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9200887

Run 9200887

Task 9950 (Supervised Classification) micro-mass Uploaded 06-05-2018 by Benjamin Strang
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  • openml-python Sklearn_0.19.1. study_123
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sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.pipeli ne.Pipeline(imputation=mylib.preprocessing_openml14.ConditionalImputer,one- hot-encoder=sklearn.preprocessing.data.OneHotEncoder,variance-thresholding= sklearn.feature_selection.variance_threshold.VarianceThreshold,feature-scal ing=sklearn.preprocessing.data.StandardScaler,classifier=sklearn.svm.classe s.SVC))(1)Automatically created scikit-learn flow.
mylib.preprocessing_openml14.ConditionalImputer(1)_axis0
mylib.preprocessing_openml14.ConditionalImputer(1)_categorical_features[]
mylib.preprocessing_openml14.ConditionalImputer(1)_copytrue
mylib.preprocessing_openml14.ConditionalImputer(1)_fill_empty0
mylib.preprocessing_openml14.ConditionalImputer(1)_missing_values"NaN"
mylib.preprocessing_openml14.ConditionalImputer(1)_strategy"median"
mylib.preprocessing_openml14.ConditionalImputer(1)_strategy_nominal"most_frequent"
mylib.preprocessing_openml14.ConditionalImputer(1)_verbose0
sklearn.preprocessing.data.OneHotEncoder(17)_categorical_features[]
sklearn.preprocessing.data.OneHotEncoder(17)_dtype{"oml-python:serialized_object": "type", "value": "np.float64"}
sklearn.preprocessing.data.OneHotEncoder(17)_handle_unknown"ignore"
sklearn.preprocessing.data.OneHotEncoder(17)_n_values"auto"
sklearn.preprocessing.data.OneHotEncoder(17)_sparsetrue
sklearn.feature_selection.variance_threshold.VarianceThreshold(11)_threshold0.0
sklearn.preprocessing.data.StandardScaler(5)_copytrue
sklearn.preprocessing.data.StandardScaler(5)_with_meanfalse
sklearn.preprocessing.data.StandardScaler(5)_with_stdtrue
sklearn.svm.classes.SVC(16)_C1.0
sklearn.svm.classes.SVC(16)_cache_size1000
sklearn.svm.classes.SVC(16)_class_weightnull
sklearn.svm.classes.SVC(16)_coef00.0
sklearn.svm.classes.SVC(16)_decision_function_shape"ovr"
sklearn.svm.classes.SVC(16)_degree3
sklearn.svm.classes.SVC(16)_gamma"auto"
sklearn.svm.classes.SVC(16)_kernel"rbf"
sklearn.svm.classes.SVC(16)_max_iter10000
sklearn.svm.classes.SVC(16)_probabilitytrue
sklearn.svm.classes.SVC(16)_random_state37027
sklearn.svm.classes.SVC(16)_shrinkingtrue
sklearn.svm.classes.SVC(16)_tol0.001
sklearn.svm.classes.SVC(16)_verbosefalse
sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.pipeline.Pipeline(imputation=mylib.preprocessing_openml14.ConditionalImputer,one-hot-encoder=sklearn.preprocessing.data.OneHotEncoder,variance-thresholding=sklearn.feature_selection.variance_threshold.VarianceThreshold,feature-scaling=sklearn.preprocessing.data.StandardScaler,classifier=sklearn.svm.classes.SVC))(1)_cv3
sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.pipeline.Pipeline(imputation=mylib.preprocessing_openml14.ConditionalImputer,one-hot-encoder=sklearn.preprocessing.data.OneHotEncoder,variance-thresholding=sklearn.feature_selection.variance_threshold.VarianceThreshold,feature-scaling=sklearn.preprocessing.data.StandardScaler,classifier=sklearn.svm.classes.SVC))(1)_error_score"raise"
sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.pipeline.Pipeline(imputation=mylib.preprocessing_openml14.ConditionalImputer,one-hot-encoder=sklearn.preprocessing.data.OneHotEncoder,variance-thresholding=sklearn.feature_selection.variance_threshold.VarianceThreshold,feature-scaling=sklearn.preprocessing.data.StandardScaler,classifier=sklearn.svm.classes.SVC))(1)_fit_paramsnull
sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.pipeline.Pipeline(imputation=mylib.preprocessing_openml14.ConditionalImputer,one-hot-encoder=sklearn.preprocessing.data.OneHotEncoder,variance-thresholding=sklearn.feature_selection.variance_threshold.VarianceThreshold,feature-scaling=sklearn.preprocessing.data.StandardScaler,classifier=sklearn.svm.classes.SVC))(1)_iidtrue
sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.pipeline.Pipeline(imputation=mylib.preprocessing_openml14.ConditionalImputer,one-hot-encoder=sklearn.preprocessing.data.OneHotEncoder,variance-thresholding=sklearn.feature_selection.variance_threshold.VarianceThreshold,feature-scaling=sklearn.preprocessing.data.StandardScaler,classifier=sklearn.svm.classes.SVC))(1)_n_iter250
sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.pipeline.Pipeline(imputation=mylib.preprocessing_openml14.ConditionalImputer,one-hot-encoder=sklearn.preprocessing.data.OneHotEncoder,variance-thresholding=sklearn.feature_selection.variance_threshold.VarianceThreshold,feature-scaling=sklearn.preprocessing.data.StandardScaler,classifier=sklearn.svm.classes.SVC))(1)_n_jobs-1
sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.pipeline.Pipeline(imputation=mylib.preprocessing_openml14.ConditionalImputer,one-hot-encoder=sklearn.preprocessing.data.OneHotEncoder,variance-thresholding=sklearn.feature_selection.variance_threshold.VarianceThreshold,feature-scaling=sklearn.preprocessing.data.StandardScaler,classifier=sklearn.svm.classes.SVC))(1)_param_distributions{"classifier__C": {"oml-python:serialized_object": "rv_frozen", "value": {"dist": "mylib.distributions.loguniform_gen", "a": 0.03125, "b": 32768, "args": [], "kwds": {"base": 2, "low": 0.03125, "high": 32768}}}, "classifier__gamma": {"oml-python:serialized_object": "rv_frozen", "value": {"dist": "mylib.distributions.loguniform_gen", "a": 3.0517578125e-05, "b": 8, "args": [], "kwds": {"base": 2, "low": 3.0517578125e-05, "high": 8}}}, "classifier__shrinking": [true, false], "classifier__tol": {"oml-python:serialized_object": "rv_frozen", "value": {"dist": "mylib.distributions.loguniform_gen", "a": 1e-05, "b": 0.1, "args": [], "kwds": {"base": 10, "low": 1e-05, "high": 0.1}}}, "imputation__strategy": ["mean", "median", "most_frequent"]}
sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.pipeline.Pipeline(imputation=mylib.preprocessing_openml14.ConditionalImputer,one-hot-encoder=sklearn.preprocessing.data.OneHotEncoder,variance-thresholding=sklearn.feature_selection.variance_threshold.VarianceThreshold,feature-scaling=sklearn.preprocessing.data.StandardScaler,classifier=sklearn.svm.classes.SVC))(1)_pre_dispatch"2*n_jobs"
sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.pipeline.Pipeline(imputation=mylib.preprocessing_openml14.ConditionalImputer,one-hot-encoder=sklearn.preprocessing.data.OneHotEncoder,variance-thresholding=sklearn.feature_selection.variance_threshold.VarianceThreshold,feature-scaling=sklearn.preprocessing.data.StandardScaler,classifier=sklearn.svm.classes.SVC))(1)_random_state1
sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.pipeline.Pipeline(imputation=mylib.preprocessing_openml14.ConditionalImputer,one-hot-encoder=sklearn.preprocessing.data.OneHotEncoder,variance-thresholding=sklearn.feature_selection.variance_threshold.VarianceThreshold,feature-scaling=sklearn.preprocessing.data.StandardScaler,classifier=sklearn.svm.classes.SVC))(1)_refittrue
sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.pipeline.Pipeline(imputation=mylib.preprocessing_openml14.ConditionalImputer,one-hot-encoder=sklearn.preprocessing.data.OneHotEncoder,variance-thresholding=sklearn.feature_selection.variance_threshold.VarianceThreshold,feature-scaling=sklearn.preprocessing.data.StandardScaler,classifier=sklearn.svm.classes.SVC))(1)_return_train_score"warn"
sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.pipeline.Pipeline(imputation=mylib.preprocessing_openml14.ConditionalImputer,one-hot-encoder=sklearn.preprocessing.data.OneHotEncoder,variance-thresholding=sklearn.feature_selection.variance_threshold.VarianceThreshold,feature-scaling=sklearn.preprocessing.data.StandardScaler,classifier=sklearn.svm.classes.SVC))(1)_scoringnull
sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.pipeline.Pipeline(imputation=mylib.preprocessing_openml14.ConditionalImputer,one-hot-encoder=sklearn.preprocessing.data.OneHotEncoder,variance-thresholding=sklearn.feature_selection.variance_threshold.VarianceThreshold,feature-scaling=sklearn.preprocessing.data.StandardScaler,classifier=sklearn.svm.classes.SVC))(1)_verbose0
sklearn.pipeline.Pipeline(imputation=mylib.preprocessing_openml14.ConditionalImputer,one-hot-encoder=sklearn.preprocessing.data.OneHotEncoder,variance-thresholding=sklearn.feature_selection.variance_threshold.VarianceThreshold,feature-scaling=sklearn.preprocessing.data.StandardScaler,classifier=sklearn.svm.classes.SVC)(1)_memorynull

Result files

xml
Description

XML file describing the run, including user-defined evaluation measures.

arff
Predictions

ARFF file with instance-level predictions generated by the model.

17 Evaluation measures

0.9223 ± 0.0208
Per class
Cross-validation details (10-fold Crossvalidation)
0.7531 ± 0.072
Per class
Cross-validation details (10-fold Crossvalidation)
0.7185 ± 0.0664
Cross-validation details (10-fold Crossvalidation)
365.3329 ± 2.2408
Cross-validation details (10-fold Crossvalidation)
0.052 ± 0.0046
Cross-validation details (10-fold Crossvalidation)
0.0941 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
571
Per class
Cross-validation details (10-fold Crossvalidation)
0.8052 ± 0.0505
Per class
Cross-validation details (10-fold Crossvalidation)
0.7356 ± 0.0626
Cross-validation details (10-fold Crossvalidation)
4.208
Cross-validation details (10-fold Crossvalidation)
0.7356 ± 0.0626
Per class
Cross-validation details (10-fold Crossvalidation)
0.5529 ± 0.0489
Cross-validation details (10-fold Crossvalidation)
0.2169 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
0.153 ± 0.0112
Cross-validation details (10-fold Crossvalidation)
0.7053 ± 0.0518
Cross-validation details (10-fold Crossvalidation)