10228407 6138 Felix Neutatz 2079 Supervised Classification 12323 sklearn.pipeline.C376930c43c8605(n14=sklearn.pipeline.C58a84e06c7285(n15=sklearn.pipeline.C58a84e06c709f(n16=sklearn.compose._column_transformer.C376930c43c61cd(n17=sklearn.preprocessing._function_transformer.C376930c43c5e94)),n18=sklearn.pipeline.C376930c43c742d(n19=sklearn.compose._column_transformer.C376930c43c70f7(n20=sklearn.preprocessing._function_transformer.C376930c43c6f47))),n21=fastsklearnfeature.transformations.HigherOrderCommutativeTransformation.C58a84e06c7320,n22=fastsklearnfeature.transformations.MinMaxScalingTransformation.C376930c43c839a,c=sklearn.linear_model.logistic.LogisticRegression)(1) 8153672 C 100 9801 class_weight "balanced" 9801 dual false 9801 fit_intercept true 9801 intercept_scaling 1 9801 max_iter 10000 9801 multi_class "auto" 9801 n_jobs null 9801 penalty "l2" 9801 random_state 31897 9801 solver "lbfgs" 9801 tol 0.0001 9801 verbose 0 9801 warm_start false 9801 memory null 12323 steps [{"oml-python:serialized_object": "component_reference", "value": {"key": "n14", "step_name": "n14"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "n21", "step_name": "n21"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "n22", "step_name": "n22"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "c", "step_name": "c"}}] 12323 n_jobs null 12324 transformer_list [{"oml-python:serialized_object": "component_reference", "value": {"key": "n15", "step_name": "n15"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "n18", "step_name": "n18"}}] 12324 transformer_weights null 12324 memory null 12325 steps [{"oml-python:serialized_object": "component_reference", "value": {"key": "n16", "step_name": "n16"}}] 12325 n_jobs null 12326 remainder "drop" 12326 sparse_threshold 0.3 12326 transformer_weights null 12326 transformers [{"oml-python:serialized_object": "component_reference", "value": {"key": "n17", "step_name": "n17", "argument_1": [14]}}] 12326 accept_sparse false 12327 check_inverse true 12327 func {"oml-python:serialized_object": "function", "value": "fastsklearnfeature.candidates.Identity.identity"} 12327 inv_kw_args null 12327 inverse_func null 12327 kw_args null 12327 pass_y "deprecated" 12327 validate false 12327 memory null 12328 steps [{"oml-python:serialized_object": "component_reference", "value": {"key": "n19", "step_name": "n19"}}] 12328 n_jobs null 12329 remainder "drop" 12329 sparse_threshold 0.3 12329 transformer_weights null 12329 transformers [{"oml-python:serialized_object": "component_reference", "value": {"key": "n20", "step_name": "n20", "argument_1": [17]}}] 12329 accept_sparse false 12330 check_inverse true 12330 func {"oml-python:serialized_object": "function", "value": "fastsklearnfeature.candidates.Identity.identity"} 12330 inv_kw_args null 12330 inverse_func null 12330 kw_args null 12330 pass_y "deprecated" 12330 validate false 12330 method {"oml-python:serialized_object": "function", "value": "numpy.nansum"} 12331 number_parent_features 2 12331 sympy_method 0 12331 ComplexityDriven openml-python Sklearn_0.20.3. 188 eucalyptus https://www.openml.org/data/download/3625/dataset_194_eucalyptus.arff -1 21378044 description https://api.openml.org/data/download/21378044/description.xml -1 21378045 predictions https://api.openml.org/data/download/21378045/predictions.arff area_under_roc_curve 0.861410439190224 [0.948681,0.840171,0.788639,0.821132,0.905637] average_cost 0 f_measure 0.5756784905061075 [0.802395,0.480349,0.447458,0.495868,0.605578] kappa 0.4636511696772283 kb_relative_information_score 0.4448438354303627 mean_absolute_error 0.2156593741474802 mean_prior_absolute_error 0.313229771753801 number_of_instances 736 [180,107,130,214,105] precision 0.5988863597206898 [0.87013,0.45082,0.4,0.604027,0.520548] predictive_accuracy 0.5720108695652174 prior_entropy 2.2620863489531073 recall 0.5720108695652174 [0.744444,0.514019,0.507692,0.420561,0.72381] relative_absolute_error 0.6885021591018773 root_mean_prior_squared_error 0.39571712668407916 root_mean_squared_error 0.32739735230637124 root_relative_squared_error 0.8273519901698593 total_cost 0 area_under_roc_curve 0.874219119366815 [0.989087,0.825397,0.840479,0.814915,0.888167] area_under_roc_curve 0.8906070510327392 [0.948909,0.816739,0.823455,0.885894,0.957431] area_under_roc_curve 0.8406604670052416 [0.985615,0.813131,0.77995,0.757867,0.871094] area_under_roc_curve 0.8761838043344189 [0.952381,0.833333,0.691047,0.910402,0.951562] area_under_roc_curve 0.8583566332669815 [0.901786,0.891053,0.773644,0.819493,0.939844] area_under_roc_curve 0.8989151742097438 [0.954861,0.900433,0.870113,0.878497,0.878906] area_under_roc_curve 0.8697547603866649 [0.964646,0.751466,0.826923,0.855311,0.915079] area_under_roc_curve 0.8595713499933562 [0.963131,0.866667,0.841026,0.789835,0.83871] area_under_roc_curve 0.8364866267429236 [0.958586,0.865873,0.719231,0.748168,0.917155] area_under_roc_curve 0.8481257511085174 [0.90404,0.87381,0.763462,0.798077,0.928886] 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 f_measure 0.5745963739206982 [0.864865,0.416667,0.461538,0.457143,0.615385] f_measure 0.5530818837270449 [0.709677,0.444444,0.516129,0.451613,0.642857] f_measure 0.5830458715854253 [0.882353,0.454545,0.482759,0.461538,0.583333] f_measure 0.614045864045864 [0.777778,0.333333,0.307692,0.75,0.727273] f_measure 0.5508958206326628 [0.75,0.583333,0.307692,0.473684,0.642857] f_measure 0.5847110240492593 [0.833333,0.444444,0.5625,0.470588,0.571429] f_measure 0.5870568619833032 [0.774194,0.5,0.428571,0.585366,0.555556] f_measure 0.5516870640158311 [0.787879,0.5,0.533333,0.432432,0.461538] f_measure 0.5379421783934274 [0.882353,0.5,0.342857,0.352941,0.592593] f_measure 0.5899935949089858 [0.733333,0.615385,0.5,0.470588,0.666667] kappa 0.47421498968599585 kappa 0.44937993235625706 kappa 0.47203682393555807 kappa 0.503700277520814 kappa 0.44246575342465755 kappa 0.4936131386861314 kappa 0.4628530738191312 kappa 0.43143733773896625 kappa 0.41544983513895434 kappa 0.4895104895104895 kb_relative_information_score 0.46169271024148606 kb_relative_information_score 0.45688333575399165 kb_relative_information_score 0.43605565605842955 kb_relative_information_score 0.4599306286490048 kb_relative_information_score 0.4382130422293811 kb_relative_information_score 0.46928568825835115 kb_relative_information_score 0.4226769569121881 kb_relative_information_score 0.42604355647741776 kb_relative_information_score 0.4424185948518081 kb_relative_information_score 0.4344922616187476 mean_absolute_error 0.21000641293246325 mean_absolute_error 0.21311538975515934 mean_absolute_error 0.21584106335431566 mean_absolute_error 0.20854568048338926 mean_absolute_error 0.2192519711147196 mean_absolute_error 0.21049418761594235 mean_absolute_error 0.22400050131549762 mean_absolute_error 0.22006935742005604 mean_absolute_error 0.21584322488461216 mean_absolute_error 0.21965474081274655 mean_prior_absolute_error 0.3137031768610717 mean_prior_absolute_error 0.3137031768610717 mean_prior_absolute_error 0.3129080497501551 mean_prior_absolute_error 0.3129080497501551 mean_prior_absolute_error 0.3129080497501551 mean_prior_absolute_error 0.3129080497501551 mean_prior_absolute_error 0.31330486384559936 mean_prior_absolute_error 0.3133196531898768 mean_prior_absolute_error 0.3133196531898768 mean_prior_absolute_error 0.3133196531898768 number_of_instances 74 [18,11,13,21,11] number_of_instances 74 [18,11,13,21,11] number_of_instances 74 [18,11,13,22,10] number_of_instances 74 [18,11,13,22,10] number_of_instances 74 [18,11,13,22,10] number_of_instances 74 [18,11,13,22,10] number_of_instances 73 [18,11,13,21,10] number_of_instances 73 [18,10,13,21,11] number_of_instances 73 [18,10,13,21,11] number_of_instances 73 [18,10,13,21,11] precision 0.5845314950578109 [0.842105,0.384615,0.461538,0.571429,0.533333] precision 0.6169875191934014 [0.846154,0.375,0.444444,0.7,0.529412] precision 0.5974264705882353 [0.9375,0.454545,0.4375,0.529412,0.5] precision 0.6268191268191269 [0.777778,0.307692,0.307692,0.833333,0.666667] precision 0.5773871398871399 [0.857143,0.538462,0.307692,0.5625,0.5] precision 0.6291178396441555 [0.833333,0.571429,0.473684,0.666667,0.444444] precision 0.619106799727267 [0.923077,0.411765,0.4,0.6,0.625] precision 0.5701047542304593 [0.866667,0.5,0.470588,0.5,0.4] precision 0.5791702589647795 [0.9375,0.666667,0.272727,0.461538,0.5] precision 0.6392601630525206 [0.916667,0.5,0.421053,0.615385,0.615385] predictive_accuracy 0.581081081081081 predictive_accuracy 0.5540540540540541 predictive_accuracy 0.581081081081081 predictive_accuracy 0.6081081081081081 predictive_accuracy 0.5540540540540541 predictive_accuracy 0.5945945945945946 predictive_accuracy 0.5753424657534246 predictive_accuracy 0.547945205479452 predictive_accuracy 0.5342465753424658 predictive_accuracy 0.589041095890411 prior_entropy 2.270428889699664 prior_entropy 2.270428889699664 prior_entropy 2.2566414249020115 prior_entropy 2.2566414249020115 prior_entropy 2.2566414249020115 prior_entropy 2.2566414249020115 prior_entropy 2.2631003912333214 prior_entropy 2.263469802844284 prior_entropy 2.263469802844284 prior_entropy 2.263469802844284 recall 0.581081081081081 [0.888889,0.454545,0.461538,0.380952,0.727273] recall 0.5540540540540541 [0.611111,0.545455,0.615385,0.333333,0.818182] recall 0.581081081081081 [0.833333,0.454545,0.538462,0.409091,0.7] recall 0.6081081081081081 [0.777778,0.363636,0.307692,0.681818,0.8] recall 0.5540540540540541 [0.666667,0.636364,0.307692,0.409091,0.9] recall 0.5945945945945946 [0.833333,0.363636,0.692308,0.363636,0.8] recall 0.5753424657534246 [0.666667,0.636364,0.461538,0.571429,0.5] recall 0.547945205479452 [0.722222,0.5,0.615385,0.380952,0.545455] recall 0.5342465753424658 [0.833333,0.4,0.461538,0.285714,0.727273] recall 0.589041095890411 [0.611111,0.8,0.615385,0.380952,0.727273] relative_absolute_error 0.6694430545262468 relative_absolute_error 0.6793536230254397 relative_absolute_error 0.6897907021780243 relative_absolute_error 0.6664759204817672 relative_absolute_error 0.7006913733596299 relative_absolute_error 0.6727030122236028 relative_absolute_error 0.714960178294225 relative_absolute_error 0.702379678962208 relative_absolute_error 0.6888914330369427 relative_absolute_error 0.7010563766953751 root_mean_prior_squared_error 0.39631483628344655 root_mean_prior_squared_error 0.39631483628344655 root_mean_prior_squared_error 0.395310412647401 root_mean_prior_squared_error 0.395310412647401 root_mean_prior_squared_error 0.395310412647401 root_mean_prior_squared_error 0.395310412647401 root_mean_prior_squared_error 0.3958119963352585 root_mean_prior_squared_error 0.3958306781784102 root_mean_prior_squared_error 0.3958306781784102 root_mean_prior_squared_error 0.3958306781784102 root_mean_squared_error 0.32440595195997013 root_mean_squared_error 0.3224109921873508 root_mean_squared_error 0.32976100854272394 root_mean_squared_error 0.3189191390206704 root_mean_squared_error 0.3317351329563279 root_mean_squared_error 0.3187872820015636 root_mean_squared_error 0.32839446753667284 root_mean_squared_error 0.3336566693925689 root_mean_squared_error 0.33153874093765545 root_mean_squared_error 0.33414250967327547 root_relative_squared_error 0.8185561635849363 root_relative_squared_error 0.8135223884395806 root_relative_squared_error 0.8341824500253067 root_relative_squared_error 0.806756232108492 root_relative_squared_error 0.839176308902899 root_relative_squared_error 0.8064226789945637 root_relative_squared_error 0.8296728511950354 root_relative_squared_error 0.8429277663066377 root_relative_squared_error 0.8375771743195284 root_relative_squared_error 0.8441551605120147 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 41.05596700000547 usercpu_time_millis 30.394374000003666 usercpu_time_millis 32.59720500000185 usercpu_time_millis 33.82179500000149 usercpu_time_millis 31.185792999998796 usercpu_time_millis 27.19918300000046 usercpu_time_millis 28.738377999999898 usercpu_time_millis 35.59988199999964 usercpu_time_millis 30.198462000001314 usercpu_time_millis 34.67547299999296 usercpu_time_millis_testing 2.0628740000034895 usercpu_time_millis_testing 1.6433589999991227 usercpu_time_millis_testing 1.4415880000058223 usercpu_time_millis_testing 1.4537440000026436 usercpu_time_millis_testing 1.44960999999455 usercpu_time_millis_testing 1.4379679999976247 usercpu_time_millis_testing 1.4731429999983447 usercpu_time_millis_testing 1.4381339999971487 usercpu_time_millis_testing 1.4383179999981621 usercpu_time_millis_testing 1.4471889999967402 usercpu_time_millis_training 38.99309300000198 usercpu_time_millis_training 28.751015000004543 usercpu_time_millis_training 31.155616999996028 usercpu_time_millis_training 32.36805099999884 usercpu_time_millis_training 29.736183000004246 usercpu_time_millis_training 25.761215000002835 usercpu_time_millis_training 27.265235000001553 usercpu_time_millis_training 34.16174800000249 usercpu_time_millis_training 28.76014400000315 usercpu_time_millis_training 33.22828399999622