10161742
1
Jan van Rijn
14
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)
8087204
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]}}, {"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
"mae"
9667
init
null
9667
learning_rate
0.022238860929305812
9667
loss
"deviance"
9667
max_depth
11
9667
max_features
0.48246499665040055
9667
max_leaf_nodes
null
9667
min_impurity_decrease
0.0925376158119835
9667
min_impurity_split
null
9667
min_samples_leaf
2
9667
min_samples_split
18
9667
min_weight_fraction_leaf
0.05333524231344128
9667
n_estimators
134
9667
n_iter_no_change
865
9667
presort
"auto"
9667
random_state
25781
9667
subsample
0.776562418054716
9667
tol
0.0002860413784426976
9667
validation_fraction
0.9479418219452574
9667
verbose
0
9667
warm_start
false
9667
openml-python
Sklearn_0.20.3.
14
mfeat-fourier
https://www.openml.org/data/download/14/dataset_14_mfeat-fourier.arff
-1
21244400
description
https://api.openml.org/data/download/21244400/description.xml
-1
21244401
predictions
https://api.openml.org/data/download/21244401/predictions.arff
area_under_roc_curve
0.5536780555555555 [0.973515,0.636572,0.666497,0.326486,0.515249,0.141535,0.533318,0.655974,0.469314,0.618321]
average_cost
0
kappa
0.10055555555555555
kb_relative_information_score
111.33453112103577
mean_absolute_error
0.17762178821556251
mean_prior_absolute_error
0.18000000000000554
number_of_instances
2000 [200,200,200,200,200,200,200,200,200,200]
predictive_accuracy
0.1905
prior_entropy
3.321928094887362
recall
0.1905 [0.945,0.705,0,0.01,0.21,0,0,0,0,0.035]
relative_absolute_error
0.9867877123086503
root_mean_prior_squared_error
0.3000000000000046
root_mean_squared_error
0.2982288055836853
root_relative_squared_error
0.9940960186122691
total_cost
0
area_under_roc_curve
0.5636944444444445 [0.972639,0.626944,0.675,0.375278,0.498333,0.031111,0.503889,0.675,0.675,0.60375]
area_under_roc_curve
0.5615833333333333 [0.972639,0.564583,0.655556,0.386944,0.459861,0.172222,0.514861,0.655556,0.610278,0.623333]
area_under_roc_curve
0.5634444444444445 [0.977917,0.56,0.738889,0.335,0.523472,0.076528,0.453194,0.673472,0.692222,0.60375]
area_under_roc_curve
0.5561944444444444 [0.997083,0.663333,0.7425,0.273611,0.466528,0.082361,0.53125,0.780556,0.425556,0.599167]
area_under_roc_curve
0.5587222222222223 [0.995556,0.619861,0.737639,0.337083,0.482361,0.095833,0.524444,0.737639,0.444722,0.612083]
area_under_roc_curve
0.5578611111111111 [0.979306,0.682778,0.758333,0.255972,0.542083,0.150417,0.481944,0.739444,0.386944,0.601389]
area_under_roc_curve
0.55475 [0.911806,0.6825,0.722222,0.239028,0.535833,0.191806,0.54625,0.722222,0.402778,0.593056]
area_under_roc_curve
0.5775277777777778 [0.98875,0.604028,0.694444,0.295556,0.576667,0.204722,0.596806,0.694444,0.493889,0.625972]
area_under_roc_curve
0.5411944444444444 [0.964722,0.628472,0.708333,0.313194,0.491667,0.224028,0.630556,0.4225,0.375833,0.652639]
area_under_roc_curve
0.5589722222222222 [0.996667,0.573889,0.381528,0.423056,0.610278,0.220278,0.701667,0.448194,0.511667,0.7225]
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
0.09444444444444443
kappa
0.08333333333333331
kappa
0.10555555555555556
kappa
0.11666666666666664
kappa
0.10555555555555556
kappa
0.11666666666666664
kappa
0.10555555555555556
kappa
0.11111111111111112
kappa
0.07777777777777778
kappa
0.08888888888888888
kb_relative_information_score
11.2389433452339
kb_relative_information_score
11.606245497593129
kb_relative_information_score
11.762377086018317
kb_relative_information_score
11.449677533941506
kb_relative_information_score
10.617507755741743
kb_relative_information_score
10.951952804718251
kb_relative_information_score
10.35493142477356
kb_relative_information_score
11.846244660487264
kb_relative_information_score
10.134484139204918
kb_relative_information_score
11.37216687332251
mean_absolute_error
0.17807889228996587
mean_absolute_error
0.17778229495432982
mean_absolute_error
0.17749030526996223
mean_absolute_error
0.17761740393892997
mean_absolute_error
0.17780100267493748
mean_absolute_error
0.17750629129053308
mean_absolute_error
0.1778054613965132
mean_absolute_error
0.17697419471910827
mean_absolute_error
0.17786275821702674
mean_absolute_error
0.1772992774043227
mean_prior_absolute_error
0.1799999999999998
mean_prior_absolute_error
0.1799999999999998
mean_prior_absolute_error
0.1799999999999998
mean_prior_absolute_error
0.1799999999999998
mean_prior_absolute_error
0.1799999999999998
mean_prior_absolute_error
0.1799999999999998
mean_prior_absolute_error
0.1799999999999998
mean_prior_absolute_error
0.1799999999999998
mean_prior_absolute_error
0.1799999999999998
mean_prior_absolute_error
0.1799999999999998
number_of_instances
200 [20,20,20,20,20,20,20,20,20,20]
number_of_instances
200 [20,20,20,20,20,20,20,20,20,20]
number_of_instances
200 [20,20,20,20,20,20,20,20,20,20]
number_of_instances
200 [20,20,20,20,20,20,20,20,20,20]
number_of_instances
200 [20,20,20,20,20,20,20,20,20,20]
number_of_instances
200 [20,20,20,20,20,20,20,20,20,20]
number_of_instances
200 [20,20,20,20,20,20,20,20,20,20]
number_of_instances
200 [20,20,20,20,20,20,20,20,20,20]
number_of_instances
200 [20,20,20,20,20,20,20,20,20,20]
number_of_instances
200 [20,20,20,20,20,20,20,20,20,20]
predictive_accuracy
0.185
predictive_accuracy
0.175
predictive_accuracy
0.195
predictive_accuracy
0.205
predictive_accuracy
0.195
predictive_accuracy
0.205
predictive_accuracy
0.195
predictive_accuracy
0.2
predictive_accuracy
0.17
predictive_accuracy
0.18
prior_entropy
3.321928094887362
prior_entropy
3.321928094887362
prior_entropy
3.321928094887362
prior_entropy
3.321928094887362
prior_entropy
3.321928094887362
prior_entropy
3.321928094887362
prior_entropy
3.321928094887362
prior_entropy
3.321928094887362
prior_entropy
3.321928094887362
prior_entropy
3.321928094887362
recall
0.185 [0.9,0,0,0,0.95,0,0,0,0,0]
recall
0.175 [0.95,0,0,0,0.8,0,0,0,0,0]
recall
0.195 [0.95,0.95,0,0,0.05,0,0,0,0,0]
recall
0.205 [0.95,0.95,0,0,0.05,0,0,0,0,0.1]
recall
0.195 [0.95,0.9,0,0,0.05,0,0,0,0,0.05]
recall
0.205 [0.95,1,0,0,0.05,0,0,0,0,0.05]
recall
0.195 [0.9,0.95,0,0,0,0,0,0,0,0.1]
recall
0.2 [1,0.85,0,0,0.1,0,0,0,0,0.05]
recall
0.17 [0.9,0.8,0,0,0,0,0,0,0,0]
recall
0.18 [1,0.65,0,0.1,0.05,0,0,0,0,0]
relative_absolute_error
0.9893271793887004
relative_absolute_error
0.9876794164129445
relative_absolute_error
0.9860572514997912
relative_absolute_error
0.9867633552162787
relative_absolute_error
0.9877833481940982
relative_absolute_error
0.9861460627251849
relative_absolute_error
0.9878081188695189
relative_absolute_error
0.9831899706617138
relative_absolute_error
0.9881264345390386
relative_absolute_error
0.9849959855795717
root_mean_prior_squared_error
0.2999999999999998
root_mean_prior_squared_error
0.2999999999999998
root_mean_prior_squared_error
0.2999999999999998
root_mean_prior_squared_error
0.2999999999999998
root_mean_prior_squared_error
0.2999999999999998
root_mean_prior_squared_error
0.2999999999999998
root_mean_prior_squared_error
0.2999999999999998
root_mean_prior_squared_error
0.2999999999999998
root_mean_prior_squared_error
0.2999999999999998
root_mean_prior_squared_error
0.2999999999999998
root_mean_squared_error
0.2990431873106697
root_mean_squared_error
0.2989294348219163
root_mean_squared_error
0.2978334806952036
root_mean_squared_error
0.29826956797765425
root_mean_squared_error
0.29919889532375704
root_mean_squared_error
0.2980085823617941
root_mean_squared_error
0.2983128506001785
root_mean_squared_error
0.29684889290903393
root_mean_squared_error
0.2983064553048073
root_mean_squared_error
0.2975288138297881
root_relative_squared_error
0.9968106243688996
root_relative_squared_error
0.9964314494063882
root_relative_squared_error
0.9927782689840126
root_relative_squared_error
0.9942318932588481
root_relative_squared_error
0.9973296510791907
root_relative_squared_error
0.993361941205981
root_relative_squared_error
0.9943761686672622
root_relative_squared_error
0.9894963096967803
root_relative_squared_error
0.9943548510160249
root_relative_squared_error
0.9917627127659608
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
2201.7754839999993
usercpu_time_millis
2149.694448
usercpu_time_millis
2180.873972999998
usercpu_time_millis
2203.129064
usercpu_time_millis
2256.134386999999
usercpu_time_millis
2224.4490450000003
usercpu_time_millis
2215.5637750000033
usercpu_time_millis
2168.7190250000017
usercpu_time_millis
2250.569648999999
usercpu_time_millis
2261.0007220000025
usercpu_time_millis_testing
3.812964999999835
usercpu_time_millis_testing
2.1152009999996224
usercpu_time_millis_testing
3.3699399999989055
usercpu_time_millis_testing
2.2029050000007544
usercpu_time_millis_testing
3.9282529999997706
usercpu_time_millis_testing
2.22976200000069
usercpu_time_millis_testing
2.5055360000010296
usercpu_time_millis_testing
2.2102090000011287
usercpu_time_millis_testing
3.6847120000018663
usercpu_time_millis_testing
2.19179800000191
usercpu_time_millis_training
2197.9625189999997
usercpu_time_millis_training
2147.5792470000006
usercpu_time_millis_training
2177.5040329999993
usercpu_time_millis_training
2200.9261589999996
usercpu_time_millis_training
2252.2061339999996
usercpu_time_millis_training
2222.2192829999995
usercpu_time_millis_training
2213.0582390000022
usercpu_time_millis_training
2166.5088160000005
usercpu_time_millis_training
2246.884936999997
usercpu_time_millis_training
2258.8089240000004