8905493
1935
Hilde Weerts
14
Supervised Classification
8317
sklearn.pipeline.Pipeline(imputation=hyperimp.utils.preprocessing.ConditionalImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,scaling=sklearn.preprocessing.data.StandardScaler,variencethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,clf=sklearn.svm.classes.SVC)(1)
6843084
categorical_features
[]
7644
dtype
{"oml-python:serialized_object": "type", "value": "np.float64"}
7644
handle_unknown
"ignore"
7644
n_values
"auto"
7644
sparse
true
7644
threshold
0.0
7645
copy
true
7646
with_mean
false
7646
with_std
true
7646
C
520.2374310079729
7650
cache_size
200
7650
class_weight
null
7650
coef0
0.7011513197244875
7650
decision_function_shape
"ovr"
7650
degree
3
7650
gamma
0.1922057971237275
7650
kernel
"rbf"
7650
max_iter
-1
7650
probability
false
7650
random_state
1
7650
shrinking
true
7650
tol
0.006376836455014594
7650
verbose
false
7650
axis
0
8316
categorical_features
[]
8316
copy
true
8316
fill_empty
0
8316
missing_values
"NaN"
8316
strategy
"mean"
8316
strategy_nominal
"most_frequent"
8316
verbose
0
8316
memory
null
8317
openml-python
Sklearn_0.19.1.
study_98
14
mfeat-fourier
https://www.openml.org/data/download/14/dataset_14_mfeat-fourier.arff
-1
18726730
description
https://api.openml.org/data/download/18726730/description.xml
-1
18726731
predictions
https://api.openml.org/data/download/18726731/predictions.arff
area_under_roc_curve
0.6688888888888889 [0.835,0.638611,0.77,0.575556,0.673056,0.545,0.577778,0.729444,0.765,0.579444]
average_cost
0
f_measure
0.44225353100922815 [0.802395,0.429119,0.701299,0.229508,0.268391,0.165138,0.259259,0.611842,0.69281,0.262774]
kappa
0.33777777777777784
kb_relative_information_score
753.4570712516663
mean_absolute_error
0.1191999999999975
mean_prior_absolute_error
0.18000000000000554
number_of_instances
2000 [200,200,200,200,200,200,200,200,200,200]
precision
0.7153271632659289 [1,0.918033,1,0.194444,0.160077,1,0.5,0.894231,1,0.486486]
predictive_accuracy
0.40399999999999997
prior_entropy
3.321928094887362
recall
0.404 [0.67,0.28,0.54,0.28,0.83,0.09,0.175,0.465,0.53,0.18]
relative_absolute_error
0.6622222222221879
root_mean_prior_squared_error
0.3000000000000046
root_mean_squared_error
0.34525353003263776
root_relative_squared_error
1.1508451001087747
total_cost
0
area_under_roc_curve
0.6666666666666665 [0.825,0.694444,0.75,0.575,0.688889,0.575,0.616667,0.7,0.675,0.566667]
area_under_roc_curve
0.7027777777777777 [0.825,0.647222,0.825,0.547222,0.744444,0.55,0.627778,0.797222,0.85,0.613889]
area_under_roc_curve
0.6805555555555556 [0.775,0.747222,0.725,0.525,0.702778,0.525,0.619444,0.722222,0.875,0.588889]
area_under_roc_curve
0.675 [0.825,0.55,0.75,0.55,0.691667,0.65,0.619444,0.697222,0.8,0.616667]
area_under_roc_curve
0.65 [0.825,0.675,0.725,0.680556,0.622222,0.575,0.516667,0.666667,0.7,0.513889]
area_under_roc_curve
0.6638888888888889 [0.875,0.65,0.8,0.525,0.680556,0.525,0.538889,0.775,0.75,0.519444]
area_under_roc_curve
0.6833333333333332 [0.875,0.675,0.825,0.575,0.711111,0.5,0.538889,0.716667,0.8,0.616667]
area_under_roc_curve
0.6638888888888889 [0.825,0.65,0.75,0.547222,0.641667,0.5,0.663889,0.819444,0.625,0.616667]
area_under_roc_curve
0.6555555555555556 [0.825,0.575,0.775,0.680556,0.566667,0.5,0.519444,0.675,0.85,0.588889]
area_under_roc_curve
0.6472222222222223 [0.875,0.522222,0.775,0.55,0.680556,0.55,0.516667,0.725,0.725,0.552778]
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
0.4450634990909591 [0.787879,0.533333,0.666667,0.26087,0.263158,0.26087,0.357143,0.571429,0.518519,0.230769]
f_measure
0.49275344502436846 [0.787879,0.444444,0.787879,0.173913,0.30303,0.181818,0.352941,0.727273,0.823529,0.344828]
f_measure
0.45513409120909515 [0.709677,0.645161,0.62069,0.095238,0.272109,0.095238,0.37037,0.6,0.857143,0.285714]
f_measure
0.4573858307416198 [0.787879,0.181818,0.666667,0.181818,0.264901,0.461538,0.37037,0.551724,0.75,0.357143]
f_measure
0.40320649989601004 [0.787879,0.518519,0.62069,0.258065,0.384615,0.26087,0.083333,0.466667,0.571429,0.08]
f_measure
0.41343687868933315 [0.857143,0.461538,0.75,0.095238,0.258065,0.095238,0.153846,0.709677,0.666667,0.086957]
f_measure
0.3797691277947118 [0.857143,0.090909,0.709677,0.181818,0.258065,0.181818,0.083333,0.62069,0.62069,0.193548]
kappa
0.33333333333333337
kappa
0.40555555555555556
kappa
0.36111111111111105
kappa
0.3499999999999999
kappa
0.3
kappa
0.32777777777777783
kappa
0.36666666666666664
kappa
0.32777777777777783
kappa
0.3111111111111111
kappa
0.29444444444444445
kb_relative_information_score
74.50910113271917
kb_relative_information_score
88.10394851000795
kb_relative_information_score
79.73788858552254
kb_relative_information_score
77.64637360440119
kb_relative_information_score
68.23455618935512
kb_relative_information_score
73.46334364215849
kb_relative_information_score
80.78364607608322
kb_relative_information_score
73.46334364215849
kb_relative_information_score
70.32607117047645
kb_relative_information_score
67.18879869879441
mean_absolute_error
0.11999999999999973
mean_absolute_error
0.10699999999999978
mean_absolute_error
0.11499999999999976
mean_absolute_error
0.11699999999999974
mean_absolute_error
0.12599999999999972
mean_absolute_error
0.12099999999999973
mean_absolute_error
0.11399999999999975
mean_absolute_error
0.12099999999999973
mean_absolute_error
0.12399999999999972
mean_absolute_error
0.1269999999999997
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]
precision
0.8076515151515151 [1,0.8,1,1,0.151515,1,0.625,1,1,0.5]
precision
0.7609584859584859 [1,0.857143,1,0.666667,0.178571,1,0.428571,0.923077,1,0.555556]
precision
0.8180856938337254 [1,0.909091,1,1,0.15748,1,0.714286,0.9,1,0.5]
precision
0.8380846358899794 [1,1,1,1,0.152672,1,0.714286,0.888889,1,0.625]
precision
0.7131481481481481 [1,1,1,0.148148,0.833333,1,0.25,0.7,1,0.2]
precision
0.7814814814814813 [1,1,1,1,0.148148,1,0.333333,1,1,0.333333]
precision
0.7170875420875421 [1,0.5,1,1,0.148148,1,0.25,1,1,0.272727]
predictive_accuracy
0.4
predictive_accuracy
0.465
predictive_accuracy
0.425
predictive_accuracy
0.415
predictive_accuracy
0.37
predictive_accuracy
0.395
predictive_accuracy
0.43
predictive_accuracy
0.395
predictive_accuracy
0.38
predictive_accuracy
0.365
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
0.4 [0.65,0.4,0.5,0.15,1,0.15,0.25,0.4,0.35,0.15]
recall
0.465 [0.65,0.3,0.65,0.1,1,0.1,0.3,0.6,0.7,0.25]
recall
0.425 [0.55,0.5,0.45,0.05,1,0.05,0.25,0.45,0.75,0.2]
recall
0.415 [0.65,0.1,0.5,0.1,1,0.3,0.25,0.4,0.6,0.25]
recall
0.37 [0.65,0.35,0.45,1,0.25,0.15,0.05,0.35,0.4,0.05]
recall
0.395 [0.75,0.3,0.6,0.05,1,0.05,0.1,0.55,0.5,0.05]
recall
0.43 [0.75,0.35,0.65,0.15,1,0,0.1,0.45,0.6,0.25]
recall
0.395 [0.65,0.3,0.5,0.1,0.9,0,0.35,0.65,0.25,0.25]
recall
0.38 [0.65,0.15,0.55,1,0.15,0,0.05,0.35,0.7,0.2]
recall
0.365 [0.75,0.05,0.55,0.1,1,0.1,0.05,0.45,0.45,0.15]
relative_absolute_error
0.6666666666666659
relative_absolute_error
0.5944444444444439
relative_absolute_error
0.6388888888888882
relative_absolute_error
0.6499999999999992
relative_absolute_error
0.6999999999999993
relative_absolute_error
0.6722222222222214
relative_absolute_error
0.6333333333333326
relative_absolute_error
0.6722222222222214
relative_absolute_error
0.6888888888888881
relative_absolute_error
0.7055555555555546
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
0.3464101615137751
root_mean_squared_error
0.32710854467592215
root_mean_squared_error
0.3391164991562631
root_mean_squared_error
0.342052627529741
root_mean_squared_error
0.35496478698597655
root_mean_squared_error
0.34785054261852133
root_mean_squared_error
0.33763886032268225
root_mean_squared_error
0.34785054261852133
root_mean_squared_error
0.3521363372331798
root_mean_squared_error
0.3563705936241088
root_relative_squared_error
1.154700538379251
root_relative_squared_error
1.0903618155864079
root_relative_squared_error
1.1303883305208775
root_relative_squared_error
1.1401754250991374
root_relative_squared_error
1.1832159566199225
root_relative_squared_error
1.159501808728405
root_relative_squared_error
1.1254628677422749
root_relative_squared_error
1.159501808728405
root_relative_squared_error
1.1737877907772667
root_relative_squared_error
1.1879019787470302
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
3502.7666830000044
usercpu_time_millis
3450.864626999987
usercpu_time_millis
3530.84149
usercpu_time_millis
3440.5916119999915
usercpu_time_millis
3535.5545710000056
usercpu_time_millis
3482.1441619999973
usercpu_time_millis
3443.4473000000307
usercpu_time_millis
3110.0867110000363
usercpu_time_millis
2657.176386000003
usercpu_time_millis
2666.507330999991
usercpu_time_millis_testing
52.319916000016065
usercpu_time_millis_testing
52.419096999983594
usercpu_time_millis_testing
51.178577000001724
usercpu_time_millis_testing
52.67947300001197
usercpu_time_millis_testing
52.679060000002664
usercpu_time_millis_testing
52.498431999993045
usercpu_time_millis_testing
52.405514000014364
usercpu_time_millis_testing
43.79088500002126
usercpu_time_millis_testing
43.72739900000511
usercpu_time_millis_testing
43.82168699999056
usercpu_time_millis_training
3450.4467669999885
usercpu_time_millis_training
3398.4455300000036
usercpu_time_millis_training
3479.6629129999983
usercpu_time_millis_training
3387.9121389999796
usercpu_time_millis_training
3482.875511000003
usercpu_time_millis_training
3429.6457300000043
usercpu_time_millis_training
3391.0417860000166
usercpu_time_millis_training
3066.295826000015
usercpu_time_millis_training
2613.448986999998
usercpu_time_millis_training
2622.6856440000006