10559339
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)
8276071
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
49.7233002061335
17495
cache_size
200
17495
class_weight
null
17495
coef0
0.46757379405725374
17495
decision_function_shape
"ovr"
17495
degree
1
17495
gamma
0.003603475971010618
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
22043643
description
https://api.openml.org/data/download/22043643/description.xml
-1
22043644
predictions
https://api.openml.org/data/download/22043644/predictions.arff
area_under_roc_curve
0.9152699628981743 [0.979966,0.929349,0.881328,0.879803,0.904324]
average_cost
0
f_measure
0.674664040439913 [0.857143,0.604651,0.539419,0.70021,0.548571]
kappa
0.5871662553286965
kb_relative_information_score
0.567159933216641
mean_absolute_error
0.1738943134269862
mean_prior_absolute_error
0.313229771753801
weighted_recall
0.6807065217391305 [0.866667,0.607477,0.5,0.780374,0.457143]
number_of_instances
736 [180,107,130,214,105]
precision
0.6807322031051407 [0.847826,0.601852,0.585586,0.634981,0.685714]
predictive_accuracy
0.6807065217391305
prior_entropy
2.2620863489531073
relative_absolute_error
0.5551653422129597
root_mean_prior_squared_error
0.39571712668407916
root_mean_squared_error
0.2909928462497165
root_relative_squared_error
0.7353557039294654
total_cost
0
unweighted_recall
0.6423319982198488 [0.866667,0.607477,0.5,0.780374,0.457143]
area_under_roc_curve
0.9187239081686963 [0.982143,0.922078,0.865069,0.884996,0.939394]
area_under_roc_curve
0.9228703373073928 [0.950397,0.922078,0.93947,0.948787,0.809524]
area_under_roc_curve
0.9064240236115235 [0.992063,0.948052,0.846154,0.850524,0.907813]
area_under_roc_curve
0.9269642491978558 [0.972222,0.883117,0.905422,0.905594,0.96875]
area_under_roc_curve
0.8974438811785124 [0.974206,0.937951,0.800757,0.854021,0.935937]
area_under_roc_curve
0.9222206846438404 [0.962302,0.894661,0.92686,0.916958,0.885938]
area_under_roc_curve
0.9006857506415614 [0.989899,0.917889,0.85,0.846154,0.901587]
area_under_roc_curve
0.9234324373520131 [0.994949,0.952381,0.942308,0.867216,0.865103]
area_under_roc_curve
0.913572995963628 [1,0.973016,0.869231,0.837912,0.914956]
area_under_roc_curve
0.9247847993318609 [0.981818,0.949206,0.871795,0.893773,0.931085]
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
0.6388217164532954 [0.8,0.5,0.583333,0.666667,0.526316]
f_measure
0.7478179650238475 [0.823529,0.666667,0.666667,0.84,0.625]
f_measure
0.6120030856055702 [0.888889,0.583333,0.434783,0.612245,0.375]
f_measure
0.7092431567221482 [0.857143,0.666667,0.5,0.734694,0.705882]
f_measure
0.670904172672106 [0.864865,0.631579,0.4,0.693878,0.666667]
f_measure
0.6830989152417724 [0.777778,0.47619,0.583333,0.77551,0.666667]
f_measure
0.6381142811997882 [0.857143,0.608696,0.583333,0.716981,0.181818]
f_measure
0.6977609002784273 [0.918919,0.631579,0.666667,0.651163,0.521739]
f_measure
0.6483521557115262 [0.972973,0.7,0.416667,0.595745,0.444444]
f_measure
0.670151988424711 [0.810811,0.555556,0.551724,0.697674,0.631579]
kappa
0.5468676401318889
kappa
0.6857008022652195
kappa
0.5095857988165681
kappa
0.6334041047416843
kappa
0.5787476280834914
kappa
0.5971597633136094
kappa
0.5691096901131333
kappa
0.6139423076923077
kappa
0.5571463237078379
kappa
0.5777295733911787
kb_relative_information_score
0.5514713826917055
kb_relative_information_score
0.6104285134703616
kb_relative_information_score
0.5658884377699469
kb_relative_information_score
0.5810625542277111
kb_relative_information_score
0.5356665993806013
kb_relative_information_score
0.5467419949777624
kb_relative_information_score
0.5512488281397528
kb_relative_information_score
0.5765878099586764
kb_relative_information_score
0.579071453543678
kb_relative_information_score
0.5733833571915662
mean_absolute_error
0.17797142283770592
mean_absolute_error
0.1612616769474264
mean_absolute_error
0.17461177782744833
mean_absolute_error
0.1709657794390945
mean_absolute_error
0.185398360990426
mean_absolute_error
0.1788606193305983
mean_absolute_error
0.17783531091989446
mean_absolute_error
0.17127152331630194
mean_absolute_error
0.1674389790018512
mean_absolute_error
0.17324955000417228
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
0.6415506415506416 [0.727273,0.555556,0.636364,0.625,0.625]
precision
0.786225307777032 [0.875,0.615385,0.727273,0.724138,1]
precision
0.6168283668283668 [0.888889,0.538462,0.5,0.555556,0.5]
precision
0.7377521954727836 [0.882353,0.5625,0.714286,0.666667,0.857143]
precision
0.6780596385859543 [0.842105,0.75,0.416667,0.62963,0.75]
precision
0.6858676858676859 [0.777778,0.5,0.636364,0.703704,0.75]
precision
0.7265821490489098 [0.882353,0.583333,0.636364,0.59375,1]
precision
0.6998645430512771 [0.894737,0.666667,0.727273,0.636364,0.5]
precision
0.6514401244033543 [0.947368,0.7,0.454545,0.538462,0.571429]
precision
0.6784754538900177 [0.789474,0.625,0.5,0.681818,0.75]
predictive_accuracy
0.6486486486486487
predictive_accuracy
0.7567567567567568
predictive_accuracy
0.6216216216216216
predictive_accuracy
0.7162162162162162
predictive_accuracy
0.6756756756756757
predictive_accuracy
0.6891891891891891
predictive_accuracy
0.6712328767123288
predictive_accuracy
0.6986301369863014
predictive_accuracy
0.6575342465753425
predictive_accuracy
0.6712328767123288
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
0.5673242605270885
relative_absolute_error
0.5140581570165088
relative_absolute_error
0.5580290374979776
relative_absolute_error
0.5463770573355463
relative_absolute_error
0.59250109141794
relative_absolute_error
0.5716075999751733
relative_absolute_error
0.5676110761163733
relative_absolute_error
0.5466351107330908
relative_absolute_error
0.5344030522732018
relative_absolute_error
0.5529482374959103
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
0.2984925092653696
root_mean_squared_error
0.2771167976863458
root_mean_squared_error
0.2934741657964862
root_mean_squared_error
0.28176481617050514
root_mean_squared_error
0.30116815063106406
root_mean_squared_error
0.3020226994085734
root_mean_squared_error
0.2959251124949918
root_mean_squared_error
0.28450345347562983
root_mean_squared_error
0.2832973085468397
root_mean_squared_error
0.29085215306814755
root_relative_squared_error
0.7531701615426936
root_relative_squared_error
0.6992339733861246
root_relative_squared_error
0.7423891615479704
root_relative_squared_error
0.7127685159708317
root_relative_squared_error
0.7618523089592694
root_relative_squared_error
0.764014024791105
root_relative_squared_error
0.7476405850123323
root_relative_squared_error
0.7187503878802376
root_relative_squared_error
0.7157032644628694
root_relative_squared_error
0.7347893154887142
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
0.6101454101454101 [0.888889,0.454545,0.538462,0.714286,0.454545]
unweighted_recall
0.714996114996115 [0.777778,0.727273,0.615385,1,0.454545]
unweighted_recall
0.5783372183372182 [0.888889,0.636364,0.384615,0.681818,0.3]
unweighted_recall
0.690862470862471 [0.833333,0.818182,0.384615,0.818182,0.6]
unweighted_recall
0.6383372183372183 [0.888889,0.545455,0.384615,0.772727,0.6]
unweighted_recall
0.6468842268842269 [0.777778,0.454545,0.538462,0.863636,0.6]
unweighted_recall
0.6025840825840826 [0.833333,0.636364,0.538462,0.904762,0.1]
unweighted_recall
0.6743900543900543 [0.944444,0.6,0.615385,0.666667,0.545455]
unweighted_recall
0.622983682983683 [1,0.7,0.384615,0.666667,0.363636]
unweighted_recall
0.6416916416916417 [0.833333,0.5,0.615385,0.714286,0.545455]
usercpu_time_millis
174.16000000000054
usercpu_time_millis
192.54199999999955
usercpu_time_millis
173.1739999999995
usercpu_time_millis
188.7480000000004
usercpu_time_millis
177.8720000000007
usercpu_time_millis
197.92400000000043
usercpu_time_millis
203.35999999999999
usercpu_time_millis
211.90599999999992
usercpu_time_millis
196.47599999999966
usercpu_time_millis
200.52200000000033
usercpu_time_millis_testing
7.103999999999999
usercpu_time_millis_testing
7.6019999999994425
usercpu_time_millis_testing
7.163999999999504
usercpu_time_millis_testing
7.355999999999696
usercpu_time_millis_testing
7.716000000000278
usercpu_time_millis_testing
7.810000000000095
usercpu_time_millis_testing
10.796000000000028
usercpu_time_millis_testing
7.305999999999813
usercpu_time_millis_testing
7.678000000000296
usercpu_time_millis_testing
9.999999999999787
usercpu_time_millis_training
167.05600000000055
usercpu_time_millis_training
184.9400000000001
usercpu_time_millis_training
166.01
usercpu_time_millis_training
181.39200000000068
usercpu_time_millis_training
170.1560000000004
usercpu_time_millis_training
190.11400000000035
usercpu_time_millis_training
192.56399999999996
usercpu_time_millis_training
204.6000000000001
usercpu_time_millis_training
188.79799999999935
usercpu_time_millis_training
190.52200000000053
wall_clock_time_millis
87.62979507446289
wall_clock_time_millis
97.4729061126709
wall_clock_time_millis
87.13102340698242
wall_clock_time_millis
94.65479850769043
wall_clock_time_millis
90.2547836303711
wall_clock_time_millis
113.32297325134277
wall_clock_time_millis
105.75604438781738
wall_clock_time_millis
110.23783683776855
wall_clock_time_millis
103.07002067565918
wall_clock_time_millis
106.97293281555176
wall_clock_time_millis_testing
3.5598278045654297
wall_clock_time_millis_testing
3.8080215454101562
wall_clock_time_millis_testing
3.626108169555664
wall_clock_time_millis_testing
3.6809444427490234
wall_clock_time_millis_testing
3.8809776306152344
wall_clock_time_millis_testing
3.957033157348633
wall_clock_time_millis_testing
5.515098571777344
wall_clock_time_millis_testing
3.6649703979492188
wall_clock_time_millis_testing
3.9539337158203125
wall_clock_time_millis_testing
5.7048797607421875
wall_clock_time_millis_training
84.06996726989746
wall_clock_time_millis_training
93.66488456726074
wall_clock_time_millis_training
83.50491523742676
wall_clock_time_millis_training
90.9738540649414
wall_clock_time_millis_training
86.37380599975586
wall_clock_time_millis_training
109.36594009399414
wall_clock_time_millis_training
100.24094581604004
wall_clock_time_millis_training
106.57286643981934
wall_clock_time_millis_training
99.11608695983887
wall_clock_time_millis_training
101.26805305480957
weighted_recall
0.6486486486486487 [0.888889,0.454545,0.538462,0.714286,0.454545]
weighted_recall
0.7567567567567568 [0.777778,0.727273,0.615385,1,0.454545]
weighted_recall
0.6216216216216216 [0.888889,0.636364,0.384615,0.681818,0.3]
weighted_recall
0.7162162162162162 [0.833333,0.818182,0.384615,0.818182,0.6]
weighted_recall
0.6756756756756757 [0.888889,0.545455,0.384615,0.772727,0.6]
weighted_recall
0.6891891891891891 [0.777778,0.454545,0.538462,0.863636,0.6]
weighted_recall
0.6712328767123288 [0.833333,0.636364,0.538462,0.904762,0.1]
weighted_recall
0.6986301369863014 [0.944444,0.6,0.615385,0.666667,0.545455]
weighted_recall
0.6575342465753424 [1,0.7,0.384615,0.666667,0.363636]
weighted_recall
0.6712328767123288 [0.833333,0.5,0.615385,0.714286,0.545455]