10101475
1
Jan van Rijn
9976
Supervised Classification
8815
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,decisiontreeclassifier=sklearn.tree.tree.DecisionTreeClassifier)(1)
8026659
axis
0
8778
copy
true
8778
missing_values
"NaN"
8778
strategy
"most_frequent"
8778
verbose
0
8778
copy
true
8779
with_mean
true
8779
with_std
true
8779
memory
null
8780
copy
true
8781
fill_value
-1
8781
missing_values
NaN
8781
strategy
"constant"
8781
verbose
0
8781
categorical_features
null
8782
categories
null
8782
dtype
{"oml-python:serialized_object": "type", "value": "np.float64"}
8782
handle_unknown
"ignore"
8782
n_values
null
8782
sparse
true
8782
class_weight
null
8783
criterion
"gini"
8783
max_depth
null
8783
max_features
1.0
8783
max_leaf_nodes
null
8783
min_impurity_decrease
0.0
8783
min_impurity_split
null
8783
min_samples_leaf
9
8783
min_samples_split
17
8783
min_weight_fraction_leaf
0.0
8783
presort
false
8783
random_state
6798
8783
splitter
"best"
8783
n_jobs
null
8812
remainder
"passthrough"
8812
sparse_threshold
0.3
8812
transformer_weights
null
8812
memory
null
8813
memory
null
8815
threshold
0.0
8816
openml-python
Sklearn_0.20.0.
1485
madelon
https://www.openml.org/data/download/1590986/phpfLuQE4
-1
21123488
description
https://api.openml.org/data/download/21123488/description.xml
-1
21123489
predictions
https://api.openml.org/data/download/21123489/predictions.arff
area_under_roc_curve
0.8358772189349113 [0.835877,0.835877]
average_cost
0
f_measure
0.777307395823456 [0.777564,0.77705]
kappa
0.5546153846153845
kb_relative_information_score
1393.891058462065
mean_absolute_error
0.23433658793443826
mean_prior_absolute_error
0.5
number_of_instances
2600 [1300,1300]
precision
0.777309169102084 [0.776669,0.777949]
predictive_accuracy
0.7773076923076923
prior_entropy
1
recall
0.7773076923076923 [0.778462,0.776154]
relative_absolute_error
0.4686731758688765
root_mean_prior_squared_error
0.5
root_mean_squared_error
0.4186506280236463
root_relative_squared_error
0.8373012560472926
total_cost
0
area_under_roc_curve
0.8528994082840237 [0.852899,0.852899]
area_under_roc_curve
0.8413313609467455 [0.841331,0.841331]
area_under_roc_curve
0.8218639053254437 [0.821864,0.821864]
area_under_roc_curve
0.8806804733727811 [0.88068,0.88068]
area_under_roc_curve
0.8789644970414201 [0.878964,0.878964]
area_under_roc_curve
0.8290532544378698 [0.829053,0.829053]
area_under_roc_curve
0.8222485207100592 [0.822249,0.822249]
area_under_roc_curve
0.7714497041420119 [0.77145,0.77145]
area_under_roc_curve
0.8172781065088758 [0.817278,0.817278]
area_under_roc_curve
0.8435502958579881 [0.84355,0.84355]
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
0.7960059806664594 [0.801498,0.790514]
f_measure
0.7768702651515151 [0.773438,0.780303]
f_measure
0.7880822181715793 [0.779116,0.797048]
f_measure
0.8036108354685348 [0.796813,0.810409]
f_measure
0.8307291666666669 [0.833333,0.828125]
f_measure
0.7884333713068308 [0.790875,0.785992]
f_measure
0.7576026637069921 [0.752941,0.762264]
f_measure
0.7076750103556423 [0.709924,0.705426]
f_measure
0.7456119544592031 [0.757353,0.733871]
f_measure
0.7768702651515151 [0.780303,0.773438]
kappa
0.5923076923076922
kappa
0.5538461538461539
kappa
0.5769230769230769
kappa
0.6076923076923078
kappa
0.6615384615384616
kappa
0.5769230769230769
kappa
0.5153846153846153
kappa
0.41538461538461546
kappa
0.49230769230769234
kappa
0.5538461538461539
kb_relative_information_score
145.1896086893156
kb_relative_information_score
141.56789803376122
kb_relative_information_score
135.8429260681678
kb_relative_information_score
157.52634797787357
kb_relative_information_score
162.50871286319733
kb_relative_information_score
141.3462812446326
kb_relative_information_score
134.3419508257261
kb_relative_information_score
107.86583829908768
kb_relative_information_score
126.69795919819336
kb_relative_information_score
141.00353526211146
mean_absolute_error
0.22443843549612788
mean_absolute_error
0.22901178603950093
mean_absolute_error
0.24229255535816624
mean_absolute_error
0.19891519491067006
mean_absolute_error
0.19249952033888693
mean_absolute_error
0.23146006582658177
mean_absolute_error
0.24251299982069224
mean_absolute_error
0.29283897537856807
mean_absolute_error
0.25893854542893
mean_absolute_error
0.23045780074626238
mean_prior_absolute_error
0.5
mean_prior_absolute_error
0.5
mean_prior_absolute_error
0.5
mean_prior_absolute_error
0.5
mean_prior_absolute_error
0.5
mean_prior_absolute_error
0.5
mean_prior_absolute_error
0.5
mean_prior_absolute_error
0.5
mean_prior_absolute_error
0.5
mean_prior_absolute_error
0.5
number_of_instances
260 [130,130]
number_of_instances
260 [130,130]
number_of_instances
260 [130,130]
number_of_instances
260 [130,130]
number_of_instances
260 [130,130]
number_of_instances
260 [130,130]
number_of_instances
260 [130,130]
number_of_instances
260 [130,130]
number_of_instances
260 [130,130]
number_of_instances
260 [130,130]
precision
0.7970150139457599 [0.781022,0.813008]
precision
0.777185501066098 [0.785714,0.768657]
precision
0.7905417486143395 [0.815126,0.765957]
precision
0.8053094714311196 [0.826446,0.784173]
precision
0.8310826818289504 [0.820896,0.84127]
precision
0.7886152388846132 [0.781955,0.795276]
precision
0.7580740740740741 [0.768,0.748148]
precision
0.7077414772727273 [0.704545,0.710938]
precision
0.7482692766770113 [0.725352,0.771186]
precision
0.777185501066098 [0.768657,0.785714]
predictive_accuracy
0.7961538461538461
predictive_accuracy
0.7769230769230769
predictive_accuracy
0.7884615384615384
predictive_accuracy
0.8038461538461539
predictive_accuracy
0.8307692307692308
predictive_accuracy
0.7884615384615384
predictive_accuracy
0.7576923076923078
predictive_accuracy
0.7076923076923077
predictive_accuracy
0.7461538461538462
predictive_accuracy
0.7769230769230769
prior_entropy
1
prior_entropy
1
prior_entropy
1
prior_entropy
1
prior_entropy
1
prior_entropy
1
prior_entropy
1
prior_entropy
1
prior_entropy
1
prior_entropy
1
recall
0.7961538461538461 [0.823077,0.769231]
recall
0.7769230769230769 [0.761538,0.792308]
recall
0.7884615384615384 [0.746154,0.830769]
recall
0.8038461538461539 [0.769231,0.838462]
recall
0.8307692307692308 [0.846154,0.815385]
recall
0.7884615384615384 [0.8,0.776923]
recall
0.7576923076923077 [0.738462,0.776923]
recall
0.7076923076923077 [0.715385,0.7]
recall
0.7461538461538462 [0.792308,0.7]
recall
0.7769230769230769 [0.792308,0.761538]
relative_absolute_error
0.4488768709922557
relative_absolute_error
0.45802357207900185
relative_absolute_error
0.4845851107163325
relative_absolute_error
0.3978303898213401
relative_absolute_error
0.38499904067777385
relative_absolute_error
0.46292013165316354
relative_absolute_error
0.4850259996413845
relative_absolute_error
0.5856779507571361
relative_absolute_error
0.51787709085786
relative_absolute_error
0.46091560149252475
root_mean_prior_squared_error
0.5
root_mean_prior_squared_error
0.5
root_mean_prior_squared_error
0.5
root_mean_prior_squared_error
0.5
root_mean_prior_squared_error
0.5
root_mean_prior_squared_error
0.5
root_mean_prior_squared_error
0.5
root_mean_prior_squared_error
0.5
root_mean_prior_squared_error
0.5
root_mean_prior_squared_error
0.5
root_mean_squared_error
0.4013305885671066
root_mean_squared_error
0.4158292156341199
root_mean_squared_error
0.43145933083099647
root_mean_squared_error
0.37736694586244607
root_mean_squared_error
0.367901873095585
root_mean_squared_error
0.41769427412233723
root_mean_squared_error
0.4343888271594606
root_mean_squared_error
0.48367126242035946
root_mean_squared_error
0.4320626451921398
root_mean_squared_error
0.4135340035308004
root_relative_squared_error
0.8026611771342133
root_relative_squared_error
0.8316584312682397
root_relative_squared_error
0.8629186616619929
root_relative_squared_error
0.7547338917248922
root_relative_squared_error
0.73580374619117
root_relative_squared_error
0.8353885482446745
root_relative_squared_error
0.8687776543189212
root_relative_squared_error
0.9673425248407189
root_relative_squared_error
0.8641252903842797
root_relative_squared_error
0.8270680070616008
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
1762.4238050002532
usercpu_time_millis
1599.3167579990768
usercpu_time_millis
1589.7242350001761
usercpu_time_millis
1559.893620999901
usercpu_time_millis
1557.702438000888
usercpu_time_millis
1578.210575000412
usercpu_time_millis
1577.0733720000862
usercpu_time_millis
1595.9211820008932
usercpu_time_millis
1595.9299169999213
usercpu_time_millis
1613.4653529998104
usercpu_time_millis_testing
4.452510000191978
usercpu_time_millis_testing
4.363119999652554
usercpu_time_millis_testing
4.437116000190144
usercpu_time_millis_testing
4.407377999996243
usercpu_time_millis_testing
4.33459300074901
usercpu_time_millis_testing
4.401669000799302
usercpu_time_millis_testing
4.35135000043374
usercpu_time_millis_testing
4.35030500011635
usercpu_time_millis_testing
4.919713999697706
usercpu_time_millis_testing
4.349821999312553
usercpu_time_millis_training
1757.9712950000612
usercpu_time_millis_training
1594.9536379994242
usercpu_time_millis_training
1585.287118999986
usercpu_time_millis_training
1555.4862429999048
usercpu_time_millis_training
1553.367845000139
usercpu_time_millis_training
1573.8089059996128
usercpu_time_millis_training
1572.7220219996525
usercpu_time_millis_training
1591.5708770007768
usercpu_time_millis_training
1591.0102030002236
usercpu_time_millis_training
1609.1155310004979