6668747 1 Jan van Rijn 9954 Supervised Classification 7096 sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.pipeline.Pipeline(imputation=openmlstudy14.preprocessing.ConditionalImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,variencethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,classifier=sklearn.ensemble.forest.RandomForestClassifier))(1) 4694701 bootstrap true 6902 class_weight null 6902 criterion "gini" 6902 max_depth null 6902 max_features 0.5 6902 max_leaf_nodes null 6902 min_impurity_split 1e-07 6902 min_samples_leaf 1 6902 min_samples_split 2 6902 min_weight_fraction_leaf 0.0 6902 n_estimators 10 6902 n_jobs 1 6902 oob_score false 6902 random_state 1 6902 verbose 0 6902 warm_start false 6902 axis 0 6947 categorical_features [] 6947 copy true 6947 fill_empty 0 6947 missing_values "NaN" 6947 strategy "median" 6947 strategy_nominal "most_frequent" 6947 verbose 0 6947 categorical_features [] 6948 dtype {"oml-python:serialized_object": "type", "value": "np.float64"} 6948 handle_unknown "ignore" 6948 n_values "auto" 6948 sparse true 6948 threshold 0.0 6949 cv null 7096 error_score "raise" 7096 fit_params {} 7096 iid true 7096 n_iter 50 7096 n_jobs -1 7096 param_distributions {"classifier__min_samples_leaf": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20], "classifier__bootstrap": [true, false], "classifier__min_samples_split": [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20], "classifier__criterion": ["gini", "entropy"], "imputation__strategy": ["mean", "median", "most_frequent"]} 7096 pre_dispatch "2*n_jobs" 7096 random_state 1 7096 refit true 7096 return_train_score true 7096 scoring null 7096 verbose 0 7096 openml-python Sklearn_0.18.1. 1491 one-hundred-plants-margin https://www.openml.org/data/download/1592283/phpCsX3fx -1 14267526 description https://api.openml.org/data/download/14267526/description.xml -1 14267527 predictions https://api.openml.org/data/download/14267527/predictions.arff -1 14267528 trace https://api.openml.org/data/download/14267528/trace.arff area_under_roc_curve 0.9752687026515151 [0.982442,0.999645,0.966363,1,0.998343,0.960819,0.998915,0.997218,0.997258,0.999842,0.996903,0.965949,0.998106,0.92515,0.998994,0.990155,0.999744,0.953776,0.94693,0.94553,0.996705,0.996488,0.995699,1,0.998441,0.878117,0.874921,0.963778,0.964568,0.997929,0.999842,1,0.998323,0.957327,0.897747,0.997929,0.985855,0.949495,0.966146,0.998639,0.993608,0.997001,0.999566,0.998402,0.965159,0.964134,0.966659,0.998363,0.992602,0.96078,0.919429,0.994358,0.992424,0.941821,0.952494,0.971216,1,0.966442,0.99491,0.956873,0.999941,0.964489,0.96218,0.997258,0.994614,0.990313,0.933081,0.999921,0.918975,0.951192,0.990767,0.998086,0.958018,0.965593,0.95565,0.996015,0.999507,0.918837,0.999211,0.998501,0.925939,0.996212,0.994338,0.961924,0.959399,0.960997,0.999527,0.993726,0.964094,0.999645,0.999171,0.998915,0.997711,0.99418,0.993154,0.964765,0.996232,0.963048,0.808771,0.996705] average_cost 0 f_measure 0.6972179845441278 [0.444444,0.848485,0.882353,0.969697,0.83871,0.48,0.875,0.742857,0.727273,0.933333,0.642857,0.83871,0.705882,0.615385,0.933333,0.764706,0.810811,0.645161,0.294118,0.071429,0.6875,0.896552,0.702703,1,0.769231,0.275862,0.216216,0.756757,0.714286,0.827586,0.909091,1,0.8125,0.5,0.764706,0.6875,0.344828,0.470588,0.8125,0.8,0.709677,0.787879,0.9375,0.769231,0.83871,0.75,0.866667,0.787879,0.774194,0.8125,0.645161,0.588235,0.647059,0.363636,0.571429,0.324324,1,0.882353,0.611111,0.62069,0.969697,0.736842,0.645161,0.647059,0.764706,0.4375,0.307692,0.914286,0.413793,0.37037,0.571429,0.774194,0.606061,0.903226,0.647059,0.866667,0.848485,0.461538,0.823529,0.83871,0.571429,0.606061,0.5625,0.689655,0.733333,0.827586,0.9375,0.588235,0.647059,0.9375,0.857143,0.848485,0.684211,0.689655,0.62069,0.764706,0.666667,0.631579,0.25,0.758621] kappa 0.6988636363636364 kb_relative_information_score 1185.267506355841 mean_absolute_error 0.011682889603451978 mean_prior_absolute_error 0.019800000000000036 number_of_instances 1600 [16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16] precision 0.7042747079015418 [0.545455,0.823529,0.833333,0.941176,0.866667,0.666667,0.875,0.684211,0.705882,1,0.75,0.866667,0.666667,0.8,1,0.722222,0.714286,0.666667,0.277778,0.083333,0.6875,1,0.619048,1,0.652174,0.307692,0.190476,0.666667,0.833333,0.923077,0.882353,1,0.8125,0.583333,0.722222,0.6875,0.384615,0.444444,0.8125,0.736842,0.733333,0.764706,0.9375,0.652174,0.866667,0.75,0.928571,0.764706,0.8,0.8125,0.666667,0.555556,0.611111,0.352941,0.666667,0.285714,1,0.833333,0.55,0.692308,0.941176,0.636364,0.666667,0.611111,0.722222,0.4375,0.4,0.842105,0.461538,0.454545,0.666667,0.8,0.588235,0.933333,0.611111,0.928571,0.823529,0.6,0.777778,0.866667,0.526316,0.588235,0.5625,0.769231,0.785714,0.923077,0.9375,0.555556,0.611111,0.9375,0.789474,0.823529,0.590909,0.769231,0.692308,0.722222,0.647059,0.545455,0.375,0.846154] predictive_accuracy 0.701875 prior_entropy 6.6438561897747395 recall 0.701875 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area_under_roc_curve 0.972841160138524 [1,1,1,1,0.993671,0.977848,1,0.990506,0.998418,1,1,1,1,1,0.995253,0.988924,1,0.996835,0.908805,0.974684,0.996855,1,0.996835,1,0.990566,0.990506,0.889241,1,1,1,1,1,1,0.726266,0.443396,1,0.993711,0.443396,1,1,1,1,1,1,0.993671,1,0.743671,1,0.993671,1,0.990506,1,1,0.971519,1,0.985759,1,1,0.987421,0.992089,1,0.987421,0.996835,1,1,0.984177,0.955696,1,0.443396,0.987342,0.996835,1,0.990566,0.996835,0.959119,1,1,0.713608,0.995253,1,1,0.996835,0.996835,1,1,1,1,0.993671,0.996835,1,0.996835,1,0.987421,0.995253,1,1,0.996835,1,0.943396,1] area_under_roc_curve 0.9841629099992039 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area_under_roc_curve 0.9870300433882653 [0.920886,1,1,1,1,0.984177,1,1,1,1,0.993671,1,1,1,1,1,1,0.996835,1,0.712025,0.996835,0.963608,1,1,0.993671,1,0.968354,1,1,1,1,1,0.996835,0.993671,0.993711,0.993671,0.996835,0.996835,0.996835,0.996835,0.996835,1,1,0.987421,1,1,1,1,0.996835,0.954114,1,1,0.996835,1,0.718354,0.971519,1,1,0.993671,0.993711,1,0.993671,0.987421,1,1,0.993671,1,1,0.981013,0.990506,0.977848,0.993671,1,1,0.990506,1,1,1,1,1,0.968553,0.996835,1,0.990506,1,1,1,0.993711,1,0.993671,1,1,1,1,0.993671,1,0.996835,0.968553,0.987421,1] area_under_roc_curve 0.9691787825411987 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average_cost 0 average_cost 0 average_cost 0 average_cost 0 average_cost 0 average_cost 0 average_cost 0 average_cost 0 average_cost 0 average_cost 0 kappa 0.6968022108172127 kappa 0.7283960364770439 kappa 0.646269245953415 kappa 0.6968141802534443 kappa 0.6714708785784798 kappa 0.6716135143669089 kappa 0.7472054350831457 kappa 0.6904122571473701 kappa 0.7473152242577384 kappa 0.6904367053620785 kb_relative_information_score 117.85246736202805 kb_relative_information_score 120.22944261767056 kb_relative_information_score 116.43828305413167 kb_relative_information_score 121.58783219138455 kb_relative_information_score 118.40413747808456 kb_relative_information_score 115.56678900753681 kb_relative_information_score 117.79529836404033 kb_relative_information_score 120.97449283537121 kb_relative_information_score 120.6584074600926 kb_relative_information_score 115.76035598550605 mean_absolute_error 0.011105833333333417 mean_absolute_error 0.011224791666666734 mean_absolute_error 0.011954791666666704 mean_absolute_error 0.011271041666666776 mean_absolute_error 0.011547291666666876 mean_absolute_error 0.012943464486901337 mean_absolute_error 0.011833883928570996 mean_absolute_error 0.011088541666666802 mean_absolute_error 0.011360000000000073 mean_absolute_error 0.01249925595238031 mean_prior_absolute_error 0.019800000000000033 mean_prior_absolute_error 0.019800000000000033 mean_prior_absolute_error 0.019800000000000033 mean_prior_absolute_error 0.019800000000000033 mean_prior_absolute_error 0.019800000000000033 mean_prior_absolute_error 0.019800000000000033 mean_prior_absolute_error 0.019800000000000033 mean_prior_absolute_error 0.019800000000000033 mean_prior_absolute_error 0.019800000000000033 mean_prior_absolute_error 0.019800000000000033 number_of_instances 160 [1,2,2,1,2,1,2,1,2,1,2,2,2,2,2,1,2,2,2,1,1,1,1,1,1,2,2,2,2,1,2,2,2,2,2,1,1,1,1,2,1,1,2,2,2,2,1,1,2,2,2,2,1,2,1,1,2,1,1,2,1,1,2,2,1,2,2,1,1,1,2,1,2,2,1,2,2,2,2,2,2,2,1,1,2,2,2,2,2,1,2,1,2,2,2,2,1,2,2,1] number_of_instances 160 [1,2,2,1,2,1,2,1,2,1,2,2,2,2,2,1,2,2,2,1,1,1,1,1,1,2,2,2,2,1,2,2,2,2,2,1,1,1,1,2,1,1,2,2,2,2,1,1,2,2,2,2,1,2,1,1,2,1,1,2,1,1,2,2,1,2,2,1,1,1,2,1,2,2,1,2,2,2,2,2,2,2,1,1,2,2,2,2,2,1,2,1,2,2,2,2,1,2,2,1] number_of_instances 160 [2,2,2,1,2,2,1,2,2,2,2,2,1,2,2,2,2,2,1,2,1,1,2,1,1,2,2,1,2,2,1,2,2,2,1,1,1,1,1,2,2,1,1,1,2,1,2,1,2,2,2,1,1,2,1,2,1,2,1,2,1,1,2,1,2,2,2,2,1,2,2,2,1,2,1,2,2,2,2,2,1,2,2,2,1,1,1,2,2,1,2,1,1,2,2,1,2,2,1,2] number_of_instances 160 [2,2,2,1,2,2,1,2,2,2,2,2,1,2,2,2,2,2,1,2,1,1,2,1,1,2,2,1,2,2,1,2,2,2,1,1,1,1,1,2,2,1,1,1,2,1,2,1,2,2,2,1,1,2,1,2,1,2,1,2,1,1,2,1,2,2,2,2,1,2,2,2,1,2,1,2,2,2,2,2,1,2,2,2,1,1,1,2,2,1,2,1,1,2,2,1,2,2,1,2] number_of_instances 160 [2,1,2,2,1,2,1,2,1,2,2,2,1,1,1,2,2,2,1,2,2,2,2,2,2,2,2,1,1,2,1,1,2,2,1,2,2,2,2,2,2,2,1,1,1,1,2,2,2,2,1,1,2,1,2,2,1,2,2,1,2,2,1,1,2,2,1,2,2,2,2,2,1,1,2,1,2,2,2,1,1,2,2,2,1,1,1,1,2,2,1,2,1,1,2,1,2,1,1,2] number_of_instances 160 [2,1,2,2,1,2,1,2,1,2,2,2,1,1,1,2,2,2,1,2,2,2,2,2,2,2,2,1,1,2,1,1,2,2,1,2,2,2,2,2,2,2,1,1,1,1,2,2,2,2,1,1,2,1,2,2,1,2,2,1,2,2,1,1,2,2,1,2,2,2,2,2,1,1,2,1,2,2,2,1,1,2,2,2,1,1,1,1,2,2,1,2,1,1,2,1,2,1,1,2] number_of_instances 160 [2,1,1,2,1,2,2,2,1,2,1,1,2,1,1,2,1,1,2,2,2,2,2,2,2,1,1,2,1,2,2,1,1,1,2,2,2,2,2,1,2,2,2,2,1,2,2,2,1,1,1,2,2,1,2,2,2,2,2,1,2,2,1,2,2,1,1,2,2,2,1,2,2,1,2,1,1,1,1,1,2,1,2,2,2,2,2,1,1,2,1,2,2,1,1,2,2,1,2,2] number_of_instances 160 [2,1,1,2,1,2,2,2,1,2,1,1,2,1,1,2,1,1,2,2,2,2,2,2,2,1,1,2,1,2,2,1,1,1,2,2,2,2,2,1,2,2,2,2,1,2,2,2,1,1,1,2,2,1,2,2,2,2,2,1,2,2,1,2,2,1,1,2,2,2,1,2,2,1,2,1,1,1,1,1,2,1,2,2,2,2,2,1,1,2,1,2,2,1,1,2,2,1,2,2] number_of_instances 160 [1,2,1,2,2,1,2,1,2,1,1,1,2,2,2,1,1,1,2,1,2,2,1,2,2,1,1,2,2,1,2,2,1,1,2,2,2,2,2,1,1,2,2,2,2,2,1,2,1,1,2,2,2,2,2,1,2,1,2,2,2,2,2,2,1,1,2,1,2,1,1,1,2,2,2,2,1,1,1,2,2,1,1,1,2,2,2,2,1,2,2,2,2,2,1,2,1,2,2,1] number_of_instances 160 [1,2,1,2,2,1,2,1,2,1,1,1,2,2,2,1,1,1,2,1,2,2,1,2,2,1,1,2,2,1,2,2,1,1,2,2,2,2,2,1,1,2,2,2,2,2,1,2,1,1,2,2,2,2,2,1,2,1,2,2,2,2,2,2,1,1,2,1,2,1,1,1,2,2,2,2,1,1,1,2,2,1,1,1,2,2,2,2,1,2,2,2,2,2,1,2,1,2,2,1] predictive_accuracy 0.7 predictive_accuracy 0.73125 predictive_accuracy 0.65 predictive_accuracy 0.7 predictive_accuracy 0.675 predictive_accuracy 0.675 predictive_accuracy 0.75 predictive_accuracy 0.69375 predictive_accuracy 0.75 predictive_accuracy 0.69375 prior_entropy 6.6438561897747395 prior_entropy 6.6438561897747395 prior_entropy 6.6438561897747395 prior_entropy 6.6438561897747395 prior_entropy 6.6438561897747395 prior_entropy 6.6438561897747395 prior_entropy 6.6438561897747395 prior_entropy 6.6438561897747395 prior_entropy 6.6438561897747395 prior_entropy 6.6438561897747395 recall 0.7 [1,0.5,1,1,1,0,1,1,1,1,0.5,0.5,1,0.5,1,1,1,0,0.5,0,1,1,1,1,1,0.5,0,1,0.5,0,0.5,1,1,0.5,1,0,1,0,1,1,1,1,1,0.5,1,1,1,1,1,0.5,0.5,0.5,1,0,1,0,1,1,0,1,1,1,0.5,1,1,0,0,1,1,0,0,1,0.5,1,1,0.5,1,0,1,1,1,0.5,0,1,0,0.5,1,1,0.5,1,1,1,1,0.5,1,0.5,1,1,0,1] recall 0.73125 [1,1,1,1,1,1,0.5,1,1,1,1,1,0.5,0.5,1,1,1,0,0,0,1,0,1,1,1,0,0.5,0,1,0,1,1,1,0.5,0.5,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0.5,0,0,1,1,1,0.5,1,1,1,1,1,1,1,1,0,0,1,1,1,0.5,1,1,0,0,1,0.5,0.5,0.5,0,1,1,1,1,1,0.5,1,1,1,0.5,0.5,0.5,1,1,0.5,0,1] recall 0.65 [0.5,1,1,1,0.5,0,1,1,0,1,1,1,1,0.5,0.5,0.5,1,1,0,0,0,1,1,1,0,0.5,0,1,1,1,1,1,1,0.5,0,0,1,0,1,1,0,1,1,1,0.5,1,0.5,1,0,1,1,1,1,0,1,0.5,1,1,1,0,1,1,0.5,1,0.5,0.5,0,1,0,0,0.5,1,0,1,0,1,1,0.5,0.5,1,1,0.5,0,0.5,1,1,1,0.5,0.5,1,1,1,0,0.5,1,1,0.5,1,0,0.5] recall 0.7 [0,1,1,1,0.5,0,1,0.5,0.5,0.5,0,0.5,1,0,1,1,1,0,0,0,1,1,0.5,1,1,0.5,0.5,1,1,1,1,1,1,0.5,1,1,0,0,1,1,1,1,1,1,1,1,0.5,1,1,1,0.5,1,1,0,1,0.5,1,1,0,0.5,1,1,0.5,1,0.5,1,0,1,1,0.5,0,0.5,0,1,1,0.5,1,0.5,1,0.5,1,1,1,1,1,1,1,0.5,0.5,1,0.5,1,1,1,1,0,1,1,1,0.5] recall 0.675 [0.5,1,1,1,0,0.5,0,0.5,1,1,0.5,1,0,0,1,1,1,1,1,0,1,0.5,1,1,1,0,0.5,1,0,1,1,1,0.5,0,1,1,0.5,0.5,0.5,1,1,1,1,1,1,1,1,1,1,0.5,0,0,0,0,0,0,1,1,1,1,1,1,1,1,0.5,0,0,1,0,0.5,0.5,1,1,0,0.5,1,1,0,1,1,0,1,0.5,0.5,1,0,1,1,1,1,1,0.5,1,0,0.5,1,1,1,0,0.5] recall 0.675 [0,1,1,1,1,0,1,0.5,1,0.5,0,1,1,1,1,1,0.5,1,0,0,0.5,0.5,0.5,1,1,0.5,0.5,1,1,1,1,1,0.5,0.5,1,0.5,0.5,1,1,0,1,0.5,0,1,1,1,1,0.5,1,0.5,1,0,1,1,0,0.5,1,1,0,1,1,0.5,1,1,1,0,1,1,0.5,0,0.5,0.5,1,1,0.5,1,1,1,1,1,0,0.5,1,0.5,0,1,1,0,1,1,1,1,1,1,0.5,1,0.5,0,0,0.5] recall 0.75 [0.5,1,1,1,1,0.5,1,1,1,1,1,1,0.5,1,1,0.5,1,1,0.5,0.5,0.5,1,1,1,1,0,0,1,0,1,1,1,1,0,1,1,0.5,1,1,1,1,0.5,1,1,0,0.5,0.5,0.5,1,1,0,1,1,1,0.5,1,1,0.5,0.5,0,1,1,1,0.5,1,0,0,1,0.5,0,1,1,1,1,1,1,1,0,0,1,0.5,1,1,0.5,1,1,1,0,0,1,1,1,0.5,1,0,0.5,0.5,1,0,1] recall 0.69375 [0.5,1,1,1,1,0.5,1,1,1,1,0,0,0.5,0,0,0.5,1,1,0.5,0,0.5,1,1,1,1,0,0,1,0,0.5,1,1,1,1,1,1,0,0,0.5,1,0.5,1,1,1,1,1,1,1,1,1,0,0.5,0.5,1,1,0,1,1,1,1,1,0.5,1,0.5,1,0,0,1,0,0.5,0,1,1,1,1,1,1,1,1,1,0,0,0,1,0.5,0.5,1,0,1,1,1,1,1,0,0,1,0.5,0,0,1] recall 0.75 [0,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,0.5,0,1,1,0,1,1,0,0,1,0.5,1,1,1,1,1,1,1,0,0,1,1,0,1,1,1,0.5,0,1,1,0,1,1,1,1,0.5,0.5,0,1,1,1,0.5,1,1,0.5,0,1,1,0,1,0.5,1,1,0,0.5,1,0.5,0.5,1,1,1,1,1,1,1,0,1,1,1,0.5,1,0.5,1,0.5,1,0.5,0,1,0,0.5,0.5,1] recall 0.69375 [0,0.5,0,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,0,0,0.5,1,1,1,1,0,0,1,0.5,0,1,1,0,0,0.5,0.5,0,1,0.5,1,0,0.5,1,1,1,0.5,1,0.5,0,1,0.5,1,0,0.5,0.5,1,1,1,1,0.5,1,1,0,0.5,1,1,0.5,1,0.5,1,1,0,0,1,0.5,1,1,0,1,0.5,1,0,1,0,0.5,0.5,0.5,1,1,1,1,1,1,1,0,1,1,1,0.5,0] relative_absolute_error 0.5609006734006767 relative_absolute_error 0.5669086700336724 relative_absolute_error 0.6037773569023578 relative_absolute_error 0.5692445286195332 relative_absolute_error 0.5831965488215585 relative_absolute_error 0.6537103276212786 relative_absolute_error 0.5976709054833826 relative_absolute_error 0.5600273569023628 relative_absolute_error 0.5737373737373764 relative_absolute_error 0.6312755531505198 root_mean_prior_squared_error 0.09949874371066206 root_mean_prior_squared_error 0.09949874371066206 root_mean_prior_squared_error 0.09949874371066206 root_mean_prior_squared_error 0.09949874371066206 root_mean_prior_squared_error 0.09949874371066206 root_mean_prior_squared_error 0.09949874371066206 root_mean_prior_squared_error 0.09949874371066206 root_mean_prior_squared_error 0.09949874371066206 root_mean_prior_squared_error 0.09949874371066206 root_mean_prior_squared_error 0.09949874371066206 root_mean_squared_error 0.0686650282976075 root_mean_squared_error 0.0683151754330211 root_mean_squared_error 0.07215429310781667 root_mean_squared_error 0.0689855535400129 root_mean_squared_error 0.07055307300969448 root_mean_squared_error 0.07408553902792571 root_mean_squared_error 0.07057246553624762 root_mean_squared_error 0.0684492994648039 root_mean_squared_error 0.06825493215796899 root_mean_squared_error 0.07341334196414467 root_relative_squared_error 0.6901095002493937 root_relative_squared_error 0.6865933466625327 root_relative_squared_error 0.7251779310665285 root_relative_squared_error 0.6933309001430193 root_relative_squared_error 0.7090850635748697 root_relative_squared_error 0.7445876828692749 root_relative_squared_error 0.7092799658000629 root_relative_squared_error 0.6879413439013002 root_relative_squared_error 0.6859878789671084 root_relative_squared_error 0.7378318481852135 total_cost 0 total_cost 0 total_cost 0 total_cost 0 total_cost 0 total_cost 0 total_cost 0 total_cost 0 total_cost 0 total_cost 0