def test_experiment_boston(self):
papermill.execute_notebook(
"Experiment.ipynb",
"/dev/null",
parameters=dict(
dataset="/tmp/data/boston.csv",
target="medv",
filter_type="remover",
model_features="",
one_hot_features="",
kernel="rbf",
degree=3,
gamma="auto",
C=1.0,
max_iter=-1,
),
)
papermill.execute_notebook(
"Deployment.ipynb",
"/dev/null",
)
data = datasets.boston_testdata()
with server.Server() as s:
response = s.test(data=data)
names = response["names"]
ndarray = response["ndarray"]
self.assertEqual(len(ndarray[0]), 14) # 13 features + 1 prediction
self.assertEqual(len(names), 14)
def test_experiment_boston(self):
papermill.execute_notebook(
"Experiment.ipynb",
"/dev/null",
parameters=dict(
dataset="/tmp/data/boston.csv",
target="medv",
filter_type="remover",
model_features="",
one_hot_features="",
time_left_for_this_task=30,
per_run_time_limit=30,
ensemble_size=5,
),
)
papermill.execute_notebook(
"Deployment.ipynb",
"/dev/null",
)
data = datasets.boston_testdata()
with server.Server() as s:
response = s.test(data=data)
names = response["names"]
ndarray = response["ndarray"]
self.assertEqual(len(ndarray[0]), 14) # 13 features + 1 prediction
self.assertEqual(len(names), 14)
def test_experiment_boston(self):
papermill.execute_notebook(
"Experiment.ipynb",
"/dev/null",
parameters=dict(
dataset="/tmp/data/boston.csv",
target="medv",
filter_type="remover",
model_features="",
ordinal_features="",
fit_intercept=True,
),
)
papermill.execute_notebook(
"Deployment.ipynb",
"/dev/null",
)
data = datasets.boston_testdata()
with server.Server() as s:
response = s.test(data=data)
names = response["names"]
ndarray = response["ndarray"]
self.assertEqual(len(ndarray[0]), 14) # 13 features + 1 prediction
self.assertEqual(len(names), 14)
def test_experiment_boston(self):
papermill.execute_notebook(
"Experiment.ipynb",
"/dev/null",
parameters=dict(
dataset="/tmp/data/boston.csv",
filter_type = "remover",
model_features = "medv",
max_samples="auto",
contamination=0.1,
max_features=1.0,
),
)
papermill.execute_notebook(
"Deployment.ipynb",
"/dev/null",
)
data = datasets.boston_testdata()
with server.Server() as s:
response = s.test(data=data)
names = response["names"]
ndarray = response["ndarray"]
self.assertEqual(len(ndarray[0]), 14) # 13 features + 1 anomaly score
self.assertEqual(len(names), 14)
def test_experiment_boston(self):
papermill.execute_notebook(
"Experiment.ipynb",
"/dev/null",
parameters=dict(
dataset="/tmp/data/boston.csv",
target="medv",
strategy_num="mean",
strategy_cat="most_frequent",
fillvalue_num=0,
fillvalue_cat="",
),
)
papermill.execute_notebook(
"Deployment.ipynb",
"/dev/null",
)
data = datasets.boston_testdata()
with server.Server() as s:
response = s.test(data=data)
names = response["names"]
ndarray = response["ndarray"]
self.assertEqual(len(ndarray[0]), 13) # 13 features
self.assertEqual(len(names), 13)
def test_experiment_boston(self):
papermill.execute_notebook(
"Experiment.ipynb",
"/dev/null",
parameters=dict(
dataset="/tmp/data/boston.csv",
target="medv",
filter_type="remover",
model_features="",
one_hot_features="",
hidden_layer_sizes=100,
activation="relu",
solver="adam",
learning_rate="constant",
max_iter=200,
shuffle=True,
),
)
papermill.execute_notebook(
"Deployment.ipynb",
"/dev/null",
)
data = datasets.boston_testdata()
with server.Server() as s:
response = s.test(data=data)
names = response["names"]
ndarray = response["ndarray"]
self.assertEqual(len(ndarray[0]), 14) # 13 features + 1 prediction
self.assertEqual(len(names), 14)
def test_experiment_boston(self):
papermill.execute_notebook(
"Experiment.ipynb",
"/dev/null",
parameters=dict(
dataset="/tmp/data/boston.csv",
filter_type="remover",
model_features="medv",
n_clusters=3,
n_init=10,
max_iter=300,
algorithm="auto",
),
)
papermill.execute_notebook(
"Deployment.ipynb",
"/dev/null",
)
data = datasets.boston_testdata()
with server.Server() as s:
response = s.test(data=data)
names = response["names"]
ndarray = response["ndarray"]
self.assertEqual(len(ndarray[0]),
17) # 13 features+ 1 cluster + 3 distance to clusters
self.assertEqual(len(names), 17)
def test_experiment_boston(self):
papermill.execute_notebook(
"Experiment.ipynb",
"/dev/null",
parameters=dict(
dataset="/tmp/data/boston.csv",
target="medv",
cutoff=0.9,
threshold=0.0,
),
)
papermill.execute_notebook(
"Deployment.ipynb",
"/dev/null",
)
data = datasets.boston_testdata()
with server.Server() as s:
response = s.test(data=data)
names = response["names"]
ndarray = response["ndarray"]
self.assertEqual(len(ndarray[0]), 12) # 13 features - 1 removed
self.assertEqual(len(names), 12)