Search is not available for this dataset
repo stringlengths 2 152 ⌀ | file stringlengths 15 239 | code stringlengths 0 58.4M | file_length int64 0 58.4M | avg_line_length float64 0 1.81M | max_line_length int64 0 12.7M | extension_type stringclasses 364
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auto-sklearn | auto-sklearn-master/scripts/2015_nips_paper/setup/create_commands.sh | #!/usr/bin/env bash
dir=../log_output # working directory
#task_ids=$(python get_tasks.py)
task_ids="233 236 242 244 246 248 251 252 253 254 256 258 260 261 262 266 273 275 288 2117 2118 2119 2120 2122 2123 2350 3043 3044 75090 75092 75093 75098 75099 75100 75103 75104 75105 75106 75107 75108 75111 75112 75113 75114 ... | 2,761 | 68.05 | 798 | sh |
auto-sklearn | auto-sklearn-master/scripts/2015_nips_paper/setup/get_tasks.py | # get tasks from openml
import openml
import pandas as pd
# List of dataset IDs used for the NIPS experiment.
dataset_ids = [
1000,
1002,
1018,
1019,
1020,
1021,
1036,
1040,
1041,
1049,
1050,
1053,
1056,
1067,
1068,
1069,
1111,
1112,
1114,
... | 2,732 | 13.384211 | 84 | py |
auto-sklearn | auto-sklearn-master/test/__init__.py | 0 | 0 | 0 | py | |
auto-sklearn | auto-sklearn-master/test/conftest.py | """
Testing
=======
The following are some features, guidelines and functionality for testing which makes
updating, adding and refactoring tests easier, especially as features and functionality
changes.
**Marks**
* todo - ``pytest.mark.todo``` to mark a test which xfails as it's todo
* slow - ``pytest.mark.slow``` to ... | 6,959 | 28.871245 | 105 | py |
auto-sklearn | auto-sklearn-master/test/util.py | from typing import Any
from pytest import mark, param
def fails(arg: Any, reason: str = "No reason given") -> Any:
"""Mark a parameter for pytest parametrize that it should fail
..code:: python
@parametrize("number", [2, 3, fails(5, "some reason")])
Parameters
----------
arg : Any
... | 1,043 | 19.88 | 69 | py |
auto-sklearn | auto-sklearn-master/test/fixtures/__init__.py | 0 | 0 | 0 | py | |
auto-sklearn | auto-sklearn-master/test/fixtures/automl.py | from __future__ import annotations
from typing import Any, Callable, Dict, Tuple, Type
from functools import partial
from autosklearn.automl import AutoML, AutoMLClassifier, AutoMLRegressor
from autosklearn.automl_common.common.utils.backend import Backend
from autosklearn.ensembles.ensemble_selection import Ensembl... | 3,182 | 28.472222 | 88 | py |
auto-sklearn | auto-sklearn-master/test/fixtures/backend.py | from __future__ import annotations
from typing import Callable
import os
from distutils.dir_util import copy_tree
from pathlib import Path
from autosklearn.automl_common.common.utils.backend import Backend, create
from autosklearn.data.xy_data_manager import XYDataManager
from pytest import fixture
HERE = Path(__f... | 3,522 | 22.331126 | 82 | py |
auto-sklearn | auto-sklearn-master/test/fixtures/caching.py | from __future__ import annotations
from typing import Any, Callable
import os
import pickle
import shutil
import tempfile
from functools import partial
from pathlib import Path
from filelock import FileLock
from pytest import FixtureRequest
from pytest_cases import fixture
from test.conftest import AUTOSKLEARN_CAC... | 3,742 | 25.546099 | 85 | py |
auto-sklearn | auto-sklearn-master/test/fixtures/dask.py | from __future__ import annotations
from typing import Callable
from functools import partial
from dask.distributed import Client, get_client
from pytest import FixtureRequest, fixture
# Terrible practice but we need to close dask clients somehow
active_clients: dict[str, Callable] = {}
@fixture(autouse=True)
def... | 2,652 | 23.564815 | 75 | py |
auto-sklearn | auto-sklearn-master/test/fixtures/datasets.py | from __future__ import annotations
from typing import Any, Callable, Dict, List, Optional, Sequence, Tuple
import numpy as np
import pandas as pd
from scipy.sparse import csr_matrix
from sklearn.utils import check_random_state
from autosklearn.constants import (
BINARY_CLASSIFICATION,
MULTICLASS_CLASSIFICATI... | 7,947 | 26.79021 | 84 | py |
auto-sklearn | auto-sklearn-master/test/fixtures/ensemble_building.py | from __future__ import annotations
from typing import Any, Callable
import copy
import math
import pickle
import sys
from pathlib import Path
import numpy as np
from autosklearn.automl import AutoML
from autosklearn.automl_common.common.utils.backend import Backend
from autosklearn.constants import BINARY_CLASSIFIC... | 7,930 | 30.851406 | 86 | py |
auto-sklearn | auto-sklearn-master/test/fixtures/ensembles.py | from __future__ import annotations
from typing import Callable, Collection, Optional, Union
import numpy as np
from sklearn.ensemble import VotingClassifier, VotingRegressor
from autosklearn.data.validation import (
SUPPORTED_FEAT_TYPES,
SUPPORTED_TARGET_TYPES,
InputValidator,
)
from autosklearn.evaluati... | 3,432 | 29.114035 | 80 | py |
auto-sklearn | auto-sklearn-master/test/fixtures/logging.py | from pytest_cases import fixture
from test.mocks.logging import MockLogger
@fixture
def mock_logger() -> MockLogger:
"""A mock logger with some mock defaults"""
return MockLogger()
| 192 | 18.3 | 47 | py |
auto-sklearn | auto-sklearn-master/test/fixtures/metrics.py | from typing import Any
import numpy as np
from autosklearn.metrics import accuracy, make_scorer
def _accuracy_requiring_X_data(
y_true: np.ndarray,
y_pred: np.ndarray,
X_data: Any,
) -> float:
"""Dummy metric that needs X Data"""
if X_data is None:
raise ValueError()
return accuracy(... | 532 | 18.740741 | 53 | py |
auto-sklearn | auto-sklearn-master/test/mocks/__init__.py | 0 | 0 | 0 | py | |
auto-sklearn | auto-sklearn-master/test/mocks/logging.py | from typing import Optional
from autosklearn.util.logging_ import PicklableClientLogger
from unittest.mock import Mock
MOCKNAME = "mock"
MOCKHOST = "mockhost"
MOCKPORT = 9020
class MockLogger(PicklableClientLogger):
"""Should not be used for testing the actual loggers functionality
Overwrites all methods ... | 1,406 | 33.317073 | 84 | py |
auto-sklearn | auto-sklearn-master/test/test_automl/__init__.py | 0 | 0 | 0 | py | |
auto-sklearn | auto-sklearn-master/test/test_automl/automl_utils.py | # -*- encoding: utf-8 -*-
import typing
import glob
import os
import re
import numpy as np
scores_dict = {
"train_single": ["single_best_train_score", "single_best_optimization_score"],
"test_single": ["single_best_test_score"],
"train_ensamble": ["ensemble_optimization_score"],
"test_ensamble": ["en... | 9,280 | 34.696154 | 108 | py |
auto-sklearn | auto-sklearn-master/test/test_automl/cases.py | """
Here we define the several different setups and cache them to allow for easier unit
testing. The caching mechanism is only per session and does not persist over sessions.
There's only really a point for caching fitted models that will be tested multiple times
for different properties.
Anything using a cached model... | 13,196 | 34.286096 | 88 | py |
auto-sklearn | auto-sklearn-master/test/test_automl/test_construction.py | """Test things related to only constructing an AutoML instance"""
from typing import Any, Dict, Optional, Union
from autosklearn.automl import AutoML
from autosklearn.util.dask import LocalDask
from autosklearn.util.data import default_dataset_compression_arg
from autosklearn.util.single_thread_client import SingleThr... | 2,722 | 27.663158 | 86 | py |
auto-sklearn | auto-sklearn-master/test/test_automl/test_dataset_compression.py | """Test things related to how AutoML compresses the dataset size"""
from typing import Any, Callable, Dict
import numpy as np
import pandas as pd
from scipy.sparse import csr_matrix
from autosklearn.automl import AutoML
from autosklearn.constants import BINARY_CLASSIFICATION
from pytest_cases import parametrize
from... | 4,013 | 28.29927 | 88 | py |
auto-sklearn | auto-sklearn-master/test/test_automl/test_dummy_predictions.py | """Test the dummy predictor of AutoML
Dummy models can serve as an early warning of issues with parameters during fit
"""
from __future__ import annotations
from typing import Callable, Sequence, Tuple
from pathlib import Path
import numpy as np
from smac.tae import StatusType
from autosklearn.automl import AutoML... | 6,530 | 27.272727 | 86 | py |
auto-sklearn | auto-sklearn-master/test/test_automl/test_early_stopping.py | from __future__ import annotations
from typing import TYPE_CHECKING, Callable
if TYPE_CHECKING:
import numpy as np
from smac.optimizer.smbo import SMBO
from smac.runhistory.runhistory import RunInfo, RunValue
from autosklearn.automl import AutoMLClassifier
def test_early_stopping(
make_automl_c... | 958 | 24.236842 | 67 | py |
auto-sklearn | auto-sklearn-master/test/test_automl/test_fit.py | """Test specific ways of calling `fit` of AutoML"""
from typing import Any, Callable, Dict, Optional, Tuple, Union
import numpy as np
from dask.distributed import Client
from smac.facade.roar_facade import ROAR
from smac.scenario.scenario import Scenario
from autosklearn.automl import AutoML
from autosklearn.constant... | 2,315 | 26.571429 | 88 | py |
auto-sklearn | auto-sklearn-master/test/test_automl/test_fit_pipeline.py | """Test specific ways of calling `fit_pipeline`"""
| 51 | 25 | 50 | py |
auto-sklearn | auto-sklearn-master/test/test_automl/test_model_predict.py | """Test the _model_predict helper function such that it shapes output correctly"""
from typing import Callable, Dict, Tuple
import warnings
import numpy as np
from sklearn.ensemble import VotingClassifier, VotingRegressor
from autosklearn.automl import _model_predict
from autosklearn.constants import (
BINARY_CL... | 4,281 | 26.448718 | 88 | py |
auto-sklearn | auto-sklearn-master/test/test_automl/test_pareto_front.py | """Test the output of loading the pareto set from an automl instance"""
from autosklearn.automl import AutoML
from pytest_cases import parametrize_with_cases
from pytest_cases.filters import has_tag
import test.test_automl.cases as cases
has_ensemble = has_tag("fitted") & ~has_tag("no_ensemble")
single_objective = ... | 1,106 | 28.918919 | 88 | py |
auto-sklearn | auto-sklearn-master/test/test_automl/test_performance.py | """Test the performance of automl instances after fitting"""
import numpy as np
from sklearn.ensemble import VotingClassifier, VotingRegressor
from autosklearn.automl import AutoML
from pytest_cases import parametrize_with_cases
import test.test_automl.cases as cases
@parametrize_with_cases("automl", cases.case_c... | 1,513 | 30.541667 | 86 | py |
auto-sklearn | auto-sklearn-master/test/test_automl/test_performance_over_time.py | """Test the performance over time functionality of automl instances"""
from autosklearn.automl import AutoML
from pytest_cases import parametrize_with_cases
from pytest_cases.filters import has_tag
import test.test_automl.cases as cases
@parametrize_with_cases(
"automl",
cases=cases,
filter=has_tag("fit... | 1,230 | 29.775 | 77 | py |
auto-sklearn | auto-sklearn-master/test/test_automl/test_post_fit.py | """Check the internal state of the automl instances after it has been fitted"""
from pathlib import Path
from autosklearn.automl import AutoML
from autosklearn.ensemble_building.builder import CANDIDATES_FILENAME
from pytest import mark
from pytest_cases import parametrize_with_cases
from pytest_cases.filters import... | 4,936 | 26.581006 | 79 | py |
auto-sklearn | auto-sklearn-master/test/test_automl/test_predict.py | """Test predictions of an automl instance"""
| 45 | 22 | 44 | py |
auto-sklearn | auto-sklearn-master/test/test_automl/test_refit.py | """Test the refitting functionality of an automl instance"""
from typing import Callable, Union
from itertools import repeat
import numpy as np
from autosklearn.automl import AutoML
from autosklearn.data.validation import InputValidator
from pytest_cases import parametrize
from unittest.mock import Mock
@parametr... | 1,704 | 26.063492 | 85 | py |
auto-sklearn | auto-sklearn-master/test/test_automl/test_show_models.py | """Test the show models functinality of an automl instance"""
from autosklearn.automl import AutoML
from pytest_cases import parametrize_with_cases
import test.test_automl.cases as cases
@parametrize_with_cases("automl", cases=cases, has_tag=["fitted", "no_ensemble"])
def test_no_ensemble_produces_empty_show_models... | 577 | 25.272727 | 81 | py |
auto-sklearn | auto-sklearn-master/test/test_automl/test_sklearn_compliance.py | """Test that autosklearn is sklearn compliant
Note
----
* This is far from complete at the moment
* This should probably be tested on AutoSklearnEstimators not AutoML
"""
from typing import List, Union
from sklearn.exceptions import NotFittedError
from autosklearn.automl import AutoML
import pytest
from pytest_case... | 1,957 | 23.78481 | 76 | py |
auto-sklearn | auto-sklearn-master/test/test_data/__init__.py | # -*- encoding: utf-8 -*-
__author__ = "feurerm"
| 49 | 15.666667 | 25 | py |
auto-sklearn | auto-sklearn-master/test/test_data/test_feature_validator.py | import numpy as np
import pandas as pd
import sklearn.datasets
import sklearn.model_selection
from pandas.api.types import is_categorical_dtype, is_numeric_dtype, is_string_dtype
from scipy import sparse
from autosklearn.data.feature_validator import FeatureValidator
import pytest
# Fixtures to be used in this clas... | 19,620 | 32.255932 | 88 | py |
auto-sklearn | auto-sklearn-master/test/test_data/test_target_validator.py | import numpy as np
import pandas as pd
import sklearn.datasets
import sklearn.model_selection
from pandas.api.types import is_bool_dtype, is_numeric_dtype
from scipy import sparse
from sklearn.utils.multiclass import type_of_target
from autosklearn.data.target_validator import TargetValidator
import pytest
# Fixtur... | 18,189 | 33.256121 | 84 | py |
auto-sklearn | auto-sklearn-master/test/test_data/test_validation.py | import numpy as np
import pandas as pd
import sklearn.datasets
import sklearn.model_selection
from scipy import sparse
from autosklearn.data.validation import InputValidator
import pytest
@pytest.mark.parametrize("openmlid", [2, 40975, 40984])
@pytest.mark.parametrize("as_frame", [True, False])
def test_data_valida... | 4,842 | 35.413534 | 87 | py |
auto-sklearn | auto-sklearn-master/test/test_ensemble_builder/__init__.py | # -*- encoding: utf-8 -*-
__author__ = "mlindauer"
| 51 | 16.333333 | 25 | py |
auto-sklearn | auto-sklearn-master/test/test_ensemble_builder/test_ensemble_builder.py | from __future__ import annotations
from typing import Callable
import random
import time
from pathlib import Path
import numpy as np
from autosklearn.automl_common.common.utils.backend import Backend
from autosklearn.ensemble_building import EnsembleBuilder, Run
from autosklearn.metrics import Scorer, accuracy, mak... | 30,837 | 29.776447 | 88 | py |
auto-sklearn | auto-sklearn-master/test/test_ensemble_builder/test_ensemble_builder_real.py | """
This file tests the ensemble builder with real runs generated from running AutoML
"""
from __future__ import annotations
from typing import Callable
from autosklearn.automl import AutoML
from autosklearn.ensemble_building.builder import EnsembleBuilder
from pytest_cases import parametrize_with_cases
from pytest_... | 4,385 | 36.810345 | 87 | py |
auto-sklearn | auto-sklearn-master/test/test_ensemble_builder/test_ensemble_selection.py | import numpy as np
from autosklearn.constants import BINARY_CLASSIFICATION, REGRESSION
from autosklearn.ensembles.ensemble_selection import EnsembleSelection
from autosklearn.metrics import accuracy, root_mean_squared_error
import pytest
def testEnsembleSelection(backend):
"""
Makes sure ensemble selection ... | 4,333 | 29.957143 | 88 | py |
auto-sklearn | auto-sklearn-master/test/test_ensemble_builder/test_manager.py | from __future__ import annotations
from typing import Callable
from autosklearn.automl import AutoML
from autosklearn.ensemble_building import EnsembleBuilderManager
from pytest_cases import parametrize_with_cases
import test.test_automl.cases as cases
from test.conftest import DEFAULT_SEED
@parametrize_with_case... | 872 | 28.1 | 73 | py |
auto-sklearn | auto-sklearn-master/test/test_ensemble_builder/test_multiobjective_dummy_ensemble.py | import numpy as np
import sklearn.metrics
from autosklearn.constants import REGRESSION
from autosklearn.ensembles.multiobjective_dummy_ensemble import (
MultiObjectiveDummyEnsemble,
)
from autosklearn.ensembles.singlebest_ensemble import SingleModelEnsemble
from autosklearn.metrics import MAXINT, make_scorer, root... | 2,527 | 33.162162 | 81 | py |
auto-sklearn | auto-sklearn-master/test/test_ensemble_builder/test_run.py | from __future__ import annotations
from typing import Callable
import pickle
import time
from pathlib import Path
import numpy as np
from autosklearn.ensemble_building import Run
from pytest_cases import parametrize
def test_is_dummy(make_run: Callable[..., Run]) -> None:
"""
Expects
-------
* We... | 4,053 | 22.847059 | 87 | py |
auto-sklearn | auto-sklearn-master/test/test_ensemble_builder/test_singlebest_ensemble.py | import numpy as np
from autosklearn.constants import REGRESSION
from autosklearn.ensembles.singlebest_ensemble import SingleBest, SingleModelEnsemble
from autosklearn.metrics import root_mean_squared_error
def test_SingleBest(backend):
ensemble = SingleBest(
task_type=REGRESSION,
metrics=[root_m... | 3,934 | 28.586466 | 85 | py |
auto-sklearn | auto-sklearn-master/test/test_estimators/__init__.py | 0 | 0 | 0 | py | |
auto-sklearn | auto-sklearn-master/test/test_estimators/cases.py | 0 | 0 | 0 | py | |
auto-sklearn | auto-sklearn-master/test/test_estimators/test_estimators.py | from typing import Any, Dict, Sequence, Type, Union, cast
import copy
import glob
import importlib
import inspect
import itertools
import os
import pickle
import re
import tempfile
import joblib
import numpy as np
import numpy.ma as npma
import pandas as pd
import sklearn
import sklearn.datasets
import sklearn.dummy
... | 59,162 | 33.021277 | 88 | py |
auto-sklearn | auto-sklearn-master/test/test_evaluation/__init__.py | # -*- encoding: utf-8 -*-
__author__ = "feurerm"
| 49 | 15.666667 | 25 | py |
auto-sklearn | auto-sklearn-master/test/test_evaluation/evaluation_util.py | import functools
import tempfile
import traceback
import numpy as np
import sklearn.datasets
import sklearn.model_selection
from numpy.linalg import LinAlgError
from sklearn import preprocessing
from autosklearn.automl_common.common.utils.backend import Backend
from autosklearn.constants import (
BINARY_CLASSIFIC... | 8,130 | 26.285235 | 86 | py |
auto-sklearn | auto-sklearn-master/test/test_evaluation/test_abstract_evaluator.py | # -*- encoding: utf-8 -*-
import logging.handlers
import os
import shutil
import sys
import tempfile
import numpy as np
import sklearn.dummy
from smac.tae import StatusType
from autosklearn.automl_common.common.utils.backend import Backend, BackendContext
from autosklearn.evaluation.abstract_evaluator import Abstract... | 11,538 | 34.395706 | 88 | py |
auto-sklearn | auto-sklearn-master/test/test_evaluation/test_custom_splitters.py | import numpy as np
from autosklearn.constants import (
BINARY_CLASSIFICATION,
MULTICLASS_CLASSIFICATION,
MULTILABEL_CLASSIFICATION,
)
from autosklearn.evaluation.splitter import CustomStratifiedShuffleSplit
import pytest
@pytest.mark.parametrize(
"task, X, y",
[
(
BINARY_CLAS... | 1,750 | 28.183333 | 82 | py |
auto-sklearn | auto-sklearn-master/test/test_evaluation/test_dummy_pipelines.py | import numpy as np
from sklearn.base import clone
from sklearn.datasets import make_classification, make_regression
from sklearn.utils.validation import check_is_fitted
from autosklearn.evaluation.abstract_evaluator import (
MyDummyClassifier,
MyDummyRegressor,
)
import pytest
@pytest.mark.parametrize("task... | 1,071 | 27.972973 | 87 | py |
auto-sklearn | auto-sklearn-master/test/test_evaluation/test_evaluation.py | import logging
import logging.handlers
import os
import shutil
import sys
import time
import numpy as np
import pynisher
from smac.runhistory.runhistory import RunInfo
from smac.stats.stats import Stats
from smac.tae import StatusType
from smac.utils.constants import MAXINT
from autosklearn.evaluation import ExecuteT... | 18,722 | 33.480663 | 86 | py |
auto-sklearn | auto-sklearn-master/test/test_evaluation/test_test_evaluator.py | # -*- encoding: utf-8 -*-
import copy
import json
import logging.handlers
import multiprocessing
import os
import shutil
import sys
import tempfile
import numpy as np
from smac.tae import StatusType
from autosklearn.automl_common.common.utils.backend import Backend
from autosklearn.constants import (
BINARY_CLASS... | 7,609 | 33.590909 | 84 | py |
auto-sklearn | auto-sklearn-master/test/test_evaluation/test_train_evaluator.py | import copy
import json
import logging.handlers
import multiprocessing
import os
import queue
import shutil
import sys
import tempfile
from itertools import chain
import numpy as np
import sklearn.model_selection
from ConfigSpace import Configuration
from sklearn.model_selection import (
GroupKFold,
GroupShuff... | 131,814 | 37.140914 | 88 | py |
auto-sklearn | auto-sklearn-master/test/test_metalearning/__init__.py | # -*- encoding: utf-8 -*-
__author__ = "feurerm"
| 49 | 15.666667 | 25 | py |
auto-sklearn | auto-sklearn-master/test/test_metalearning/test_metalearning.py | # -*- encoding: utf-8 -*-
from sklearn.datasets import load_breast_cancer
from autosklearn.classification import AutoSklearnClassifier
from autosklearn.constants import MULTICLASS_CLASSIFICATION, REGRESSION
from autosklearn.metalearning.mismbo import suggest_via_metalearning
from autosklearn.pipeline.util import get_d... | 5,836 | 38.174497 | 85 | py |
auto-sklearn | auto-sklearn-master/test/test_metalearning/pyMetaLearn/__init__.py | __author__ = "feurerm"
| 23 | 11 | 22 | py |
auto-sklearn | auto-sklearn-master/test/test_metalearning/pyMetaLearn/test_meta_base.py | import logging
import os
import pandas as pd
import autosklearn.pipeline.classification
from autosklearn.metalearning.metalearning.meta_base import MetaBase
import unittest
class MetaBaseTest(unittest.TestCase):
_multiprocess_can_split_ = True
def setUp(self):
self.cwd = os.getcwd()
data_d... | 2,253 | 32.147059 | 85 | py |
auto-sklearn | auto-sklearn-master/test/test_metalearning/pyMetaLearn/test_meta_features.py | import logging
import os
import tempfile
import arff
import numpy as np
import pandas as pd
from joblib import Memory
from sklearn.datasets import fetch_openml, make_multilabel_classification
import autosklearn.metalearning.metafeatures.metafeatures as meta_features
from autosklearn.metalearning.metafeatures.metafeat... | 30,688 | 31.787393 | 87 | py |
auto-sklearn | auto-sklearn-master/test/test_metalearning/pyMetaLearn/test_meta_features_sparse.py | import logging
import os
import arff
import numpy as np
from scipy import sparse
from sklearn.impute import SimpleImputer
from sklearn.preprocessing import StandardScaler
import autosklearn.metalearning.metafeatures.metafeatures as meta_features
from autosklearn.pipeline.components.data_preprocessing.feature_type imp... | 11,422 | 26.525301 | 83 | py |
auto-sklearn | auto-sklearn-master/test/test_metalearning/pyMetaLearn/test_metalearner.py | import logging
import os
import numpy as np
import pandas as pd
from ConfigSpace.configuration_space import Configuration
import autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner as metalearner # noqa: E501
import autosklearn.pipeline.classification
from autosklearn.metalearning.metalearning.meta_b... | 3,165 | 36.690476 | 103 | py |
auto-sklearn | auto-sklearn-master/test/test_metalearning/pyMetaLearn/test_metalearning_configuration.py | import logging
import os
import autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner as metalearner # noqa: E501
import autosklearn.pipeline.classification
from autosklearn.metalearning.metalearning.meta_base import MetaBase
import unittest
logging.basicConfig()
class MetalearningConfiguration(unit... | 1,879 | 39 | 103 | py |
auto-sklearn | auto-sklearn-master/test/test_metalearning/pyMetaLearn/test_optimizer_base.py | from collections import OrderedDict
from autosklearn.metalearning.optimizers import optimizer_base
import unittest
class OptimizerBaseTest(unittest.TestCase):
_multiprocess_can_split_ = True
def setUp(self):
self.hyperparameters = OrderedDict()
self.hyperparameters["x"] = [-5, 0, 5, 10]
... | 1,518 | 35.166667 | 80 | py |
auto-sklearn | auto-sklearn-master/test/test_metalearning/pyMetaLearn/metalearning/test_kND.py | import logging
import numpy as np
import pandas as pd
from autosklearn.metalearning.metalearning.kNearestDatasets.kND import KNearestDatasets
from autosklearn.metalearning.metalearning.metrics.misc import get_random_metric
import unittest
class kNDTest(unittest.TestCase):
_multiprocess_can_split_ = True
d... | 4,580 | 35.648 | 88 | py |
auto-sklearn | auto-sklearn-master/test/test_metalearning/pyMetaLearn/metalearning/test_metrics.py | """
def test_learned(self):
kND = KNearestDatasets(metric='learned')
rf = kND.fit(pd.DataFrame([self.krvskp, self.labor]),
{233: self.runs[233], 234: self.runs[234]})
self.assertEqual(kND._learned(self.anneal, self.krvskp), 1.5)
self.assertEqual(kND._learned(self.anneal, self.labor), 1... | 1,840 | 39.911111 | 77 | py |
auto-sklearn | auto-sklearn-master/test/test_metric/__init__.py | # -*- encoding: utf-8 -*-
__author__ = "feurerm"
| 49 | 15.666667 | 25 | py |
auto-sklearn | auto-sklearn-master/test/test_metric/test_metrics.py | import warnings
import numpy as np
import sklearn.metrics
from smac.utils.constants import MAXINT
import autosklearn.metrics
from autosklearn.constants import BINARY_CLASSIFICATION, REGRESSION
from autosklearn.metrics import (
calculate_losses,
calculate_scores,
compute_single_metric,
)
import pytest
imp... | 30,654 | 35.235225 | 88 | py |
auto-sklearn | auto-sklearn-master/test/test_metric/test_util.py | 0 | 0 | 0 | py | |
auto-sklearn | auto-sklearn-master/test/test_optimizer/test_smbo.py | import logging.handlers
from ConfigSpace.configuration_space import Configuration
import autosklearn.metrics
import autosklearn.pipeline.util as putil
from autosklearn.automl import AutoML
from autosklearn.constants import BINARY_CLASSIFICATION
from autosklearn.data.xy_data_manager import XYDataManager
from autosklea... | 2,259 | 30.830986 | 88 | py |
auto-sklearn | auto-sklearn-master/test/test_pipeline/__init__.py | 0 | 0 | 0 | py | |
auto-sklearn | auto-sklearn-master/test/test_pipeline/ignored_warnings.py | from typing import Iterator, List, Tuple, Type
import warnings
from contextlib import contextmanager
from sklearn.exceptions import ConvergenceWarning
regressor_warnings = [
(
UserWarning,
( # From QuantileTransformer
r"n_quantiles \(\d+\) is greater than the total number of samples ... | 3,608 | 27.195313 | 88 | py |
auto-sklearn | auto-sklearn-master/test/test_pipeline/test_base.py | from typing import Optional
import ConfigSpace.configuration_space
import autosklearn.pipeline.base
import autosklearn.pipeline.components.base
import autosklearn.pipeline.components.classification as classification
import autosklearn.pipeline.components.feature_preprocessing as feature_preprocessing
from autosklearn... | 9,669 | 38.958678 | 87 | py |
auto-sklearn | auto-sklearn-master/test/test_pipeline/test_classification.py | from typing import Any, Dict, Optional, Union
import copy
import itertools
import os
import resource
import tempfile
import numpy as np
import sklearn.datasets
import sklearn.decomposition
import sklearn.ensemble
import sklearn.model_selection
import sklearn.svm
from ConfigSpace.configuration_space import Configurati... | 52,507 | 37.159884 | 88 | py |
auto-sklearn | auto-sklearn-master/test/test_pipeline/test_create_searchspace_util_classification.py | from collections import OrderedDict
import numpy
from ConfigSpace.configuration_space import ConfigurationSpace
from ConfigSpace.hyperparameters import CategoricalHyperparameter
import autosklearn.pipeline.create_searchspace_util
from autosklearn.pipeline.components.classification.lda import LDA
from autosklearn.pipe... | 6,534 | 39.590062 | 104 | py |
auto-sklearn | auto-sklearn-master/test/test_pipeline/test_regression.py | import copy
import itertools
import resource
import tempfile
import numpy as np
import sklearn.datasets
import sklearn.decomposition
import sklearn.ensemble
import sklearn.svm
from ConfigSpace.configuration_space import ConfigurationSpace
from ConfigSpace.hyperparameters import CategoricalHyperparameter
from joblib im... | 27,908 | 39.447826 | 88 | py |
auto-sklearn | auto-sklearn-master/test/test_pipeline/components/__init__.py | __author__ = "feurerm"
| 23 | 11 | 22 | py |
auto-sklearn | auto-sklearn-master/test/test_pipeline/components/test_base.py | import os
import sys
from autosklearn.pipeline.components.base import (
AutoSklearnClassificationAlgorithm,
find_components,
)
import unittest
this_dir = os.path.dirname(os.path.abspath(__file__))
sys.path.append(this_dir)
class TestBase(unittest.TestCase):
def test_find_components(self):
c = f... | 714 | 26.5 | 76 | py |
auto-sklearn | auto-sklearn-master/test/test_pipeline/components/classification/__init__.py | __author__ = "feurerm"
| 23 | 11 | 22 | py |
auto-sklearn | auto-sklearn-master/test/test_pipeline/components/classification/test_adaboost.py | import sklearn.ensemble
from autosklearn.pipeline.components.classification.adaboost import AdaboostClassifier
from .test_base import BaseClassificationComponentTest
class AdaBoostComponentTest(BaseClassificationComponentTest):
__test__ = True
res = dict()
res["default_iris"] = 0.93999999999999995
... | 777 | 28.923077 | 86 | py |
auto-sklearn | auto-sklearn-master/test/test_pipeline/components/classification/test_base.py | from typing import Dict, Optional
import numpy as np
import sklearn.metrics
from autosklearn.pipeline.constants import SPARSE
from autosklearn.pipeline.util import (
_test_classifier,
_test_classifier_iterative_fit,
_test_classifier_predict_proba,
)
import unittest
from test.test_pipeline.ignored_warnin... | 12,655 | 33.113208 | 88 | py |
auto-sklearn | auto-sklearn-master/test/test_pipeline/components/classification/test_bernoulli_nb.py | import sklearn.naive_bayes
from autosklearn.pipeline.components.classification.bernoulli_nb import BernoulliNB
from .test_base import BaseClassificationComponentTest
class BernoulliNBComponentTest(BaseClassificationComponentTest):
__test__ = True
res = dict()
res["default_iris"] = 0.26
res["iris_n... | 839 | 30.111111 | 83 | py |
auto-sklearn | auto-sklearn-master/test/test_pipeline/components/classification/test_decision_tree.py | import sklearn.tree
from autosklearn.pipeline.components.classification.decision_tree import DecisionTree
from .test_base import BaseClassificationComponentTest
class DecisionTreeComponentTest(BaseClassificationComponentTest):
__test__ = True
res = dict()
res["default_iris"] = 0.62
res["default_ir... | 790 | 30.64 | 85 | py |
auto-sklearn | auto-sklearn-master/test/test_pipeline/components/classification/test_extra_trees.py | import sklearn.ensemble
from autosklearn.pipeline.components.classification.extra_trees import (
ExtraTreesClassifier,
)
from .test_base import BaseClassificationComponentTest
class ExtraTreesComponentTest(BaseClassificationComponentTest):
__test__ = True
res = dict()
res["default_iris"] = 0.96
... | 1,042 | 29.676471 | 72 | py |
auto-sklearn | auto-sklearn-master/test/test_pipeline/components/classification/test_gaussian_nb.py | import sklearn.naive_bayes
from autosklearn.pipeline.components.classification.gaussian_nb import GaussianNB
from .test_base import BaseClassificationComponentTest
class GaussianNBComponentTest(BaseClassificationComponentTest):
__test__ = True
res = dict()
res["default_iris"] = 0.95999999999999996
... | 879 | 31.592593 | 81 | py |
auto-sklearn | auto-sklearn-master/test/test_pipeline/components/classification/test_gradient_boosting.py | import sklearn.ensemble
from autosklearn.pipeline.components.classification.gradient_boosting import (
GradientBoostingClassifier,
)
from .test_base import BaseClassificationComponentTest
class GradientBoostingComponentTest(BaseClassificationComponentTest):
__test__ = True
res = dict()
res["defaul... | 906 | 28.258065 | 78 | py |
auto-sklearn | auto-sklearn-master/test/test_pipeline/components/classification/test_k_nearest_neighbor.py | import sklearn.neighbors
from autosklearn.pipeline.components.classification.k_nearest_neighbors import (
KNearestNeighborsClassifier,
)
from .test_base import BaseClassificationComponentTest
class KNearestNeighborsComponentTest(BaseClassificationComponentTest):
__test__ = True
res = dict()
res["d... | 842 | 30.222222 | 80 | py |
auto-sklearn | auto-sklearn-master/test/test_pipeline/components/classification/test_lda.py | import sklearn.discriminant_analysis
from autosklearn.pipeline.components.classification.lda import LDA
from .test_base import BaseClassificationComponentTest
class LDAComponentTest(BaseClassificationComponentTest):
__test__ = True
res = dict()
res["default_iris"] = 1.0
res["default_iris_iterative... | 769 | 29.8 | 69 | py |
auto-sklearn | auto-sklearn-master/test/test_pipeline/components/classification/test_liblinear.py | import sklearn.svm
from autosklearn.pipeline.components.classification.liblinear_svc import LibLinear_SVC
from .test_base import BaseClassificationComponentTest
class LibLinearComponentTest(BaseClassificationComponentTest):
__test__ = True
res = dict()
res["default_iris"] = 1
res["default_iris_ite... | 837 | 30.037037 | 86 | py |
auto-sklearn | auto-sklearn-master/test/test_pipeline/components/classification/test_libsvm_svc.py | import sklearn.metrics
import sklearn.svm
from autosklearn.pipeline.components.classification.libsvm_svc import LibSVM_SVC
from autosklearn.pipeline.util import _test_classifier_predict_proba, get_dataset
from .test_base import BaseClassificationComponentTest
class LibSVM_SVCComponentTest(BaseClassificationComponen... | 2,738 | 35.039474 | 82 | py |
auto-sklearn | auto-sklearn-master/test/test_pipeline/components/classification/test_mlp.py | import sklearn.neural_network
from autosklearn.pipeline.components.classification.mlp import MLPClassifier
from .test_base import BaseClassificationComponentTest
class MLPComponentTest(BaseClassificationComponentTest):
# NOTE: `default_iris_proba_places`
#
# Github runners seem to indeterministicly fail... | 1,982 | 39.469388 | 134 | py |
auto-sklearn | auto-sklearn-master/test/test_pipeline/components/classification/test_multinomial_nb.py | import numpy as np
import sklearn.naive_bayes
import sklearn.preprocessing
from autosklearn.pipeline.components.classification.multinomial_nb import MultinomialNB
from autosklearn.pipeline.util import get_dataset
from .test_base import BaseClassificationComponentTest
class MultinomialNBComponentTest(BaseClassificat... | 1,832 | 34.941176 | 87 | py |
auto-sklearn | auto-sklearn-master/test/test_pipeline/components/classification/test_passive_aggressive.py | import sklearn.linear_model
from autosklearn.pipeline.components.classification.passive_aggressive import (
PassiveAggressive,
)
from .test_base import BaseClassificationComponentTest
class PassiveAggressiveComponentTest(BaseClassificationComponentTest):
__test__ = True
res = dict()
res["default_i... | 1,077 | 28.944444 | 79 | py |
auto-sklearn | auto-sklearn-master/test/test_pipeline/components/classification/test_qda.py | import sklearn.discriminant_analysis
from autosklearn.pipeline.components.classification.qda import QDA
from .test_base import BaseClassificationComponentTest
class QDAComponentTest(BaseClassificationComponentTest):
__test__ = True
res = dict()
res["default_iris"] = 1.0
res["default_iris_iterative... | 823 | 30.692308 | 72 | py |
auto-sklearn | auto-sklearn-master/test/test_pipeline/components/classification/test_random_forest.py | import sklearn.ensemble
from autosklearn.pipeline.components.classification.random_forest import RandomForest
from .test_base import BaseClassificationComponentTest
class RandomForestComponentTest(BaseClassificationComponentTest):
__test__ = True
res = dict()
res["default_iris"] = 0.96
res["iris_n... | 992 | 31.032258 | 85 | py |
auto-sklearn | auto-sklearn-master/test/test_pipeline/components/classification/test_sgd.py | import sklearn.linear_model
from autosklearn.pipeline.components.classification.sgd import SGD
from .test_base import BaseClassificationComponentTest
class SGDComponentTest(BaseClassificationComponentTest):
__test__ = True
res = dict()
res["default_iris"] = 0.69999999999999996
res["iris_n_calls"] ... | 816 | 29.259259 | 66 | py |
auto-sklearn | auto-sklearn-master/test/test_pipeline/components/data_preprocessing/__init__.py | __author__ = "feurerm"
| 23 | 11 | 22 | py |