Enables FastTreeHighMinDocsTest (dotnet#228)

* Test Enabled, Zbaseline files added

Author: Anipik

ZBaselines/SingleDebug/FastTreeBinaryClassification/FastTreeHighMinDocs-TrainTest-breast-cancer-out.txt

@@ -0,0 +1,55 @@
+maml.exe TrainTest test=%Data% tr=FastTreeBinaryClassification{mil=10000 iter=5} cache=- dout=%Output% loader=Text{sparse- col=Attr:TX:6 col=Label:0 col=Features:1-5,6,7-9} data=%Data% out=%Output% seed=1
+Not adding a normalizer.
+Making per-feature arrays
+Changing data from row-wise to column-wise
+Warning: Skipped 16 instances with missing features during training
+Processed 683 instances
+Binning and forming Feature objects
+Reserved memory for tree learner: 468 bytes
+Starting to train ...
+Warning: 5 of the boosting iterations failed to grow a tree. This is commonly because the minimum documents in leaf hyperparameter was set too high for this dataset.
+Not training a calibrator because it is not needed.
+TEST POSITIVE RATIO:	0.3448 (241.0/(241.0+458.0))
+Confusion table
+          ||======================
+PREDICTED || positive | negative | Recall
+TRUTH     ||======================
+ positive ||        0 |      241 | 0.0000
+ negative ||        0 |      458 | 1.0000
+          ||======================
+Precision ||   0.0000 |   0.6552 |
+OVERALL 0/1 ACCURACY: 0.655222
+LOG LOSS/instance:  1.000000
+Test-set entropy (prior Log-Loss/instance): 0.929318
+LOG-LOSS REDUCTION (RIG): -7.605800
+AUC:                0.500000
+
+OVERALL RESULTS
+---------------------------------------
+AUC:                0.500000 (0.0000)
+Accuracy:           0.655222 (0.0000)
+Positive precision: 0.000000 (0.0000)
+Positive recall:    0.000000 (0.0000)
+Negative precision: 0.655222 (0.0000)
+Negative recall:    1.000000 (0.0000)
+Log-loss:           1.000000 (0.0000)
+Log-loss reduction: -7.605800 (0.0000)
+F1 Score:               NaN (0.0000)
+AUPRC:              0.415719 (0.0000)
+
+---------------------------------------
+Physical memory usage(MB): %Number%
+Virtual memory usage(MB): %Number%
+%DateTime%	 Time elapsed(s): %Number%
+
+--- Progress log ---
+[1] 'FastTree data preparation' started.
+[1] 'FastTree data preparation' finished in %Time%.
+[2] 'FastTree in-memory bins initialization' started.
+[2] 'FastTree in-memory bins initialization' finished in %Time%.
+[3] 'FastTree feature conversion' started.
+[3] 'FastTree feature conversion' finished in %Time%.
+[4] 'FastTree training' started.
+[4] 'FastTree training' finished in %Time%.
+[5] 'Saving model' started.
+[5] 'Saving model' finished in %Time%.

ZBaselines/SingleDebug/FastTreeBinaryClassification/FastTreeHighMinDocs-TrainTest-breast-cancer-rp.txt

@@ -0,0 +1,4 @@
+FastTreeBinaryClassification
+AUC	Accuracy	Positive precision	Positive recall	Negative precision	Negative recall	Log-loss	Log-loss reduction	F1 Score	AUPRC	/mil	/iter	Learner Name	Train Dataset	Test Dataset	Results File	Run Time	Physical Memory	Virtual Memory	Command Line	Settings	
+0.5	0.655222	0	0	0.655222	1	1	-7.6058	NaN	0.415719	10000	5	FastTreeBinaryClassification	%Data%	%Data%	%Output%	99	0	0	maml.exe TrainTest test=%Data% tr=FastTreeBinaryClassification{mil=10000 iter=5} cache=- dout=%Output% loader=Text{sparse- col=Attr:TX:6 col=Label:0 col=Features:1-5,6,7-9} data=%Data% out=%Output% seed=1	/mil:10000;/iter:5	
+