10444956
8323
Heinrich Peters
125920
Supervised Classification
17651
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)),randomforestclassifier=sklearn.ensemble.forest.RandomForestClassifier)(1)
8263646
add_indicator
false
12737
copy
true
12737
fill_value
null
12737
missing_values
NaN
12737
strategy
"most_frequent"
12737
verbose
0
12737
copy
true
13294
with_mean
true
13294
with_std
true
13294
categorical_features
null
16348
categories
null
16348
drop
null
16348
dtype
{"oml-python:serialized_object": "type", "value": "np.float64"}
16348
handle_unknown
"ignore"
16348
n_values
null
16348
sparse
true
16348
n_jobs
null
16375
remainder
"drop"
16375
sparse_threshold
0.3
16375
transformer_weights
null
16375
transformers
[{"oml-python:serialized_object": "component_reference", "value": {"key": "num", "step_name": "num", "argument_1": [false, false, true, false, false, false, false, false, false, false, false, false]}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "cat", "step_name": "cat", "argument_1": [true, true, false, true, true, true, true, true, true, true, true, true]}}]
16375
verbose
false
16375
memory
null
16376
steps
[{"oml-python:serialized_object": "component_reference", "value": {"key": "standardscaler", "step_name": "standardscaler"}}]
16376
verbose
false
16376
memory
null
16377
steps
[{"oml-python:serialized_object": "component_reference", "value": {"key": "onehotencoder", "step_name": "onehotencoder"}}]
16377
verbose
false
16377
bootstrap
false
17650
class_weight
null
17650
criterion
"entropy"
17650
max_depth
null
17650
max_features
0.8505427867970985
17650
max_leaf_nodes
null
17650
min_impurity_decrease
0
17650
min_impurity_split
null
17650
min_samples_leaf
1
17650
min_samples_split
2
17650
min_weight_fraction_leaf
0.0
17650
n_estimators
300
17650
n_jobs
1
17650
oob_score
false
17650
random_state
1
17650
verbose
0
17650
warm_start
false
17650
memory
null
17651
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": "randomforestclassifier", "step_name": "randomforestclassifier"}}]
17651
verbose
false
17651
openml-python
Sklearn_0.21.2.
23381
dresses-sales
https://www.openml.org/data/download/1910507/phpcFPMhq
-1
21814341
description
https://api.openml.org/data/download/21814341/description.xml
-1
21814342
predictions
https://api.openml.org/data/download/21814342/predictions.arff
area_under_roc_curve
0.5579392446633826 [0.557939,0.557939]
average_cost
0
f_measure
0.5356872030122165 [0.601375,0.444976]
kappa
0.046366326866162495
kb_relative_information_score
0.05421639354153825
mean_absolute_error
0.45566333333333353
mean_prior_absolute_error
0.4872509960159361
weighted_recall
0.536 [0.603448,0.442857]
number_of_instances
500 [290,210]
precision
0.5353912012644889 [0.599315,0.447115]
predictive_accuracy
0.536
prior_entropy
0.9814541958069474
relative_absolute_error
0.935171681657128
root_mean_prior_squared_error
0.4935586100816085
root_mean_squared_error
0.5699717585596286
root_relative_squared_error
1.15482081948765
total_cost
0
unweighted_recall
0.5231527093596059 [0.603448,0.442857]
area_under_roc_curve
0.45320197044334976 [0.453202,0.453202]
area_under_roc_curve
0.6009852216748769 [0.600985,0.600985]
area_under_roc_curve
0.5853858784893268 [0.585386,0.585386]
area_under_roc_curve
0.43185550082101815 [0.431856,0.431856]
area_under_roc_curve
0.5213464696223317 [0.521346,0.521346]
area_under_roc_curve
0.4688013136288998 [0.468801,0.468801]
area_under_roc_curve
0.6789819376026273 [0.678982,0.678982]
area_under_roc_curve
0.6863711001642037 [0.686371,0.686371]
area_under_roc_curve
0.5246305418719212 [0.524631,0.524631]
area_under_roc_curve
0.5673234811165845 [0.567323,0.567323]
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
0.52 [0.586207,0.428571]
f_measure
0.52 [0.586207,0.428571]
f_measure
0.5811995104039168 [0.631579,0.511628]
f_measure
0.3950000000000001 [0.5,0.25]
f_measure
0.44272727272727275 [0.5,0.363636]
f_measure
0.5509362279511534 [0.686567,0.363636]
f_measure
0.6210852713178293 [0.666667,0.55814]
f_measure
0.62228823765556 [0.641509,0.595745]
f_measure
0.5030303030303029 [0.545455,0.444444]
f_measure
0.5741740226986128 [0.655738,0.461538]
kappa
0.014778325123152677
kappa
0.014778325123152677
kappa
0.14355628058727551
kappa
-0.2479201331114808
kappa
-0.13452188006482974
kappa
0.08376963350785338
kappa
0.22512234910277315
kappa
0.2448330683624801
kappa
-0.006441223832528141
kappa
0.12060301507537685
kb_relative_information_score
-0.0345208744753934
kb_relative_information_score
0.09858718010089319
kb_relative_information_score
0.09636590030993952
kb_relative_information_score
-0.10849433667638315
kb_relative_information_score
-0.01965872312952395
kb_relative_information_score
0.07499403741017746
kb_relative_information_score
0.17153911148563686
kb_relative_information_score
0.19617471630346398
kb_relative_information_score
-0.026887542680949384
kb_relative_information_score
0.09406446676751981
mean_absolute_error
0.5033666666666666
mean_absolute_error
0.43000000000000016
mean_absolute_error
0.4364666666666666
mean_absolute_error
0.5260333333333336
mean_absolute_error
0.48419999999999985
mean_absolute_error
0.4527999999999999
mean_absolute_error
0.4001333333333335
mean_absolute_error
0.3900666666666666
mean_absolute_error
0.49176666666666663
mean_absolute_error
0.4417999999999999
mean_prior_absolute_error
0.48725099601593624
mean_prior_absolute_error
0.48725099601593624
mean_prior_absolute_error
0.48725099601593624
mean_prior_absolute_error
0.48725099601593624
mean_prior_absolute_error
0.48725099601593624
mean_prior_absolute_error
0.48725099601593624
mean_prior_absolute_error
0.48725099601593624
mean_prior_absolute_error
0.48725099601593624
mean_prior_absolute_error
0.48725099601593624
mean_prior_absolute_error
0.48725099601593624
number_of_instances
50 [29,21]
number_of_instances
50 [29,21]
number_of_instances
50 [29,21]
number_of_instances
50 [29,21]
number_of_instances
50 [29,21]
number_of_instances
50 [29,21]
number_of_instances
50 [29,21]
number_of_instances
50 [29,21]
number_of_instances
50 [29,21]
number_of_instances
50 [29,21]
precision
0.52 [0.586207,0.428571]
precision
0.52 [0.586207,0.428571]
precision
0.582857142857143 [0.642857,0.5]
precision
0.39117147707979627 [0.483871,0.263158]
precision
0.44682769726247984 [0.518519,0.347826]
precision
0.5610526315789474 [0.605263,0.5]
precision
0.6226623376623377 [0.678571,0.545455]
precision
0.6369871794871795 [0.708333,0.538462]
precision
0.5096153846153846 [0.576923,0.416667]
precision
0.5725 [0.625,0.5]
predictive_accuracy
0.52
predictive_accuracy
0.52
predictive_accuracy
0.58
predictive_accuracy
0.4
predictive_accuracy
0.44
predictive_accuracy
0.58
predictive_accuracy
0.62
predictive_accuracy
0.62
predictive_accuracy
0.5
predictive_accuracy
0.58
prior_entropy
0.9814541958069504
prior_entropy
0.9814541958069504
prior_entropy
0.9814541958069504
prior_entropy
0.9814541958069504
prior_entropy
0.9814541958069504
prior_entropy
0.9814541958069504
prior_entropy
0.9814541958069504
prior_entropy
0.9814541958069504
prior_entropy
0.9814541958069504
prior_entropy
0.9814541958069504
relative_absolute_error
1.0330746797492505
relative_absolute_error
0.8825020441537207
relative_absolute_error
0.8957737803216135
relative_absolute_error
1.0795941673480518
relative_absolute_error
0.9937383483237937
relative_absolute_error
0.9292951757972199
relative_absolute_error
0.8212057781411832
relative_absolute_error
0.8005456527664212
relative_absolute_error
1.0092676478604523
relative_absolute_error
0.9067195421095665
root_mean_prior_squared_error
0.49355861008160823
root_mean_prior_squared_error
0.49355861008160823
root_mean_prior_squared_error
0.49355861008160823
root_mean_prior_squared_error
0.49355861008160823
root_mean_prior_squared_error
0.49355861008160823
root_mean_prior_squared_error
0.49355861008160823
root_mean_prior_squared_error
0.49355861008160823
root_mean_prior_squared_error
0.49355861008160823
root_mean_prior_squared_error
0.49355861008160823
root_mean_prior_squared_error
0.49355861008160823
root_mean_squared_error
0.6229154124848021
root_mean_squared_error
0.5261747702891967
root_mean_squared_error
0.5670675052897631
root_mean_squared_error
0.618424835996888
root_mean_squared_error
0.5957324156961001
root_mean_squared_error
0.576926434748063
root_mean_squared_error
0.5104133401252144
root_mean_squared_error
0.507499425287031
root_mean_squared_error
0.5995872191210662
root_mean_squared_error
0.560763963020291
root_relative_squared_error
1.2620900532599464
root_relative_squared_error
1.066083661679401
root_relative_squared_error
1.1489365066410258
root_relative_squared_error
1.2529916880482213
root_relative_squared_error
1.2070145338921305
root_relative_squared_error
1.168911701596433
root_relative_squared_error
1.034149399279691
root_relative_squared_error
1.0282455111118771
root_relative_squared_error
1.2148247581415437
root_relative_squared_error
1.13616488815294
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
0.5073891625615763 [0.586207,0.428571]
unweighted_recall
0.5073891625615763 [0.586207,0.428571]
unweighted_recall
0.5722495894909688 [0.62069,0.52381]
unweighted_recall
0.37766830870279144 [0.517241,0.238095]
unweighted_recall
0.4318555008210181 [0.482759,0.380952]
unweighted_recall
0.5394088669950738 [0.793103,0.285714]
unweighted_recall
0.6133004926108374 [0.655172,0.571429]
unweighted_recall
0.6264367816091954 [0.586207,0.666667]
unweighted_recall
0.4967159277504105 [0.517241,0.47619]
unweighted_recall
0.5591133004926109 [0.689655,0.428571]
usercpu_time_millis
1829.579958000977
usercpu_time_millis
1883.2098040002165
usercpu_time_millis
1888.372288998653
usercpu_time_millis
1883.760587003053
usercpu_time_millis
1817.168244997447
usercpu_time_millis
1992.1012220002012
usercpu_time_millis
1921.577254001022
usercpu_time_millis
1954.74204799757
usercpu_time_millis
1903.9989299999434
usercpu_time_millis
1910.402730001806
usercpu_time_millis_testing
29.56993599946145
usercpu_time_millis_testing
30.289545000414364
usercpu_time_millis_testing
30.69941599824233
usercpu_time_millis_testing
32.61628100153757
usercpu_time_millis_testing
31.957724997482728
usercpu_time_millis_testing
31.16911699908087
usercpu_time_millis_testing
31.253859000571538
usercpu_time_millis_testing
31.80883799723233
usercpu_time_millis_testing
60.590500997932395
usercpu_time_millis_testing
30.111012001725612
usercpu_time_millis_training
1800.0100220015156
usercpu_time_millis_training
1852.9202589998022
usercpu_time_millis_training
1857.6728730004106
usercpu_time_millis_training
1851.1443060015154
usercpu_time_millis_training
1785.2105199999642
usercpu_time_millis_training
1960.9321050011204
usercpu_time_millis_training
1890.3233950004505
usercpu_time_millis_training
1922.9332100003376
usercpu_time_millis_training
1843.408429002011
usercpu_time_millis_training
1880.2917180000804
wall_clock_time_millis
1829.5905590057373
wall_clock_time_millis
1883.209228515625
wall_clock_time_millis
1888.4055614471436
wall_clock_time_millis
1883.8117122650146
wall_clock_time_millis
1817.1684741973877
wall_clock_time_millis
1992.1021461486816
wall_clock_time_millis
1921.586513519287
wall_clock_time_millis
1954.7529220581055
wall_clock_time_millis
1904.2530059814453
wall_clock_time_millis
1910.4018211364746
wall_clock_time_millis_testing
29.573917388916016
wall_clock_time_millis_testing
30.29322624206543
wall_clock_time_millis_testing
30.70354461669922
wall_clock_time_millis_testing
32.62066841125488
wall_clock_time_millis_testing
31.961679458618164
wall_clock_time_millis_testing
31.1737060546875
wall_clock_time_millis_testing
31.25786781311035
wall_clock_time_millis_testing
31.812191009521484
wall_clock_time_millis_testing
60.60910224914551
wall_clock_time_millis_testing
30.11465072631836
wall_clock_time_millis_training
1800.0166416168213
wall_clock_time_millis_training
1852.9160022735596
wall_clock_time_millis_training
1857.7020168304443
wall_clock_time_millis_training
1851.1910438537598
wall_clock_time_millis_training
1785.2067947387695
wall_clock_time_millis_training
1960.9284400939941
wall_clock_time_millis_training
1890.3286457061768
wall_clock_time_millis_training
1922.940731048584
wall_clock_time_millis_training
1843.6439037322998
wall_clock_time_millis_training
1880.2871704101562
weighted_recall
0.52 [0.586207,0.428571]
weighted_recall
0.52 [0.586207,0.428571]
weighted_recall
0.58 [0.62069,0.52381]
weighted_recall
0.4 [0.517241,0.238095]
weighted_recall
0.44 [0.482759,0.380952]
weighted_recall
0.58 [0.793103,0.285714]
weighted_recall
0.62 [0.655172,0.571429]
weighted_recall
0.62 [0.586207,0.666667]
weighted_recall
0.5 [0.517241,0.47619]
weighted_recall
0.58 [0.689655,0.428571]