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AnipikTomFinley
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Enables RandomCalibratorPerceptronTest (#231)
* Test Enabled, added Debug and release zbaselines
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‎ZBaselines/SingleDebug/AveragedPerceptron/AveragedPerceptron-CV-breast-cancer.calibrateRandom-out.txt‎

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maml.exe CV threads=- numcali=200 dout=%Output% data=%Data% seed=1
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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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Warning: Skipped 8 instances with missing features during training (over 1 iterations; 8 inst/iter)
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Training calibrator.
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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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Warning: Skipped 8 instances with missing features during training (over 1 iterations; 8 inst/iter)
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Training calibrator.
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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
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||======================
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PREDICTED || positive | negative | Recall
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TRUTH ||======================
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positive || 132 | 2 | 0.9851
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negative || 9 | 211 | 0.9591
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||======================
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Precision || 0.9362 | 0.9906 |
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OVERALL 0/1 ACCURACY: 0.968927
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LOG LOSS/instance: 0.156405
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Test-set entropy (prior Log-Loss/instance): 0.956998
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LOG-LOSS REDUCTION (RIG): 83.656717
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AUC: 0.992809
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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))
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Confusion table
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||======================
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PREDICTED || positive | negative | Recall
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TRUTH ||======================
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positive || 102 | 3 | 0.9714
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negative || 4 | 220 | 0.9821
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||======================
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Precision || 0.9623 | 0.9865 |
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OVERALL 0/1 ACCURACY: 0.978723
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LOG LOSS/instance: 0.130063
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Test-set entropy (prior Log-Loss/instance): 0.903454
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LOG-LOSS REDUCTION (RIG): 85.603819
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AUC: 0.997279
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OVERALL RESULTS
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---------------------------------------
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AUC: 0.995044 (0.0022)
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Accuracy: 0.973825 (0.0049)
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Positive precision: 0.949217 (0.0130)
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Positive recall: 0.978252 (0.0068)
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Negative precision: 0.988579 (0.0020)
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Negative recall: 0.970617 (0.0115)
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Log-loss: 0.143234 (0.0132)
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Log-loss reduction: 84.630268 (0.9736)
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F1 Score: 0.963412 (0.0034)
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AUPRC: 0.990172 (0.0037)
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---------------------------------------
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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%
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‎ZBaselines/SingleDebug/AveragedPerceptron/AveragedPerceptron-CV-breast-cancer.calibrateRandom-rp.txt‎

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AveragedPerceptron
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AUC Accuracy Positive precision Positive recall Negative precision Negative recall Log-loss Log-loss reduction F1 Score AUPRC Learner Name Train Dataset Test Dataset Results File Run Time Physical Memory Virtual Memory Command Line Settings
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0.995044 0.973825 0.949217 0.978252 0.988579 0.970617 0.143234 84.63026 0.963412 0.990172 AveragedPerceptron %Data% %Output% 99 0 0 maml.exe CV threads=- numcali=200 dout=%Output% data=%Data% seed=1
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‎ZBaselines/SingleDebug/AveragedPerceptron/AveragedPerceptron-CV-breast-cancer.calibrateRandom.txt‎

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‎ZBaselines/SingleDebug/AveragedPerceptron/AveragedPerceptron-CV-breast-cancer.nocalibration-out.txt‎

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maml.exe CV threads=- cali={} dout=%Output% data=%Data% seed=1
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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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Warning: Skipped 8 instances with missing features during training (over 1 iterations; 8 inst/iter)
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Not training a calibrator because a valid calibrator trainer was not provided.
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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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Warning: Skipped 8 instances with missing features during training (over 1 iterations; 8 inst/iter)
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Not training a calibrator because a valid calibrator trainer was not provided.
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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
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||======================
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PREDICTED || positive | negative | Recall
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TRUTH ||======================
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positive || 132 | 2 | 0.9851
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negative || 9 | 211 | 0.9591
18+
||======================
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Precision || 0.9362 | 0.9906 |
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OVERALL 0/1 ACCURACY: 0.968927
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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): 0.000000
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AUC: 0.992809
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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))
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Confusion table
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||======================
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PREDICTED || positive | negative | Recall
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TRUTH ||======================
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positive || 102 | 3 | 0.9714
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negative || 4 | 220 | 0.9821
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||======================
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Precision || 0.9623 | 0.9865 |
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OVERALL 0/1 ACCURACY: 0.978723
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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): 0.000000
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AUC: 0.997279
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OVERALL RESULTS
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---------------------------------------
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AUC: 0.995044 (0.0022)
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Accuracy: 0.973825 (0.0049)
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Positive precision: 0.949217 (0.0130)
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Positive recall: 0.978252 (0.0068)
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Negative precision: 0.988579 (0.0020)
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Negative recall: 0.970617 (0.0115)
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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: 0.963412 (0.0034)
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AUPRC: 0.990172 (0.0037)
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---------------------------------------
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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%
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‎ZBaselines/SingleDebug/AveragedPerceptron/AveragedPerceptron-CV-breast-cancer.nocalibration-rp.txt‎

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AveragedPerceptron
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AUC Accuracy Positive precision Positive recall Negative precision Negative recall Log-loss Log-loss reduction F1 Score AUPRC Learner Name Train Dataset Test Dataset Results File Run Time Physical Memory Virtual Memory Command Line Settings
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0.995044 0.973825 0.949217 0.978252 0.988579 0.970617 NaN 0 0.963412 0.990172 AveragedPerceptron %Data% %Output% 99 0 0 maml.exe CV threads=- cali={} dout=%Output% data=%Data% seed=1
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