10417068 1140 Andreas Mueller 9956 Supervised Classification 17315 sklearn.pipeline.Pipeline(columntransformer=sklearn.compose._column_transformer.ColumnTransformer(cont=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,standardscaler=sklearn.preprocessing.data.StandardScaler)),decisiontreeclassifier=sklearn.tree.tree.DecisionTreeClassifier)(1) 8254316 copy true 17283 with_mean true 17283 with_std true 17283 ccp_alpha 0.0 17313 class_weight null 17313 criterion "gini" 17313 max_depth 1 17313 max_features null 17313 max_leaf_nodes null 17313 min_impurity_decrease 0.0 17313 min_impurity_split null 17313 min_samples_leaf 1 17313 min_samples_split 2 17313 min_weight_fraction_leaf 0.0 17313 presort "deprecated" 17313 random_state 50158 17313 splitter "best" 17313 memory null 17315 steps [{"oml-python:serialized_object": "component_reference", "value": {"key": "columntransformer", "step_name": "columntransformer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "decisiontreeclassifier", "step_name": "decisiontreeclassifier"}}] 17315 verbose false 17315 n_jobs null 17316 remainder "drop" 17316 sparse_threshold 0.3 17316 transformer_weights null 17316 transformers [{"oml-python:serialized_object": "component_reference", "value": {"key": "cont", "step_name": "cont", "argument_1": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63]}}] 17316 verbose false 17316 memory null 17317 steps [{"oml-python:serialized_object": "component_reference", "value": {"key": "simpleimputer", "step_name": "simpleimputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "standardscaler", "step_name": "standardscaler"}}] 17317 verbose false 17317 add_indicator false 17318 copy true 17318 fill_value null 17318 missing_values NaN 17318 strategy "median" 17318 verbose 0 17318 openml-python Sklearn_0.22.dev0. 1493 one-hundred-plants-texture https://www.openml.org/data/download/1592285/phpoOxxNn -1 21756209 description https://api.openml.org/data/download/21756209/description.xml -1 21756210 predictions https://api.openml.org/data/download/21756210/predictions.arff area_under_roc_curve 0.45797554029116916 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mean_absolute_error 0.01966707876403231 mean_prior_absolute_error 0.019799992711748222 number_of_instances 1599 [15,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16] predictive_accuracy 0.013133208255159474 prior_entropy 6.643827772868604 recall 0.013133208255159476 [0,0.25,0.125,0.1875,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.4375,0,0.3125,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0] relative_absolute_error 0.9932871718868337 root_mean_prior_squared_error 0.09949872432040595 root_mean_squared_error 0.09926128326527564 root_relative_squared_error 0.9976136271419351 total_cost 0 area_under_roc_curve 0.5061858132314314 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average_cost 0 average_cost 0 average_cost 0 average_cost 0 kappa 0.006289308176100629 kappa 0.006289308176100629 kappa 0.012462161418406259 kappa 0.006289308176100629 kappa 0 kappa 0.012229169124297118 kappa -0.00007862253321802035 kappa 0.012229169124297118 kappa 0.006289308176100629 kappa 0.006329113924050633 kb_relative_information_score 0.008845261973969754 kb_relative_information_score 0.008845261973969754 kb_relative_information_score 0.0149195794708687 kb_relative_information_score 0.04343170533432992 kb_relative_information_score 0.0026091477166615353 kb_relative_information_score 0.04087768176360149 kb_relative_information_score 0.008865413596775697 kb_relative_information_score 0.03714264129602567 kb_relative_information_score 0.008834943238522068 kb_relative_information_score 0.01127305757541274 mean_absolute_error 0.019684860720973855 mean_absolute_error 0.019684860720973855 mean_absolute_error 0.01958518534785659 mean_absolute_error 0.019617275921444518 mean_absolute_error 0.019801351825842764 mean_absolute_error 0.019615864030053262 mean_absolute_error 0.01967885964912286 mean_absolute_error 0.019633812480434144 mean_absolute_error 0.019684772940074986 mean_absolute_error 0.019684050074238794 mean_prior_absolute_error 0.01980002942907592 mean_prior_absolute_error 0.01980002942907592 mean_prior_absolute_error 0.019800029429075917 mean_prior_absolute_error 0.019800029429075917 mean_prior_absolute_error 0.01980002942907591 mean_prior_absolute_error 0.01979995585638609 mean_prior_absolute_error 0.01979995585638609 mean_prior_absolute_error 0.01979995585638609 mean_prior_absolute_error 0.019799955856386102 mean_prior_absolute_error 0.01979995631910742 number_of_instances 160 [2,1,1,2,2,2,2,1,2,2,1,2,2,2,2,2,2,1,2,2,1,2,2,2,2,1,1,2,2,1,2,2,1,1,1,2,1,1,2,2,2,1,1,2,1,1,2,1,2,2,1,2,1,2,1,2,2,1,1,1,1,2,1,1,2,2,2,1,1,2,2,2,1,1,2,2,2,2,1,1,1,2,2,2,1,2,2,2,2,2,2,2,1,2,2,2,1,1,2,1] number_of_instances 160 [2,1,1,2,2,2,2,1,2,2,1,2,2,2,2,2,2,1,2,2,2,2,2,2,2,2,1,2,2,2,2,2,1,1,1,2,1,1,2,2,2,1,1,2,1,1,2,1,2,2,1,2,1,2,1,2,1,1,1,1,1,2,1,1,2,2,2,1,1,2,2,2,1,1,2,2,2,2,1,1,1,2,1,2,1,2,2,2,2,2,2,2,1,1,2,2,1,1,2,1] number_of_instances 160 [2,1,2,2,2,1,2,1,1,2,2,1,2,2,2,2,2,2,2,1,2,2,2,1,1,2,1,2,2,2,2,1,2,2,2,1,1,2,1,1,2,1,1,2,2,2,2,2,2,1,1,2,2,2,1,2,1,1,1,1,2,1,1,1,2,2,2,1,1,2,2,2,2,1,2,2,2,1,2,2,1,2,1,2,1,2,2,1,2,1,1,2,2,1,2,1,1,2,2,1] number_of_instances 160 [2,1,2,2,2,1,2,2,1,2,2,1,2,2,2,2,2,2,2,1,2,2,2,1,1,2,1,2,2,2,2,1,2,2,2,1,1,2,1,1,2,1,1,2,2,2,2,2,1,1,1,2,2,2,2,2,1,1,1,1,2,1,1,1,2,1,2,1,1,2,2,2,2,1,2,2,2,1,2,2,1,2,1,2,1,2,2,1,2,1,1,2,2,1,1,1,2,2,2,1] number_of_instances 160 [2,2,2,1,1,1,1,2,1,1,2,1,1,2,1,1,2,2,2,1,2,1,2,1,1,2,2,1,2,2,1,1,2,2,2,1,2,2,1,1,2,2,2,2,2,2,2,2,1,1,2,2,2,1,2,2,1,2,2,2,2,1,2,2,1,1,2,2,2,2,1,1,2,2,2,1,1,1,2,2,2,2,1,1,2,2,2,1,2,1,1,2,2,1,1,1,2,2,2,2] number_of_instances 160 [1,2,2,1,1,1,1,2,1,1,2,1,1,2,1,1,2,2,2,1,2,1,2,1,1,2,2,1,2,2,1,1,2,2,2,1,2,2,1,1,2,2,2,2,2,2,2,2,1,1,2,1,2,1,2,2,2,2,2,2,2,1,2,2,1,1,2,2,2,2,1,1,2,2,2,1,1,1,2,2,2,1,2,1,2,2,2,1,2,1,1,2,2,2,1,1,2,2,2,2] number_of_instances 160 [1,2,2,1,1,2,1,2,2,1,2,2,1,1,1,1,1,2,1,2,2,1,1,2,2,2,2,1,1,2,1,2,2,2,2,2,2,2,2,2,1,2,2,1,2,2,1,2,1,2,2,1,2,1,2,1,2,2,2,2,2,2,2,2,1,1,1,2,2,1,1,1,2,2,1,1,1,2,2,2,2,1,2,1,2,1,1,2,1,2,2,1,2,2,1,2,2,2,1,2] number_of_instances 160 [1,2,2,1,1,2,1,2,2,1,2,2,1,1,1,1,1,2,1,2,1,1,1,2,2,1,2,1,1,1,1,2,2,2,2,2,2,2,2,2,1,2,2,1,2,2,1,2,2,2,2,1,2,1,2,1,2,2,2,2,2,2,2,2,1,2,1,2,2,1,1,1,2,2,1,1,1,2,2,2,2,1,2,1,2,1,1,2,1,2,2,1,2,2,2,2,2,2,1,2] number_of_instances 160 [1,2,1,2,2,2,2,2,2,2,1,2,2,1,2,2,1,1,1,2,1,2,1,2,2,1,2,2,1,1,2,2,1,1,1,2,2,1,2,2,1,2,2,1,1,1,1,1,2,2,2,1,1,2,2,1,2,2,2,2,1,2,2,2,2,2,1,2,2,1,2,2,1,2,1,2,2,2,1,1,2,1,2,2,2,1,1,2,1,2,2,1,1,2,2,2,2,1,1,2] number_of_instances 159 [1,2,1,2,2,2,2,1,2,2,1,2,2,1,2,2,1,1,1,2,1,2,1,2,2,1,2,2,1,1,2,2,1,1,1,2,2,1,2,2,1,2,2,1,1,1,1,1,2,2,2,2,1,2,1,1,2,2,2,2,1,2,2,2,2,2,1,2,2,1,2,2,1,2,1,2,2,2,1,1,2,2,2,2,2,1,1,2,1,2,2,1,1,2,2,2,1,1,1,2] predictive_accuracy 0.0125 predictive_accuracy 0.0125 predictive_accuracy 0.01875 predictive_accuracy 0.0125 predictive_accuracy 0.00625 predictive_accuracy 0.01875 predictive_accuracy 0.00625 predictive_accuracy 0.01875 predictive_accuracy 0.0125 predictive_accuracy 0.012578616352201257 prior_entropy 6.644100581449517 prior_entropy 6.644100581449517 prior_entropy 6.644100581449517 prior_entropy 6.644100581449517 prior_entropy 6.644100581449517 prior_entropy 6.643553938691703 prior_entropy 6.643553938691703 prior_entropy 6.643553938691703 prior_entropy 6.643553938691703 prior_entropy 6.64355737669647 recall 0.0125 [0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0] recall 0.0125 [0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0] recall 0.01875 [0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0] recall 0.0125 [0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0] recall 0.00625 [0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0] recall 0.01875 [0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0] recall 0.00625 [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0] recall 0.01875 [0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0] recall 0.0125 [0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0] recall 0.012578616352201259 [0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0] relative_absolute_error 0.9941834072260043 relative_absolute_error 0.9941834072260043 relative_absolute_error 0.9891493049548788 relative_absolute_error 0.9907700385857493 relative_absolute_error 1.0000667876162301 relative_absolute_error 0.99070241228475 relative_absolute_error 0.9938840163007648 relative_absolute_error 0.9916089016987197 relative_absolute_error 0.9941826680247893 relative_absolute_error 0.9941461363348174 root_mean_prior_squared_error 0.09949890883178135 root_mean_prior_squared_error 0.09949890883178135 root_mean_prior_squared_error 0.09949890883178135 root_mean_prior_squared_error 0.09949890883178135 root_mean_prior_squared_error 0.09949890883178135 root_mean_prior_squared_error 0.09949853911503082 root_mean_prior_squared_error 0.09949853911503082 root_mean_prior_squared_error 0.09949853911503082 root_mean_prior_squared_error 0.09949853911503082 root_mean_prior_squared_error 0.0994985414402977 root_mean_squared_error 0.09919656677508504 root_mean_squared_error 0.09919656677508504 root_mean_squared_error 0.09915108137536725 root_mean_squared_error 0.09920636944071876 root_mean_squared_error 0.09951054805729016 root_mean_squared_error 0.09906084690531985 root_mean_squared_error 0.09951744605007061 root_mean_squared_error 0.09916529101465349 root_mean_squared_error 0.09919607491068667 root_mean_squared_error 0.099411836569121 root_relative_squared_error 0.9969613530414945 root_relative_squared_error 0.9969613530414945 root_relative_squared_error 0.9965042083325542 root_relative_squared_error 0.9970598733745193 root_relative_squared_error 1.0001169784236377 root_relative_squared_error 0.9956010187324967 root_relative_squared_error 1.0001900222375921 root_relative_squared_error 0.9966507236855804 root_relative_squared_error 0.9969601141179122 root_relative_squared_error 0.9991285814855013 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 usercpu_time_millis 29.205421000028764 usercpu_time_millis 30.245654000054856 usercpu_time_millis 16.001767999910044 usercpu_time_millis 15.316134000045167 usercpu_time_millis 15.384154999992461 usercpu_time_millis 15.525895999871864 usercpu_time_millis 15.484481000157757 usercpu_time_millis 15.293890000066312 usercpu_time_millis 15.658787000006669 usercpu_time_millis 15.344454000000951 usercpu_time_millis_testing 3.1275560000949554 usercpu_time_millis_testing 2.9479820000233303 usercpu_time_millis_testing 0.8572209999329061 usercpu_time_millis_testing 0.8182410000472373 usercpu_time_millis_testing 0.7808450000084122 usercpu_time_millis_testing 0.8241509999606933 usercpu_time_millis_testing 0.8015000000796135 usercpu_time_millis_testing 0.7871200000408862 usercpu_time_millis_testing 0.7840979999400588 usercpu_time_millis_testing 0.8098929999960092 usercpu_time_millis_training 26.07786499993381 usercpu_time_millis_training 27.297672000031525 usercpu_time_millis_training 15.144546999977138 usercpu_time_millis_training 14.49789299999793 usercpu_time_millis_training 14.603309999984049 usercpu_time_millis_training 14.70174499991117 usercpu_time_millis_training 14.682981000078144 usercpu_time_millis_training 14.506770000025426 usercpu_time_millis_training 14.87468900006661 usercpu_time_millis_training 14.534561000004942 wall_clock_time_millis 29.28447723388672 wall_clock_time_millis 30.37571907043457 wall_clock_time_millis 16.005992889404297 wall_clock_time_millis 15.320301055908203 wall_clock_time_millis 15.387773513793945 wall_clock_time_millis 16.201019287109375 wall_clock_time_millis 15.502691268920898 wall_clock_time_millis 15.298128128051758 wall_clock_time_millis 15.66314697265625 wall_clock_time_millis 15.348672866821289 wall_clock_time_millis_testing 3.1728744506835938 wall_clock_time_millis_testing 2.9671192169189453 wall_clock_time_millis_testing 0.8597373962402344 wall_clock_time_millis_testing 0.8208751678466797 wall_clock_time_millis_testing 0.7839202880859375 wall_clock_time_millis_testing 0.8268356323242188 wall_clock_time_millis_testing 0.8046627044677734 wall_clock_time_millis_testing 0.7898807525634766 wall_clock_time_millis_testing 0.7870197296142578 wall_clock_time_millis_testing 0.8132457733154297 wall_clock_time_millis_training 26.111602783203125 wall_clock_time_millis_training 27.408599853515625 wall_clock_time_millis_training 15.146255493164062 wall_clock_time_millis_training 14.499425888061523 wall_clock_time_millis_training 14.603853225708008 wall_clock_time_millis_training 15.374183654785156 wall_clock_time_millis_training 14.698028564453125 wall_clock_time_millis_training 14.508247375488281 wall_clock_time_millis_training 14.876127243041992 wall_clock_time_millis_training 14.53542709350586