Run
9200355

Run 9200355

Task 9983 (Supervised Classification) eeg-eye-state Uploaded 06-05-2018 by Benjamin Strang
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  • openml-python Sklearn_0.19.1. study_123
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Flow

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.linear_mod el.stochastic_gradient.SGDClassifier))(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"
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sklearn.preprocessing.data.OneHotEncoder(17)_sparsefalse
sklearn.feature_selection.variance_threshold.VarianceThreshold(11)_threshold0.0
sklearn.preprocessing.data.StandardScaler(5)_copytrue
sklearn.preprocessing.data.StandardScaler(5)_with_meantrue
sklearn.preprocessing.data.StandardScaler(5)_with_stdtrue
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.linear_model.stochastic_gradient.SGDClassifier))(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.linear_model.stochastic_gradient.SGDClassifier))(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.linear_model.stochastic_gradient.SGDClassifier))(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.linear_model.stochastic_gradient.SGDClassifier))(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.linear_model.stochastic_gradient.SGDClassifier))(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.linear_model.stochastic_gradient.SGDClassifier))(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.linear_model.stochastic_gradient.SGDClassifier))(1)_param_distributions{"classifier__alpha": {"oml-python:serialized_object": "rv_frozen", "value": {"dist": "mylib.distributions.loguniform_gen", "a": 1e-07, "b": 0.1, "args": [], "kwds": {"base": 10, "low": 1e-07, "high": 0.1}}}, "classifier__penalty": ["l2", "l1", "elasticnet"], "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.linear_model.stochastic_gradient.SGDClassifier))(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.linear_model.stochastic_gradient.SGDClassifier))(1)_random_state3
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.linear_model.stochastic_gradient.SGDClassifier))(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.linear_model.stochastic_gradient.SGDClassifier))(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.linear_model.stochastic_gradient.SGDClassifier))(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.linear_model.stochastic_gradient.SGDClassifier))(1)_verbose0
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sklearn.linear_model.stochastic_gradient.SGDClassifier(5)_l1_ratio0.15
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sklearn.linear_model.stochastic_gradient.SGDClassifier(5)_loss"log"
sklearn.linear_model.stochastic_gradient.SGDClassifier(5)_max_iter2000
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sklearn.linear_model.stochastic_gradient.SGDClassifier(5)_penalty"l2"
sklearn.linear_model.stochastic_gradient.SGDClassifier(5)_power_t0.5
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sklearn.linear_model.stochastic_gradient.SGDClassifier(5)_warm_startfalse

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

0.6156 ± 0.0167
Per class
Cross-validation details (10-fold Crossvalidation)
0.5842 ± 0.0221
Per class
Cross-validation details (10-fold Crossvalidation)
0.1591 ± 0.0365
Cross-validation details (10-fold Crossvalidation)
1153.8619 ± 32.2507
Cross-validation details (10-fold Crossvalidation)
0.461 ± 0.0105
Cross-validation details (10-fold Crossvalidation)
0.4948 ± 0
Cross-validation details (10-fold Crossvalidation)
14980
Per class
Cross-validation details (10-fold Crossvalidation)
0.587 ± 0.0169
Per class
Cross-validation details (10-fold Crossvalidation)
0.5921 ± 0.0177
Cross-validation details (10-fold Crossvalidation)
0.9924
Cross-validation details (10-fold Crossvalidation)
0.5921 ± 0.0177
Per class
Cross-validation details (10-fold Crossvalidation)
0.9318 ± 0.0212
Cross-validation details (10-fold Crossvalidation)
0.4974 ± 0
Cross-validation details (10-fold Crossvalidation)
0.4919 ± 0.0118
Cross-validation details (10-fold Crossvalidation)
0.989 ± 0.0237
Cross-validation details (10-fold Crossvalidation)