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Enables FastTreeHighMinDocsTest #228

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May 24, 2018
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Enables FastTreeHighMinDocsTest #228

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Test Enabled
Anipik May 24, 2018
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Zbaseline files added
Anipik May 24, 2018
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55 changes: 55 additions & 0 deletions ...gleDebug/FastTreeBinaryClassification/FastTreeHighMinDocs-TrainTest-breast-cancer-out.txt
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Original file line number Diff line number Diff line change
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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%.
4 changes: 4 additions & 0 deletions ...ngleDebug/FastTreeBinaryClassification/FastTreeHighMinDocs-TrainTest-breast-cancer-rp.txt
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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

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