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9200271

Run 9200271

Task 3996 (Supervised Classification) AP_Ovary_Uterus 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.neural_net work.multilayer_perceptron.MLPClassifier))(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)_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.neural_network.multilayer_perceptron.MLPClassifier(10)_activation"logistic"
sklearn.neural_network.multilayer_perceptron.MLPClassifier(10)_alpha0.0001
sklearn.neural_network.multilayer_perceptron.MLPClassifier(10)_batch_size"auto"
sklearn.neural_network.multilayer_perceptron.MLPClassifier(10)_beta_10.9
sklearn.neural_network.multilayer_perceptron.MLPClassifier(10)_beta_20.999
sklearn.neural_network.multilayer_perceptron.MLPClassifier(10)_early_stoppingfalse
sklearn.neural_network.multilayer_perceptron.MLPClassifier(10)_epsilon1e-08
sklearn.neural_network.multilayer_perceptron.MLPClassifier(10)_hidden_layer_sizes[100]
sklearn.neural_network.multilayer_perceptron.MLPClassifier(10)_learning_rate"constant"
sklearn.neural_network.multilayer_perceptron.MLPClassifier(10)_learning_rate_init0.001
sklearn.neural_network.multilayer_perceptron.MLPClassifier(10)_max_iter2000
sklearn.neural_network.multilayer_perceptron.MLPClassifier(10)_momentum0.9
sklearn.neural_network.multilayer_perceptron.MLPClassifier(10)_nesterovs_momentumtrue
sklearn.neural_network.multilayer_perceptron.MLPClassifier(10)_power_t0.5
sklearn.neural_network.multilayer_perceptron.MLPClassifier(10)_random_state3
sklearn.neural_network.multilayer_perceptron.MLPClassifier(10)_shuffletrue
sklearn.neural_network.multilayer_perceptron.MLPClassifier(10)_solver"adam"
sklearn.neural_network.multilayer_perceptron.MLPClassifier(10)_tol0.0001
sklearn.neural_network.multilayer_perceptron.MLPClassifier(10)_validation_fraction0.1
sklearn.neural_network.multilayer_perceptron.MLPClassifier(10)_verbosefalse
sklearn.neural_network.multilayer_perceptron.MLPClassifier(10)_warm_startfalse
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.neural_network.multilayer_perceptron.MLPClassifier))(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.neural_network.multilayer_perceptron.MLPClassifier))(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.neural_network.multilayer_perceptron.MLPClassifier))(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.neural_network.multilayer_perceptron.MLPClassifier))(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.neural_network.multilayer_perceptron.MLPClassifier))(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.neural_network.multilayer_perceptron.MLPClassifier))(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.neural_network.multilayer_perceptron.MLPClassifier))(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__early_stopping": [true, false], "classifier__hidden_layer_sizes": [[128, 128], [128], [64, 64], [64], [32, 32], [32]], "classifier__learning_rate_init": {"oml-python:serialized_object": "rv_frozen", "value": {"dist": "mylib.distributions.loguniform_gen", "a": 1e-05, "b": 1, "args": [], "kwds": {"base": 10, "low": 1e-05, "high": 1}}}, "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.neural_network.multilayer_perceptron.MLPClassifier))(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.neural_network.multilayer_perceptron.MLPClassifier))(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.neural_network.multilayer_perceptron.MLPClassifier))(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.neural_network.multilayer_perceptron.MLPClassifier))(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.neural_network.multilayer_perceptron.MLPClassifier))(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.neural_network.multilayer_perceptron.MLPClassifier))(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.neural_network.multilayer_perceptron.MLPClassifier)(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

0.9091 ± 0.0667
Per class
Cross-validation details (10-fold Crossvalidation)
0.8556 ± 0.0775
Per class
Cross-validation details (10-fold Crossvalidation)
0.7013 ± 0.159
Cross-validation details (10-fold Crossvalidation)
198.9114 ± 6.7966
Cross-validation details (10-fold Crossvalidation)
0.1873 ± 0.1028
Cross-validation details (10-fold Crossvalidation)
0.4738 ± 0.0031
Cross-validation details (10-fold Crossvalidation)
322
Per class
Cross-validation details (10-fold Crossvalidation)
0.8645 ± 0.0765
Per class
Cross-validation details (10-fold Crossvalidation)
0.854 ± 0.0784
Cross-validation details (10-fold Crossvalidation)
0.962
Cross-validation details (10-fold Crossvalidation)
0.854 ± 0.0784
Per class
Cross-validation details (10-fold Crossvalidation)
0.3954 ± 0.2156
Cross-validation details (10-fold Crossvalidation)
0.4866 ± 0.0032
Cross-validation details (10-fold Crossvalidation)
0.3309 ± 0.0888
Cross-validation details (10-fold Crossvalidation)
0.68 ± 0.1822
Cross-validation details (10-fold Crossvalidation)