10226858
1
Jan van Rijn
9986
Supervised Classification
9666
sklearn.pipeline.Pipeline(columntransformer=sklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,standardscaler=sklearn.preprocessing.data.StandardScaler),nominal=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)),variancethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,gradientboostingclassifier=sklearn.ensemble.gradient_boosting.GradientBoostingClassifier)(4)
8152290
copy
true
9559
fill_value
-1
9559
missing_values
NaN
9559
strategy
"constant"
9559
verbose
0
9559
n_jobs
null
9606
remainder
"passthrough"
9606
sparse_threshold
0.3
9606
transformer_weights
null
9606
transformers
[{"oml-python:serialized_object": "component_reference", "value": {"key": "numeric", "step_name": "numeric", "argument_1": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127]}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "nominal", "step_name": "nominal", "argument_1": []}}]
9606
memory
null
9607
steps
[{"oml-python:serialized_object": "component_reference", "value": {"key": "imputer", "step_name": "imputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "standardscaler", "step_name": "standardscaler"}}]
9607
axis
0
9608
copy
true
9608
missing_values
"NaN"
9608
strategy
"mean"
9608
verbose
0
9608
copy
true
9609
with_mean
true
9609
with_std
true
9609
memory
null
9610
steps
[{"oml-python:serialized_object": "component_reference", "value": {"key": "simpleimputer", "step_name": "simpleimputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "onehotencoder", "step_name": "onehotencoder"}}]
9610
categorical_features
null
9611
categories
null
9611
dtype
{"oml-python:serialized_object": "type", "value": "np.float64"}
9611
handle_unknown
"ignore"
9611
n_values
null
9611
sparse
true
9611
threshold
0.0
9612
memory
null
9666
steps
[{"oml-python:serialized_object": "component_reference", "value": {"key": "columntransformer", "step_name": "columntransformer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "variancethreshold", "step_name": "variancethreshold"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "gradientboostingclassifier", "step_name": "gradientboostingclassifier"}}]
9666
criterion
"friedman_mse"
9667
init
null
9667
learning_rate
5.7628210394723986e-05
9667
loss
"deviance"
9667
max_depth
29
9667
max_features
0.5691122441394714
9667
max_leaf_nodes
null
9667
min_impurity_decrease
0.1832354334864591
9667
min_impurity_split
null
9667
min_samples_leaf
9
9667
min_samples_split
3
9667
min_weight_fraction_leaf
0.37541685461536806
9667
n_estimators
323
9667
n_iter_no_change
605
9667
presort
"auto"
9667
random_state
7259
9667
subsample
0.32784182464756917
9667
tol
3.1731579887429746e-05
9667
validation_fraction
0.807586311029996
9667
verbose
0
9667
warm_start
false
9667
openml-python
Sklearn_0.20.3.
1476
gas-drift
https://www.openml.org/data/download/1588715/phpbL6t4U
-1
21374632
description
https://api.openml.org/data/download/21374632/description.xml
-1
21374633
predictions
https://api.openml.org/data/download/21374633/predictions.arff
area_under_roc_curve
0.8763009589506103 [0.883857,0.89108,0.867193,0.808136,0.90611,0.873352]
average_cost
0
kappa
0.282988637025062
kb_relative_information_score
522.2754663881271
mean_absolute_error
0.27607029286371754
mean_prior_absolute_error
0.27476832857057837
number_of_instances
13910 [2565,2926,1641,1936,3009,1833]
predictive_accuracy
0.4351545650611071
prior_entropy
2.5457299651568843
recall
0.4351545650611071 [0.196881,0.936774,0,0,0.932868,0]
relative_absolute_error
1.0047384074427805
root_mean_prior_squared_error
0.37065282342196226
root_mean_squared_error
0.3704644434968128
root_relative_squared_error
0.9994917617963617
total_cost
0
area_under_roc_curve
0.8872628880697472 [0.897958,0.895493,0.871186,0.827878,0.920865,0.880914]
area_under_roc_curve
0.8803581606646588 [0.87789,0.909465,0.851387,0.832793,0.911319,0.862681]
area_under_roc_curve
0.876584060943149 [0.889328,0.904152,0.85629,0.76083,0.916787,0.888774]
area_under_roc_curve
0.8761020649853125 [0.882095,0.884579,0.872657,0.811917,0.907184,0.87377]
area_under_roc_curve
0.8789089181362778 [0.907224,0.902747,0.854078,0.791272,0.895975,0.888218]
area_under_roc_curve
0.8699245034580443 [0.868072,0.86663,0.882082,0.81799,0.908144,0.859088]
area_under_roc_curve
0.8833689457038255 [0.895731,0.890218,0.869931,0.845152,0.899758,0.880711]
area_under_roc_curve
0.8774297193897133 [0.873838,0.885938,0.872441,0.81293,0.915153,0.879632]
area_under_roc_curve
0.8738329234960276 [0.886523,0.886422,0.884459,0.805872,0.895052,0.863546]
area_under_roc_curve
0.8706793698206334 [0.881898,0.901307,0.856515,0.775719,0.903153,0.866258]
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
kappa
0.30885657425882757
kappa
0.28824693628938247
kappa
0.2967519578547302
kappa
0.27779484372189867
kappa
0.27794982245383176
kappa
0.2640970083958157
kappa
0.2732726346685989
kappa
0.2788456174821646
kappa
0.2695128619695713
kappa
0.2944555631136293
kb_relative_information_score
52.37565464314052
kb_relative_information_score
52.19909427836919
kb_relative_information_score
52.10758522114225
kb_relative_information_score
52.13235284803874
kb_relative_information_score
52.19298972972798
kb_relative_information_score
52.16769804980917
kb_relative_information_score
52.38000772975729
kb_relative_information_score
52.28472542362233
kb_relative_information_score
52.168416112073594
kb_relative_information_score
52.26694235244188
mean_absolute_error
0.27603914033809523
mean_absolute_error
0.27607173788397965
mean_absolute_error
0.2760662301051522
mean_absolute_error
0.2760756169104842
mean_absolute_error
0.27606767846036234
mean_absolute_error
0.2760929985955715
mean_absolute_error
0.27605220352217524
mean_absolute_error
0.2760641488396676
mean_absolute_error
0.2760828127588108
mean_absolute_error
0.27609036122287706
mean_prior_absolute_error
0.27477202746106094
mean_prior_absolute_error
0.27477202746106094
mean_prior_absolute_error
0.27477202746106094
mean_prior_absolute_error
0.2747532058256237
mean_prior_absolute_error
0.27476403730658433
mean_prior_absolute_error
0.27476403730658433
mean_prior_absolute_error
0.27476403730658433
mean_prior_absolute_error
0.27476403730658433
mean_prior_absolute_error
0.27476403730658433
mean_prior_absolute_error
0.2747938109641058
number_of_instances
1391 [257,292,164,193,301,184]
number_of_instances
1391 [257,292,164,193,301,184]
number_of_instances
1391 [257,292,164,193,301,184]
number_of_instances
1391 [257,293,164,193,301,183]
number_of_instances
1391 [256,293,164,194,301,183]
number_of_instances
1391 [256,293,164,194,301,183]
number_of_instances
1391 [256,293,164,194,301,183]
number_of_instances
1391 [256,293,164,194,301,183]
number_of_instances
1391 [256,293,164,194,301,183]
number_of_instances
1391 [257,292,165,194,300,183]
predictive_accuracy
0.45506829618979155
predictive_accuracy
0.4392523364485982
predictive_accuracy
0.44572250179726813
predictive_accuracy
0.43134435657800146
predictive_accuracy
0.43134435657800146
predictive_accuracy
0.4205607476635514
predictive_accuracy
0.4277498202731847
predictive_accuracy
0.43206326383896476
predictive_accuracy
0.4248741912293314
predictive_accuracy
0.4435657800143782
prior_entropy
2.5457299651568843
prior_entropy
2.5457299651568843
prior_entropy
2.5457299651568843
prior_entropy
2.5457299651568843
prior_entropy
2.5457299651568843
prior_entropy
2.5457299651568843
prior_entropy
2.5457299651568843
prior_entropy
2.5457299651568843
prior_entropy
2.5457299651568843
prior_entropy
2.5457299651568843
recall
0.4550682961897915 [0.287938,0.94863,0,0,0.936877,0]
recall
0.4392523364485981 [0.18677,0.955479,0,0,0.943522,0]
recall
0.44572250179726813 [0.241245,0.945205,0,0,0.936877,0]
recall
0.43134435657800146 [0.171206,0.921502,0,0,0.950166,0]
recall
0.43134435657800146 [0.195312,0.938567,0,0,0.913621,0]
recall
0.4205607476635514 [0.152344,0.897611,0,0,0.940199,0]
recall
0.42774982027318476 [0.164062,0.94198,0,0,0.920266,0]
recall
0.43206326383896476 [0.183594,0.928328,0,0,0.936877,0]
recall
0.4248741912293314 [0.144531,0.945392,0,0,0.920266,0]
recall
0.44356578001437813 [0.241245,0.945205,0,0,0.93,0]
relative_absolute_error
1.0046115060864915
relative_absolute_error
1.0047301409642322
relative_absolute_error
1.004710096060541
relative_absolute_error
1.0048130870061616
relative_absolute_error
1.0047445843588454
relative_absolute_error
1.0048367366487059
relative_absolute_error
1.0046882635304764
relative_absolute_error
1.0047317383520342
relative_absolute_error
1.0047996654334896
relative_absolute_error
1.0047182658671325
root_mean_prior_squared_error
0.3706578130852553
root_mean_prior_squared_error
0.3706578130852553
root_mean_prior_squared_error
0.3706578130852553
root_mean_prior_squared_error
0.37063242271245894
root_mean_prior_squared_error
0.37064703458501796
root_mean_prior_squared_error
0.37064703458501796
root_mean_prior_squared_error
0.37064703458501796
root_mean_prior_squared_error
0.37064703458501796
root_mean_prior_squared_error
0.37064703458501796
root_mean_prior_squared_error
0.37068719684417073
root_mean_squared_error
0.37042264130035396
root_mean_squared_error
0.37046637821856293
root_mean_squared_error
0.3704586042639538
root_mean_squared_error
0.37047120297742225
root_mean_squared_error
0.37046100773398055
root_mean_squared_error
0.370494708278399
root_mean_squared_error
0.3704408584217003
root_mean_squared_error
0.3704565425331339
root_mean_squared_error
0.37048136956401473
root_mean_squared_error
0.37049111577147226
root_relative_squared_error
0.999365528591064
root_relative_squared_error
0.9994835266924528
root_relative_squared_error
0.9994625532923659
root_relative_squared_error
0.9995650144856275
root_relative_squared_error
0.999498102416371
root_relative_squared_error
0.9995890259670105
root_relative_squared_error
0.9994437398816681
root_relative_squared_error
0.9994860553731469
root_relative_squared_error
0.9995530383207065
root_relative_squared_error
0.9994710335982256
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
7734.094729996286
usercpu_time_millis
7716.803719995369
usercpu_time_millis
7682.285893999506
usercpu_time_millis
7721.636617992772
usercpu_time_millis
7717.86762499687
usercpu_time_millis
7721.693897001387
usercpu_time_millis
7678.692271991167
usercpu_time_millis
7675.516809002147
usercpu_time_millis
7737.328156996227
usercpu_time_millis
7739.247351993981
usercpu_time_millis_testing
26.14527099649422
usercpu_time_millis_testing
26.754456994240172
usercpu_time_millis_testing
26.59539099840913
usercpu_time_millis_testing
26.75098699546652
usercpu_time_millis_testing
26.466205999895465
usercpu_time_millis_testing
26.75899500172818
usercpu_time_millis_testing
26.607016996422317
usercpu_time_millis_testing
27.233681998040993
usercpu_time_millis_testing
26.706669996201526
usercpu_time_millis_testing
26.908690997515805
usercpu_time_millis_training
7707.949458999792
usercpu_time_millis_training
7690.049263001129
usercpu_time_millis_training
7655.690503001097
usercpu_time_millis_training
7694.885630997305
usercpu_time_millis_training
7691.401418996975
usercpu_time_millis_training
7694.934901999659
usercpu_time_millis_training
7652.085254994745
usercpu_time_millis_training
7648.283127004106
usercpu_time_millis_training
7710.621487000026
usercpu_time_millis_training
7712.3386609964655