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remove things related to vowpalwabbit
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MichaelFu512 committed May 17, 2024
1 parent 6c61d6e commit b00d604
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Showing 18 changed files with 0 additions and 528 deletions.
1 change: 0 additions & 1 deletion .github/meta.yaml
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Expand Up @@ -81,7 +81,6 @@ outputs:
- imbalanced-learn >=0.11.0
- sktime >=0.21.0, <0.29.0
- pmdarima >=1.8.5
- vowpalwabbit >=8.11.0
test:
imports:
- evalml
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3 changes: 0 additions & 3 deletions docs/source/api_index.rst
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Expand Up @@ -264,8 +264,6 @@ Classifiers are components that output a predicted class label.
evalml.pipelines.components.RandomForestClassifier
evalml.pipelines.components.StackedEnsembleClassifier
evalml.pipelines.components.SVMClassifier
evalml.pipelines.components.VowpalWabbitBinaryClassifier
evalml.pipelines.components.VowpalWabbitMulticlassClassifier
evalml.pipelines.components.XGBoostClassifier


Expand All @@ -290,7 +288,6 @@ Regressors are components that output a predicted target value.
evalml.pipelines.components.StackedEnsembleRegressor
evalml.pipelines.components.SVMRegressor
evalml.pipelines.components.TimeSeriesBaselineEstimator
evalml.pipelines.components.VowpalWabbitRegressor
evalml.pipelines.components.XGBoostRegressor


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3 changes: 0 additions & 3 deletions evalml/pipelines/components/__init__.py
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Expand Up @@ -30,9 +30,6 @@
ExponentialSmoothingRegressor,
ARIMARegressor,
VARMAXRegressor,
VowpalWabbitBinaryClassifier,
VowpalWabbitMulticlassClassifier,
VowpalWabbitRegressor,
)
from evalml.pipelines.components.transformers import (
Transformer,
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3 changes: 0 additions & 3 deletions evalml/pipelines/components/estimators/__init__.py
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Expand Up @@ -13,8 +13,6 @@
DecisionTreeClassifier,
KNeighborsClassifier,
SVMClassifier,
VowpalWabbitBinaryClassifier,
VowpalWabbitMulticlassClassifier,
)
from evalml.pipelines.components.estimators.regressors import (
LinearRegressor,
Expand All @@ -33,5 +31,4 @@
ARIMARegressor,
VARMAXRegressor,
ProphetRegressor,
VowpalWabbitRegressor,
)
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Expand Up @@ -33,7 +33,3 @@
from evalml.pipelines.components.estimators.classifiers.svm_classifier import (
SVMClassifier,
)
from evalml.pipelines.components.estimators.classifiers.vowpal_wabbit_classifiers import (
VowpalWabbitBinaryClassifier,
VowpalWabbitMulticlassClassifier,
)

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3 changes: 0 additions & 3 deletions evalml/pipelines/components/estimators/regressors/__init__.py
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Expand Up @@ -46,6 +46,3 @@
from evalml.pipelines.components.estimators.regressors.varmax_regressor import (
VARMAXRegressor,
)
from evalml.pipelines.components.estimators.regressors.vowpal_wabbit_regressor import (
VowpalWabbitRegressor,
)

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63 changes: 0 additions & 63 deletions evalml/tests/component_tests/test_components.py
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Expand Up @@ -76,13 +76,6 @@
StackedEnsembleClassifier,
StackedEnsembleRegressor,
)
from evalml.pipelines.components.estimators.classifiers.vowpal_wabbit_classifiers import (
VowpalWabbitBinaryClassifier,
VowpalWabbitMulticlassClassifier,
)
from evalml.pipelines.components.estimators.regressors.vowpal_wabbit_regressor import (
VowpalWabbitRegressor,
)
from evalml.pipelines.components.transformers.encoders.label_encoder import LabelEncoder
from evalml.pipelines.components.transformers.preprocessing.log_transformer import (
LogTransformer,
Expand Down Expand Up @@ -525,56 +518,6 @@ def test_describe_component():
}
except ImportError:
pass
vw_binary_classifier = VowpalWabbitBinaryClassifier(
loss_function="classic",
learning_rate=0.1,
decay_learning_rate=1.0,
power_t=0.1,
passes=1,
)
vw_multi_classifier = VowpalWabbitMulticlassClassifier(
loss_function="classic",
learning_rate=0.1,
decay_learning_rate=1.0,
power_t=0.1,
passes=1,
)
vw_regressor = VowpalWabbitRegressor(
learning_rate=0.1,
decay_learning_rate=1.0,
power_t=0.1,
passes=1,
)

assert vw_binary_classifier.describe(return_dict=True) == {
"name": "Vowpal Wabbit Binary Classifier",
"parameters": {
"loss_function": "classic",
"learning_rate": 0.1,
"decay_learning_rate": 1.0,
"power_t": 0.1,
"passes": 1,
},
}
assert vw_multi_classifier.describe(return_dict=True) == {
"name": "Vowpal Wabbit Multiclass Classifier",
"parameters": {
"loss_function": "classic",
"learning_rate": 0.1,
"decay_learning_rate": 1.0,
"power_t": 0.1,
"passes": 1,
},
}
assert vw_regressor.describe(return_dict=True) == {
"name": "Vowpal Wabbit Regressor",
"parameters": {
"learning_rate": 0.1,
"decay_learning_rate": 1.0,
"power_t": 0.1,
"passes": 1,
},
}


def test_update_parameters(X_y_binary):
Expand Down Expand Up @@ -1215,9 +1158,6 @@ def test_all_estimators_check_fit(
StackedEnsembleRegressor,
TimeSeriesBaselineEstimator,
MultiseriesTimeSeriesBaselineRegressor,
VowpalWabbitBinaryClassifier,
VowpalWabbitMulticlassClassifier,
VowpalWabbitRegressor,
]
] + [test_estimator_needs_fitting_false]
for component_class in estimators_to_check:
Expand Down Expand Up @@ -1399,9 +1339,6 @@ def test_serialization(
(
StackedEnsembleClassifier,
StackedEnsembleRegressor,
VowpalWabbitBinaryClassifier,
VowpalWabbitMulticlassClassifier,
VowpalWabbitRegressor,
TimeSeriesBaselineEstimator,
),
)
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