998
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LOG-LOSS REDUCTION (RIG): 86.427410
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LOG-LOSS REDUCTION (RIG): 0.000000
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AUC: 0.994539
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Warning: The predictor produced non-finite prediction values on 8 instances during testing. Possible causes: abnormal data or the predictor is numerically unstable.
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TEST POSITIVE RATIO: 0.3191 (105.0/(105.0+224.0))
@@ -35,9 +37,9 @@ TRUTH ||======================
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||======================
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Precision || 1.0000 | 0.7698 |
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OVERALL 0/1 ACCURACY: 0.796353
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LOG LOSS/instance: 0.126797
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LOG LOSS/instance: NaN
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Test-set entropy (prior Log-Loss/instance): 0.903454
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LOG-LOSS REDUCTION (RIG): 85.965336
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LOG-LOSS REDUCTION (RIG): 0.000000
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AUC: 0.996854
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OVERALL RESULTS
@@ -48,8 +50,8 @@ Positive precision: 0.971014 (0.0290)
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Positive recall: 0.666027 (0.3041)
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Negative precision: 0.875620 (0.1059)
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Negative recall: 0.981818 (0.0182)
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Log-loss: 0.128343 (0.0015)
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Log-loss reduction: 86.196373 (0.2310)
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Log-loss: NaN (NaN)
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Log-loss reduction: 0.000000 (0.0000)
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F1 Score: 0.743675 (0.2122)
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AUPRC: 0.991479 (0.0016)
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‎test/BaselineOutput/SingleRelease/SDCA/BinarySDCA-SmoothedHinge-CV-breast-cancer-rp.txt

Lines changed: 1 addition & 1 deletion
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@@ -1,4 +1,4 @@
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SDCA
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AUC Accuracy Positive precision Positive recall Negative precision Negative recall Log-loss Log-loss reduction F1 Score AUPRC /loss /l2 /l1 /nt /iter /checkFreq Learner Name Train Dataset Test Dataset Results File Run Time Physical Memory Virtual Memory Command Line Settings
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0.995696 0.881227 0.971014 0.666027 0.87562 0.981818 0.128343 86.19637 0.743675 0.991479 SmoothedHinge 1E-06 0.5 1 5 9 SDCA %Data% %Output% 99 0 0 maml.exe CV tr=SDCA{l2=1e-06 loss=SmoothedHinge l1=0.5 maxIterations=5 checkFreq=9 nt=1} threads=- dout=%Output% data=%Data% seed=1 /loss:SmoothedHinge;/l2:1E-06;/l1:0.5;/nt:1;/iter:5;/checkFreq:9
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0.995696 0.881227 0.971014 0.666027 0.87562 0.981818 NaN 0 0.743675 0.991479 SmoothedHinge 1E-06 0.5 1 5 9 SDCA %Data% %Output% 99 0 0 maml.exe CV tr=SDCA{l2=1e-06 loss=SmoothedHinge l1=0.5 maxIterations=5 checkFreq=9 nt=1} threads=- dout=%Output% data=%Data% seed=1 /loss:SmoothedHinge;/l2:1E-06;/l1:0.5;/nt:1;/iter:5;/checkFreq:9
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‎test/BaselineOutput/SingleRelease/SDCA/BinarySDCA-SmoothedHinge-CV-breast-cancer.txt

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‎test/BaselineOutput/SingleRelease/SDCA/BinarySDCA-SmoothedHinge-TrainTest-breast-cancer-out.txt

Lines changed: 6 additions & 5 deletions
Original file line numberDiff line numberDiff line change
@@ -3,7 +3,7 @@ Automatically adding a MinMax normalization transform, use 'norm=Warn' or 'norm=
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Using 1 thread to train.
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Warning: Skipped 16 instances with missing features/label during training
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Using model from last iteration.
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Training calibrator.
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Not training a calibrator because it is not needed.
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Warning: The predictor produced non-finite prediction values on 16 instances during testing. Possible causes: abnormal data or the predictor is numerically unstable.
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TEST POSITIVE RATIO: 0.3499 (239.0/(239.0+444.0))
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Confusion table
@@ -15,9 +15,9 @@ TRUTH ||======================
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||======================
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Precision || 0.9655 | 0.9667 |
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OVERALL 0/1 ACCURACY: 0.966325
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LOG LOSS/instance: 0.118542
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LOG LOSS/instance: NaN
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Test-set entropy (prior Log-Loss/instance): 0.934003
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LOG-LOSS REDUCTION (RIG): 87.308128
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LOG-LOSS REDUCTION (RIG): 0.000000
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AUC: 0.995816
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OVERALL RESULTS
@@ -28,12 +28,13 @@ Positive precision: 0.965517 (0.0000)
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Positive recall: 0.937238 (0.0000)
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Negative precision: 0.966741 (0.0000)
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Negative recall: 0.981982 (0.0000)
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Log-loss: 0.118542 (0.0000)
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Log-loss reduction: 87.308128 (0.0000)
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Log-loss: NaN (0.0000)
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Log-loss reduction: 0.000000 (0.0000)
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F1 Score: 0.951168 (0.0000)
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AUPRC: 0.991045 (0.0000)
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---------------------------------------
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Warning: Data does not contain a probability column. Will not output the Log-loss column
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Physical memory usage(MB): %Number%
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Virtual memory usage(MB): %Number%
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%DateTime% Time elapsed(s): %Number%

‎test/BaselineOutput/SingleRelease/SDCA/BinarySDCA-SmoothedHinge-TrainTest-breast-cancer-rp.txt

Lines changed: 1 addition & 1 deletion
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@@ -1,4 +1,4 @@
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SDCA
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AUC Accuracy Positive precision Positive recall Negative precision Negative recall Log-loss Log-loss reduction F1 Score AUPRC /loss /l2 /l1 /nt /iter /checkFreq Learner Name Train Dataset Test Dataset Results File Run Time Physical Memory Virtual Memory Command Line Settings
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0.995816 0.966325 0.965517 0.937238 0.966741 0.981982 0.118542 87.30813 0.951168 0.991045 SmoothedHinge 1E-06 0.5 1 5 9 SDCA %Data% %Data% %Output% 99 0 0 maml.exe TrainTest test=%Data% tr=SDCA{l2=1e-06 loss=SmoothedHinge l1=0.5 maxIterations=5 checkFreq=9 nt=1} dout=%Output% data=%Data% out=%Output% seed=1 /loss:SmoothedHinge;/l2:1E-06;/l1:0.5;/nt:1;/iter:5;/checkFreq:9
3+
0.995816 0.966325 0.965517 0.937238 0.966741 0.981982 NaN 0 0.951168 0.991045 SmoothedHinge 1E-06 0.5 1 5 9 SDCA %Data% %Data% %Output% 99 0 0 maml.exe TrainTest test=%Data% tr=SDCA{l2=1e-06 loss=SmoothedHinge l1=0.5 maxIterations=5 checkFreq=9 nt=1} dout=%Output% data=%Data% out=%Output% seed=1 /loss:SmoothedHinge;/l2:1E-06;/l1:0.5;/nt:1;/iter:5;/checkFreq:9
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