10559350
8323
Heinrich Peters
2079
Supervised Classification
18298
sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,columntransformer=sklearn.compose._column_transformer.ColumnTransformer(num=sklearn.pipeline.Pipeline(standardscaler=sklearn.preprocessing.data.StandardScaler),cat=sklearn.pipeline.Pipeline(onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)),svc=sklearn.svm.classes.SVC)(4)
8276082
copy
true
17405
with_mean
true
17405
with_std
true
17405
add_indicator
false
17407
copy
true
17407
fill_value
null
17407
missing_values
NaN
17407
strategy
"most_frequent"
17407
verbose
0
17407
categorical_features
null
17408
categories
null
17408
drop
null
17408
dtype
{"oml-python:serialized_object": "type", "value": "np.float64"}
17408
handle_unknown
"ignore"
17408
n_values
null
17408
sparse
true
17408
C
1.2019329859336583
17495
cache_size
200
17495
class_weight
null
17495
coef0
-0.8056274588169823
17495
decision_function_shape
"ovr"
17495
degree
2
17495
gamma
0.14660663245874161
17495
kernel
"rbf"
17495
max_iter
-1
17495
probability
true
17495
random_state
1
17495
shrinking
true
17495
tol
0.001
17495
verbose
false
17495
memory
null
18298
steps
[{"oml-python:serialized_object": "component_reference", "value": {"key": "simpleimputer", "step_name": "simpleimputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "columntransformer", "step_name": "columntransformer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "svc", "step_name": "svc"}}]
18298
verbose
false
18298
n_jobs
null
18299
remainder
"drop"
18299
sparse_threshold
0.3
18299
transformer_weights
null
18299
transformers
[{"oml-python:serialized_object": "component_reference", "value": {"key": "num", "step_name": "num", "argument_1": [false, true, false, false, false, true, true, true, true, false, true, true, true, true, true, true, true, true, true]}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "cat", "step_name": "cat", "argument_1": [true, false, true, true, true, false, false, false, false, true, false, false, false, false, false, false, false, false, false]}}]
18299
verbose
false
18299
memory
null
18300
steps
[{"oml-python:serialized_object": "component_reference", "value": {"key": "standardscaler", "step_name": "standardscaler"}}]
18300
verbose
false
18300
memory
null
18301
steps
[{"oml-python:serialized_object": "component_reference", "value": {"key": "onehotencoder", "step_name": "onehotencoder"}}]
18301
verbose
false
18301
openml-python
Sklearn_0.21.2.
188
eucalyptus
https://www.openml.org/data/download/3625/dataset_194_eucalyptus.arff
-1
22043665
description
https://api.openml.org/data/download/22043665/description.xml
-1
22043666
predictions
https://api.openml.org/data/download/22043666/predictions.arff
area_under_roc_curve
0.9017623034532096 [0.981855,0.904031,0.861615,0.853815,0.909577]
average_cost
0
f_measure
0.6178285821517111 [0.846995,0.509615,0.490119,0.644491,0.439024]
kappa
0.5158890754533757
kb_relative_information_score
0.5278587310816107
mean_absolute_error
0.1831534033928644
mean_prior_absolute_error
0.313229771753801
weighted_recall
0.626358695652174 [0.861111,0.495327,0.476923,0.724299,0.342857]
number_of_instances
736 [180,107,130,214,105]
precision
0.6249687180489608 [0.833333,0.524752,0.504065,0.580524,0.610169]
predictive_accuracy
0.626358695652174
prior_entropy
2.2620863489531073
relative_absolute_error
0.5847253994004862
root_mean_prior_squared_error
0.39571712668407916
root_mean_squared_error
0.3044139148878073
root_relative_squared_error
0.7692715183662904
total_cost
0
unweighted_recall
0.580103499823126 [0.861111,0.495327,0.476923,0.724299,0.342857]
area_under_roc_curve
0.916300256444859 [0.991071,0.873016,0.862547,0.897574,0.936508]
area_under_roc_curve
0.9184535768590826 [0.986111,0.903319,0.895334,0.896676,0.891775]
area_under_roc_curve
0.9059358910793338 [0.996032,0.924964,0.885246,0.83479,0.90625]
area_under_roc_curve
0.896748927870854 [0.975198,0.834055,0.852459,0.856643,0.970313]
area_under_roc_curve
0.9102788272870239 [0.987103,0.935065,0.854981,0.861014,0.925]
area_under_roc_curve
0.9068835008896485 [0.955357,0.901876,0.910467,0.863636,0.915625]
area_under_roc_curve
0.8703847191253288 [0.973737,0.887097,0.788462,0.82326,0.871429]
area_under_roc_curve
0.8945943755267661 [0.976768,0.892063,0.891026,0.831502,0.887097]
area_under_roc_curve
0.9086112051644529 [0.99899,0.936508,0.860256,0.845238,0.91349]
area_under_roc_curve
0.9027610063624205 [0.982828,0.963492,0.855128,0.826007,0.919355]
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
0.6101564722617354 [0.842105,0.315789,0.538462,0.72,0.4]
f_measure
0.6449089306698003 [0.833333,0.608696,0.521739,0.72,0.375]
f_measure
0.6488300244821983 [0.914286,0.608696,0.592593,0.64,0.307692]
f_measure
0.5781526207058122 [0.777778,0.272727,0.518519,0.638298,0.5]
f_measure
0.6006020499263743 [0.864865,0.47619,0.333333,0.625,0.555556]
f_measure
0.6574834234939994 [0.810811,0.583333,0.521739,0.695652,0.555556]
f_measure
0.5414481409001957 [0.777778,0.454545,0.48,0.612245,0.142857]
f_measure
0.6063583616575686 [0.888889,0.6,0.47619,0.6,0.315789]
f_measure
0.6651509598204058 [0.923077,0.625,0.434783,0.692308,0.5]
f_measure
0.5933271058594439 [0.833333,0.555556,0.470588,0.461538,0.631579]
kappa
0.5249643366619114
kappa
0.5622337908187411
kappa
0.5605700712589075
kappa
0.458834630809153
kappa
0.4925514305982502
kappa
0.5650129320479661
kappa
0.43024390243902444
kappa
0.5019493177387915
kappa
0.5859432799013563
kappa
0.4768275203057812
kb_relative_information_score
0.5402217742815387
kb_relative_information_score
0.5462275457870756
kb_relative_information_score
0.543413745824872
kb_relative_information_score
0.500056736963927
kb_relative_information_score
0.5389846135212101
kb_relative_information_score
0.5316273666851002
kb_relative_information_score
0.4706858371078198
kb_relative_information_score
0.5114575693543165
kb_relative_information_score
0.5537595515017365
kb_relative_information_score
0.5415983031786833
mean_absolute_error
0.17811161027809447
mean_absolute_error
0.17351079583110204
mean_absolute_error
0.17948373672405774
mean_absolute_error
0.19183589538381374
mean_absolute_error
0.18333152414657067
mean_absolute_error
0.18363471658503636
mean_absolute_error
0.19576967566495848
mean_absolute_error
0.19068927751927756
mean_absolute_error
0.17213011988443874
mean_absolute_error
0.183160135903193
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
0.6325605778191985 [0.8,0.375,0.538462,0.62069,0.75]
precision
0.6601506679092887 [0.833333,0.583333,0.6,0.62069,0.6]
precision
0.6760068892421833 [0.941176,0.583333,0.571429,0.571429,0.666667]
precision
0.586036036036036 [0.777778,0.272727,0.5,0.6,0.666667]
precision
0.5990199345462504 [0.842105,0.5,0.363636,0.576923,0.625]
precision
0.6601387825072035 [0.789474,0.538462,0.6,0.666667,0.625]
precision
0.5376712328767124 [0.777778,0.454545,0.5,0.535714,0.25]
precision
0.6179735474728388 [0.888889,0.6,0.625,0.517241,0.375]
precision
0.7021294951918019 [0.857143,0.833333,0.5,0.580645,0.8]
precision
0.6157860404435747 [0.833333,0.625,0.380952,0.5,0.75]
predictive_accuracy
0.6351351351351352
predictive_accuracy
0.6621621621621621
predictive_accuracy
0.6621621621621621
predictive_accuracy
0.581081081081081
predictive_accuracy
0.6081081081081081
predictive_accuracy
0.6621621621621621
predictive_accuracy
0.5616438356164384
predictive_accuracy
0.6164383561643836
predictive_accuracy
0.684931506849315
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
relative_absolute_error
0.5677711397770573
relative_absolute_error
0.5531050006163757
relative_absolute_error
0.5735989753774902
relative_absolute_error
0.6130743377710711
relative_absolute_error
0.5858958383875191
relative_absolute_error
0.5868647889744655
relative_absolute_error
0.6248536114697418
relative_absolute_error
0.6086093724983053
relative_absolute_error
0.5493754321888167
relative_absolute_error
0.5845791479674433
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
0.2993136822518457
root_mean_squared_error
0.29940022092683505
root_mean_squared_error
0.2966625334134576
root_mean_squared_error
0.31267102064205576
root_mean_squared_error
0.3013551787992268
root_mean_squared_error
0.3050419663248318
root_mean_squared_error
0.32893020991121114
root_mean_squared_error
0.30996091468904163
root_mean_squared_error
0.29113090683065623
root_mean_squared_error
0.2981300555096898
root_relative_squared_error
0.7552421833579172
root_relative_squared_error
0.7554605417615563
root_relative_squared_error
0.7504546400048084
root_relative_squared_error
0.7909506318037319
root_relative_squared_error
0.7623254261911435
root_relative_squared_error
0.7716517363708186
root_relative_squared_error
0.831026378575455
root_relative_squared_error
0.783064405506576
root_relative_squared_error
0.7354935402440854
root_relative_squared_error
0.7531757186726077
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
unweighted_recall
0.5659895659895661 [0.888889,0.272727,0.538462,0.857143,0.272727]
unweighted_recall
0.6122211122211123 [0.833333,0.636364,0.461538,0.857143,0.272727]
unweighted_recall
0.6135819735819735 [0.888889,0.636364,0.615385,0.727273,0.2]
unweighted_recall
0.5341569541569541 [0.777778,0.272727,0.538462,0.681818,0.4]
unweighted_recall
0.5665889665889666 [0.888889,0.454545,0.307692,0.681818,0.5]
unweighted_recall
0.6317016317016317 [0.833333,0.636364,0.461538,0.727273,0.5]
unweighted_recall
0.5016294816294817 [0.777778,0.454545,0.461538,0.714286,0.1]
unweighted_recall
0.5721034521034521 [0.888889,0.6,0.384615,0.714286,0.272727]
unweighted_recall
0.6210789210789212 [1,0.5,0.384615,0.857143,0.363636]
unweighted_recall
0.5845487845487846 [0.833333,0.5,0.615385,0.428571,0.545455]
usercpu_time_millis
354.5599999999993
usercpu_time_millis
365.5339999999967
usercpu_time_millis
358.1999999999965
usercpu_time_millis
376.36799999999937
usercpu_time_millis
353.84400000000227
usercpu_time_millis
342.0060000000049
usercpu_time_millis
342.3580000000044
usercpu_time_millis
343.9819999999969
usercpu_time_millis
351.85999999999495
usercpu_time_millis
388.3900000000011
usercpu_time_millis_testing
9.26199999999966
usercpu_time_millis_testing
8.761999999997272
usercpu_time_millis_testing
8.48999999999478
usercpu_time_millis_testing
8.592000000000155
usercpu_time_millis_testing
8.538000000001489
usercpu_time_millis_testing
8.316000000000656
usercpu_time_millis_testing
8.484000000002823
usercpu_time_millis_testing
8.545999999995502
usercpu_time_millis_testing
8.615999999996404
usercpu_time_millis_testing
9.154000000002327
usercpu_time_millis_training
345.29799999999966
usercpu_time_millis_training
356.7719999999994
usercpu_time_millis_training
349.71000000000174
usercpu_time_millis_training
367.7759999999992
usercpu_time_millis_training
345.3060000000008
usercpu_time_millis_training
333.69000000000426
usercpu_time_millis_training
333.87400000000156
usercpu_time_millis_training
335.4360000000014
usercpu_time_millis_training
343.24399999999855
usercpu_time_millis_training
379.2359999999988
wall_clock_time_millis
178.2996654510498
wall_clock_time_millis
184.97490882873535
wall_clock_time_millis
181.44893646240234
wall_clock_time_millis
194.75817680358887
wall_clock_time_millis
178.5256862640381
wall_clock_time_millis
172.49774932861328
wall_clock_time_millis
172.60289192199707
wall_clock_time_millis
173.30694198608398
wall_clock_time_millis
178.9572238922119
wall_clock_time_millis
200.84691047668457
wall_clock_time_millis_testing
4.654645919799805
wall_clock_time_millis_testing
4.44793701171875
wall_clock_time_millis_testing
4.298925399780273
wall_clock_time_millis_testing
4.308938980102539
wall_clock_time_millis_testing
4.275798797607422
wall_clock_time_millis_testing
4.20379638671875
wall_clock_time_millis_testing
4.3468475341796875
wall_clock_time_millis_testing
4.318952560424805
wall_clock_time_millis_testing
4.558086395263672
wall_clock_time_millis_testing
4.728078842163086
wall_clock_time_millis_training
173.64501953125
wall_clock_time_millis_training
180.5269718170166
wall_clock_time_millis_training
177.15001106262207
wall_clock_time_millis_training
190.44923782348633
wall_clock_time_millis_training
174.24988746643066
wall_clock_time_millis_training
168.29395294189453
wall_clock_time_millis_training
168.25604438781738
wall_clock_time_millis_training
168.98798942565918
wall_clock_time_millis_training
174.39913749694824
wall_clock_time_millis_training
196.11883163452148
weighted_recall
0.6351351351351351 [0.888889,0.272727,0.538462,0.857143,0.272727]
weighted_recall
0.6621621621621622 [0.833333,0.636364,0.461538,0.857143,0.272727]
weighted_recall
0.6621621621621622 [0.888889,0.636364,0.615385,0.727273,0.2]
weighted_recall
0.581081081081081 [0.777778,0.272727,0.538462,0.681818,0.4]
weighted_recall
0.6081081081081081 [0.888889,0.454545,0.307692,0.681818,0.5]
weighted_recall
0.6621621621621622 [0.833333,0.636364,0.461538,0.727273,0.5]
weighted_recall
0.5616438356164384 [0.777778,0.454545,0.461538,0.714286,0.1]
weighted_recall
0.6164383561643836 [0.888889,0.6,0.384615,0.714286,0.272727]
weighted_recall
0.684931506849315 [1,0.5,0.384615,0.857143,0.363636]
weighted_recall
0.589041095890411 [0.833333,0.5,0.615385,0.428571,0.545455]