Bhrolenok3: Created page with "These test cases rely on a set of orders files, provided here: File:mc3p1_data_spr2016.zip

 learning_test_cases = [     LearningTestCase(         description="Test C..."

2016-04-23T04:16:03Z

Created page with "These test cases rely on a set of orders files, provided here: File:mc3p1_data_spr2016.zip <pre> learning_test_cases = [ LearningTestCase( description="Test C..."

New page

These test cases rely on a set of orders files, provided here:
[[File:mc3p1_data_spr2016.zip]]

<pre>
learning_test_cases = [
LearningTestCase(
description="Test Case 01",
group='KNNLearner',
inputs=dict(
train_file=os.path.join('Data', 'ripple.csv'),
test_file=os.path.join('Data', 'testcase01.csv')
),
outputs=dict(
rmse=6.08094194449e-17,
corr=1.0
)
),
LearningTestCase(
description="Test Case 01 - Noisy, 4 features",
group='KNNLearner',
inputs=dict(
train_file=os.path.join('Data', 'ripple_noisy.csv'),
test_file=os.path.join('Data', 'testcase01_noisy.csv')
),
outputs=dict(
rmse=0.568574577879,
corr=0.61379073821
)
),
LearningTestCase(
description="Test Case 03",
group='KNNLearner',
inputs=dict(
train_file=os.path.join('Data', 'ripple.csv'),
test_file=os.path.join('Data', 'testcase03.csv')
),
outputs=dict(
rmse=2.85197162452e-12,
corr=1.0
)
),
LearningTestCase(
description="Test Case 04",
group='KNNLearner',
inputs=dict(
train_file=os.path.join('Data', 'best4KNN.csv'),
test_file=os.path.join('Data', 'testcase04.csv')
),
outputs=dict(
rmse=0.00240027433274,
corr=0.999999987071
)
),
LearningTestCase(
description="Test Case 05",
group='KNNLearner',
inputs=dict(
train_file=os.path.join('Data', 'ripple.csv'),
test_file=os.path.join('Data', 'testcase05.csv')
),
outputs=dict(
rmse=0.359438468147,
corr=0.838279931481
)
),
LearningTestCase(
description="Test Case 06",
group='KNNLearner',
inputs=dict(
train_file=os.path.join('Data', '3_groups.csv'),
test_file=os.path.join('Data', 'testcase06.csv'),
kwargs={'k': 10}
),
outputs=dict(
rmse=35.1015004428,
corr=-0.208568812714
)
),
LearningTestCase(
description="Test Case 07",
group='KNNLearner',
inputs=dict(
train_file=os.path.join('Data', 'ripple.csv'),
test_file=os.path.join('Data', 'testcase07.csv')
),
outputs=dict(
rmse=0.918312680526,
corr=-0.119588294412
)
),
LearningTestCase(
description="Test Case 08",
group='KNNLearner',
inputs=dict(
train_file=os.path.join('Data', 'ripple.csv'),
test_file=os.path.join('Data', 'testcase08.csv')
),
outputs=dict(
rmse=0.0904271221715,
corr=0.988993695858
)
),
LearningTestCase(
description="Test Case 09",
group='KNNLearner',
inputs=dict(
train_file=os.path.join('Data', 'simple.csv'),
test_file=os.path.join('Data', 'testcase09.csv'),
kwargs={'k': 1}
),
outputs=dict(
rmse=0.0,
corr=1.0
)
),
LearningTestCase(
description="Test Case 10",
group='KNNLearner',
inputs=dict(
train_file=os.path.join('Data', 'ripple.csv'),
test_file=os.path.join('Data', 'testcase10.csv')
),
outputs=dict(
rmse=1.78531847475,
corr=-0.789236317359
)
),
LearningTestCase(
description="Test Case 01 - Bagging",
group='BagLearner',
inputs=dict(
train_file=os.path.join('Data', 'ripple.csv'),
test_file=os.path.join('Data', 'testcase01.csv')
),
outputs=dict(
rmse=0.102347955217,
corr=0.991328696155
)
),
LearningTestCase(
description="Test Case 02 - Bagging",
group='BagLearner',
inputs=dict(
train_file=os.path.join('Data', 'simple.csv'),
test_file=os.path.join('Data', 'testcase02.csv')
),
outputs=dict(
rmse=0.0894427191,
corr=0.99966144456
)
),
LearningTestCase(
description="Test Case 03 - Bagging",
group='BagLearner',
inputs=dict(
train_file=os.path.join('Data', 'ripple.csv'),
test_file=os.path.join('Data', 'testcase03.csv')
),
outputs=dict(
rmse=1.78531847475,
corr=-0.789236317359
)
),
LearningTestCase(
description="Test Case 04 - Bagging",
group='BagLearner',
inputs=dict(
train_file=os.path.join('Data', 'best4KNN.csv'),
test_file=os.path.join('Data', 'testcase04.csv')
),
outputs=dict(
rmse=0.0301204201819,
corr=0.999997608631
)
),
LearningTestCase(
description="Test Case 05 - Bagging",
group='BagLearner',
inputs=dict(
train_file=os.path.join('Data', 'ripple.csv'),
test_file=os.path.join('Data', 'testcase05.csv')
),
outputs=dict(
rmse=0.323579476488,
corr=0.867361902312
)
),
LearningTestCase(
description="Test Case 06 - Bagging",
group='BagLearner',
inputs=dict(
train_file=os.path.join('Data', '3_groups.csv'),
test_file=os.path.join('Data', 'testcase06.csv'),
kwargs={'kwargs': {'k': 1}, 'bags': 20, 'boost': False}
),
outputs=dict(
rmse=35.1014280336,
corr=-0.230388246034
)
),
LearningTestCase(
description="Test Case 07 - Bagging",
group='BagLearner',
inputs=dict(
train_file=os.path.join('Data', 'ripple.csv'),
test_file=os.path.join('Data', 'testcase07.csv'),
kwargs={'kwargs': {'k': 3}, 'bags': 20, 'boost': False}
),
outputs=dict(
rmse=0.912956660467,
corr=-0.112955082143
)
),
LearningTestCase(
description="Test Case 08 - Bagging",
group='BagLearner',
inputs=dict(
train_file=os.path.join('Data', 'ripple.csv'),
test_file=os.path.join('Data', 'testcase08.csv'),
kwargs={'kwargs': {'k': 3}, 'bags': 20, 'boost': False}
),
outputs=dict(
rmse=0.141072888643,
corr=0.971258408243
)
),
LearningTestCase(
description="Test Case 09 - Bagging",
group='BagLearner',
inputs=dict(
train_file=os.path.join('Data', 'simple.csv'),
test_file=os.path.join('Data', 'testcase09.csv'),
kwargs={'kwargs': {'k': 1}, 'bags': 20, 'boost': False}
),
outputs=dict(
rmse=0.0235702260396,
corr=0.999957755088
)
),
LearningTestCase(
description="Test Case 10 - Bagging, 5 bags",
group='BagLearner',
inputs=dict(
train_file=os.path.join('Data', 'ripple.csv'),
test_file=os.path.join('Data', 'testcase10.csv'),
kwargs={'kwargs': {'k': 3}, 'bags': 5, 'boost': False}
),
outputs=dict(
rmse=1.79642483731,
corr=-0.73463819703
)
)
]
</pre>

MC3-Project-1-Test-Cases-spr2016 - Revision history

Bhrolenok3: Created page with "These test cases rely on a set of orders files, provided here: File:mc3p1_data_spr2016.zip
learning_test_cases = [ LearningTestCase( description="Test C..."