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