[Test Stability] PR to Test BinaryClassifierSymSgdTest

config.json

@@ -92,14 +92,14 @@
     },
     "RunNightlyBuildTests": {
       "description": "MsBuild target that run the nightly build tests. Call this after building.",
-        "valueType": "target",
-        "values": [],
-        "defaultValue": ""
+      "valueType": "target",
+      "values": [],
+      "defaultValue": ""
     },
     "Coverage": {
       "description": "Turn on code coverge.",
       "valueType": "property",
-      "values": ["false", "true"],
+      "values": [ "false", "true" ],
       "defaultValue": "false"
     },
     "CleanAllProjects": {

test/BaselineOutput/Common/SymSGD/SymSGD-CV-breast-cancer-out.txt

@@ -2,7 +2,7 @@ maml.exe CV tr=SymSGD{nt=1} threads=- norm=No dout=%Output% data=%Data% seed=1
 Not adding a normalizer.
 Data fully loaded into memory.
 Initial learning rate is tuned to 100.000000
-Bias: -467.9297, Weights: [5.415065,76.39395,22.35155,-11.98839,-28.26446,44.58415,22.72012,11.13254,2.851256]
+Bias: -468.3528, Weights: [4.515409,75.74901,22.2914,-10.50209,-28.58107,44.81024,23.8734,13.20304,2.448269]
 Not training a calibrator because it is not needed.
 Not adding a normalizer.
 Data fully loaded into memory.
@@ -15,15 +15,15 @@ Confusion table
           ||======================
 PREDICTED || positive | negative | Recall
 TRUTH     ||======================
- positive ||      130 |        4 | 0.9701
+ positive ||      132 |        2 | 0.9851
  negative ||        8 |      212 | 0.9636
           ||======================
-Precision ||   0.9420 |   0.9815 |
-OVERALL 0/1 ACCURACY: 0.966102
+Precision ||   0.9429 |   0.9907 |
+OVERALL 0/1 ACCURACY: 0.971751
 LOG LOSS/instance:  Infinity
 Test-set entropy (prior Log-Loss/instance): 0.956998
 LOG-LOSS REDUCTION (RIG): -Infinity
-AUC:                0.990706
+AUC:                0.991045
 Warning: The predictor produced non-finite prediction values on 8 instances during testing. Possible causes: abnormal data or the predictor is numerically unstable.
 TEST POSITIVE RATIO:	0.3191 (105.0/(105.0+224.0))
 Confusion table
@@ -42,16 +42,16 @@ AUC:                0.963435
 
 OVERALL RESULTS
 ---------------------------------------
-AUC:                0.977070 (0.0136)
-Accuracy:           0.952656 (0.0134)
-Positive precision: 0.919613 (0.0224)
-Positive recall:    0.942217 (0.0279)
-Negative precision: 0.970470 (0.0110)
+AUC:                0.977240 (0.0138)
+Accuracy:           0.955481 (0.0163)
+Positive precision: 0.920027 (0.0228)
+Positive recall:    0.949680 (0.0354)
+Negative precision: 0.975057 (0.0156)
 Negative recall:    0.957265 (0.0064)
 Log-loss:           Infinity (NaN)
 Log-loss reduction: -Infinity (NaN)
-F1 Score:           0.930771 (0.0251)
-AUPRC:              0.964018 (0.0164)
+F1 Score:           0.934582 (0.0289)
+AUPRC:              0.964431 (0.0168)
 
 ---------------------------------------
 Physical memory usage(MB): %Number%

test/BaselineOutput/Common/SymSGD/SymSGD-CV-breast-cancer-rp.txt

@@ -1,4 +1,4 @@
 SymSGD
 AUC	Accuracy	Positive precision	Positive recall	Negative precision	Negative recall	Log-loss	Log-loss reduction	F1 Score	AUPRC	/nt	Learner Name	Train Dataset	Test Dataset	Results File	Run Time	Physical Memory	Virtual Memory	Command Line	Settings	
-0.97707	0.952656	0.919613	0.942217	0.97047	0.957265	Infinity	-Infinity	0.930771	0.964018	1	SymSGD	%Data%		%Output%	99	0	0	maml.exe CV tr=SymSGD{nt=1} threads=- norm=No dout=%Output% data=%Data% seed=1	/nt:1	
+0.97724	0.955481	0.920027	0.94968	0.975057	0.957265	Infinity	-Infinity	0.934582	0.964431	1	SymSGD	%Data%		%Output%	99	0	0	maml.exe CV tr=SymSGD{nt=1} threads=- norm=No dout=%Output% data=%Data% seed=1	/nt:1	
 

test/BaselineOutput/Common/SymSGD/SymSGD-CV-breast-cancer.linux-out.txt

@@ -0,0 +1,69 @@
+maml.exe CV tr=SymSGD{nt=1} threads=- norm=No dout=%Output% data=%Data% seed=1
+Not adding a normalizer.
+Data fully loaded into memory.
+Initial learning rate is tuned to 100.000000
+Bias: -465.74258, Weights: [10.088505,67.45707,18.099556,-11.573266,-32.295338,52.25842,17.802341,14.058811,-2.0404801]
+Not training a calibrator because it is not needed.
+Not adding a normalizer.
+Data fully loaded into memory.
+Initial learning rate is tuned to 100.000000
+Bias: -484.28625, Weights: [-12.7873125,140.42897,121.93798,37.52739,-129.81442,70.90551,-89.37083,81.64296,-32.327835]
+Not training a calibrator because it is not needed.
+Warning: The predictor produced non-finite prediction values on 8 instances during testing. Possible causes: abnormal data or the predictor is numerically unstable.
+TEST POSITIVE RATIO:	0.3785 (134.0/(134.0+220.0))
+Confusion table
+          ||======================
+PREDICTED || positive | negative | Recall
+TRUTH     ||======================
+ positive ||      130 |        4 | 0.9701
+ negative ||        7 |      213 | 0.9682
+          ||======================
+Precision ||   0.9489 |   0.9816 |
+OVERALL 0/1 ACCURACY: 0.968927
+LOG LOSS/instance:  Infinity
+Test-set entropy (prior Log-Loss/instance): 0.956998
+LOG-LOSS REDUCTION (RIG): -Infinity
+AUC:                0.990095
+Warning: The predictor produced non-finite prediction values on 8 instances during testing. Possible causes: abnormal data or the predictor is numerically unstable.
+TEST POSITIVE RATIO:	0.3191 (105.0/(105.0+224.0))
+Confusion table
+          ||======================
+PREDICTED || positive | negative | Recall
+TRUTH     ||======================
+ positive ||       96 |        9 | 0.9143
+ negative ||       11 |      213 | 0.9509
+          ||======================
+Precision ||   0.8972 |   0.9595 |
+OVERALL 0/1 ACCURACY: 0.939210
+LOG LOSS/instance:  Infinity
+Test-set entropy (prior Log-Loss/instance): 0.903454
+LOG-LOSS REDUCTION (RIG): -Infinity
+AUC:                0.963435
+
+OVERALL RESULTS
+---------------------------------------
+AUC:                0.976765 (0.0133)
+Accuracy:           0.954068 (0.0149)
+Positive precision: 0.923051 (0.0259)
+Positive recall:    0.942217 (0.0279)
+Negative precision: 0.970513 (0.0111)
+Negative recall:    0.959537 (0.0086)
+Log-loss:           Infinity (NaN)
+Log-loss reduction: -Infinity (NaN)
+F1 Score:           0.932535 (0.0269)
+AUPRC:              0.963544 (0.0159)
+
+---------------------------------------
+Physical memory usage(MB): %Number%
+Virtual memory usage(MB): %Number%
+%DateTime%	 Time elapsed(s): %Number%
+
+--- Progress log ---
+[1] 'Preprocessing' started.
+[1] 'Preprocessing' finished in %Time%.
+[2] 'Training' started.
+[2] 'Training' finished in %Time%.
+[3] 'Preprocessing #2' started.
+[3] 'Preprocessing #2' finished in %Time%.
+[4] 'Training #2' started.
+[4] 'Training #2' finished in %Time%.