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Update workflow.py #2

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Update workflow.py #2

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yaronha
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@yaronha yaronha commented Jun 10, 2020

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yaronha commented Jun 10, 2020

/run

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Pipeline started id=0a9a9b38-fc9c-4577-8e1a-3cd1d5ada45f, commit=400a634

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Run Results

Workflow 0a9a9b38-fc9c-4577-8e1a-3cd1d5ada45f finished, status=Succeeded
click the hyper links below to see detailed results
uid start state name results artifacts
Jun 10 13:00:39 completed model-tester
total_tests=15
errors=0
match=14
avg_latency=7307
min_latency=5300
max_latency=8788
latency
Jun 10 13:00:28 completed test
rocauc=0.3333333333333333
avg_precscore=0.3673982494785104
accuracy=0.9333333333333333
f1_score=0.9333333333333333
roc
confusion
test_set_preds
Jun 10 13:00:12 completed train
best_iteration=2
rocauc=0.9945117845117846
accuracy=0.9705882352941176
f1_score=0.9705882352941176
test_set
roc
confusion
model
iteration_results
Jun 10 13:00:02 completed get-data
iris_dataset

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yaronha commented Jun 10, 2020

/run

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Pipeline started id=11a7da59-48f1-40fe-8d19-9dbf9b2cf20c, commit=12432a6

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Run Results

Workflow 11a7da59-48f1-40fe-8d19-9dbf9b2cf20c finished with 1 errors, status=Failed
click the hyper links below to see detailed results
uid start state name results artifacts
Jun 10 23:46:38
error
test
Jun 10 23:46:20 completed train
iteration_results
Jun 10 23:46:08 completed get-data
iris_dataset

@yaronha
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yaronha commented Jun 10, 2020

/run

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Pipeline started id=7c81a55a-c57e-48ed-9ed5-78dc81f52fa9, commit=12432a6

@github-actions
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Run Results

Workflow 7c81a55a-c57e-48ed-9ed5-78dc81f52fa9 finished, status=Succeeded
click the hyper links below to see detailed results
uid start state name results artifacts
Jun 10 23:52:51 completed model-tester
total_tests=15
errors=0
match=14
avg_latency=12531
min_latency=11974
max_latency=13549
latency
Jun 10 23:52:27 completed test
accuracy=0.9333333333333333
test-error=0.06666666666666667
auc-micro=0.9622222222222221
auc-weighted=0.9888888888888889
f1-score=0.9137254901960784
precision_score=0.8888888888888888
recall_score=0.9629629629629629
confusion-matrix
feature-importances
precision-recall-multiclass
roc-multiclass
test_set_preds
Jun 10 23:52:10 completed train
best_iteration=1
accuracy=0.9705882352941176
test-error=0.029411764705882353
auc-micro=0.9969723183391004
auc-weighted=0.9949732620320856
f1-score=0.9679633867276888
precision_score=0.9666666666666667
recall_score=0.9722222222222222
test_set
confusion-matrix
feature-importances
precision-recall-multiclass
roc-multiclass
model
iteration_results
Jun 10 23:51:58 completed get-data
iris_dataset

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