Enable Conditional Numerical Reproducibility for tests (#4569)

* Enable Conditional Numerical Reproducibility for tests

* Update baselines for failing tests

* Skip BinaryClassifierSymSgdTest on Linux due to numerical differences

Author: sharwell

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: -468.3528, Weights: [4.515409,75.74901,22.2914,-10.50209,-28.58107,44.81024,23.8734,13.20304,2.448269]
+Bias: -467.9297, Weights: [5.415065,76.39395,22.35155,-11.98839,-28.26446,44.58415,22.72012,11.13254,2.851256]
 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 ||      132 |        2 | 0.9851
+ positive ||      130 |        4 | 0.9701
  negative ||        8 |      212 | 0.9636
           ||======================
-Precision ||   0.9429 |   0.9907 |
-OVERALL 0/1 ACCURACY: 0.971751
+Precision ||   0.9420 |   0.9815 |
+OVERALL 0/1 ACCURACY: 0.966102
 LOG LOSS/instance:  Infinity
 Test-set entropy (prior Log-Loss/instance): 0.956998
 LOG-LOSS REDUCTION (RIG): -Infinity
-AUC:                0.991045
+AUC:                0.990706
 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:                0.977240 (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)
+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)
 Negative recall:    0.957265 (0.0064)
 Log-loss:           Infinity (NaN)
 Log-loss reduction: -Infinity (NaN)
-F1 Score:           0.934582 (0.0289)
-AUPRC:              0.964431 (0.0168)
+F1 Score:           0.930771 (0.0251)
+AUPRC:              0.964018 (0.0164)
 
 ---------------------------------------
 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	
-0.97724	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	
+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