8958687
1935
Hilde Weerts
9954
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)
6894291
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
13.685410278618933
7650
cache_size
200
7650
class_weight
null
7650
coef0
0.43872833905918407
7650
decision_function_shape
"ovr"
7650
degree
3
7650
gamma
0.007274733449149372
7650
kernel
"rbf"
7650
max_iter
-1
7650
probability
false
7650
random_state
1
7650
shrinking
false
7650
tol
0.0005687394533659914
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
1491
one-hundred-plants-margin
https://www.openml.org/data/download/1592283/phpCsX3fx
-1
18832636
description
https://api.openml.org/data/download/18832636/description.xml
-1
18832637
predictions
https://api.openml.org/data/download/18832637/predictions.arff
area_under_roc_curve
0.9204545454545456 [0.842803,0.96875,1,1,0.96875,0.874369,0.999684,1,0.936553,0.96875,0.967803,0.937184,1,0.843434,1,0.96875,1,0.809343,0.714331,0.590593,0.842803,0.96875,0.998737,1,0.937184,0.715278,0.715909,0.936553,0.9375,1,0.999684,1,0.999369,0.81029,0.937184,0.967803,0.71654,0.715909,0.999369,1,0.904356,0.968434,1,0.968119,0.968434,0.96875,0.9375,0.968119,0.904672,0.936869,0.904672,0.905619,0.937184,0.842487,0.874053,0.778725,1,0.968434,0.873106,0.873737,0.968119,0.968434,0.874053,0.967803,0.999369,0.810606,0.684975,1,0.905619,0.873422,0.905303,0.9375,0.904356,0.96875,0.936869,0.96875,0.968434,0.84154,1,1,0.905934,0.937184,0.874684,0.873106,0.905303,1,1,0.935922,0.9375,1,0.874684,0.999369,0.968119,0.936869,0.96875,0.936869,0.905303,0.905303,0.686237,0.937184]
average_cost
0
f_measure
0.8426648814107015 [0.733333,0.967742,1,1,0.967742,0.8,0.969697,1,0.848485,0.967742,0.882353,0.903226,1,0.785714,1,0.967742,1,0.555556,0.378378,0.206897,0.733333,0.967742,0.888889,1,0.903226,0.411765,0.4375,0.848485,0.933333,1,0.969697,1,0.941176,0.606061,0.903226,0.882353,0.466667,0.4375,0.941176,1,0.742857,0.9375,1,0.909091,0.9375,0.967742,0.933333,0.909091,0.764706,0.875,0.764706,0.83871,0.903226,0.709677,0.774194,0.545455,1,0.9375,0.705882,0.75,0.909091,0.9375,0.774194,0.882353,0.941176,0.625,0.4,1,0.83871,0.727273,0.8125,0.933333,0.742857,0.967742,0.875,0.967742,0.9375,0.647059,1,1,0.866667,0.903226,0.827586,0.705882,0.8125,1,1,0.8,0.933333,1,0.827586,0.941176,0.909091,0.875,0.967742,0.875,0.8125,0.8125,0.461538,0.903226]
kappa
0.8409090909090909
kb_relative_information_score
1347.4500345192819
mean_absolute_error
0.003149999999999988
mean_prior_absolute_error
0.019800000000000036
number_of_instances
1600 [16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16]
precision
0.8468775346170857 [0.785714,1,1,1,1,0.857143,0.941176,1,0.823529,1,0.833333,0.933333,1,0.916667,1,1,1,0.5,0.333333,0.230769,0.785714,1,0.8,1,0.933333,0.388889,0.4375,0.823529,1,1,0.941176,1,0.888889,0.588235,0.933333,0.833333,0.5,0.4375,0.888889,1,0.684211,0.9375,1,0.882353,0.9375,1,1,0.882353,0.722222,0.875,0.722222,0.866667,0.933333,0.733333,0.8,0.529412,1,0.9375,0.666667,0.75,0.882353,0.9375,0.8,0.833333,0.888889,0.625,0.428571,1,0.866667,0.705882,0.8125,1,0.684211,1,0.875,1,0.9375,0.611111,1,1,0.928571,0.933333,0.923077,0.666667,0.8125,1,1,0.736842,1,1,0.923077,0.888889,0.882353,0.875,1,0.875,0.8125,0.8125,0.6,0.933333]
predictive_accuracy
0.8425
prior_entropy
6.6438561897747395
recall
0.8425 [0.6875,0.9375,1,1,0.9375,0.75,1,1,0.875,0.9375,0.9375,0.875,1,0.6875,1,0.9375,1,0.625,0.4375,0.1875,0.6875,0.9375,1,1,0.875,0.4375,0.4375,0.875,0.875,1,1,1,1,0.625,0.875,0.9375,0.4375,0.4375,1,1,0.8125,0.9375,1,0.9375,0.9375,0.9375,0.875,0.9375,0.8125,0.875,0.8125,0.8125,0.875,0.6875,0.75,0.5625,1,0.9375,0.75,0.75,0.9375,0.9375,0.75,0.9375,1,0.625,0.375,1,0.8125,0.75,0.8125,0.875,0.8125,0.9375,0.875,0.9375,0.9375,0.6875,1,1,0.8125,0.875,0.75,0.75,0.8125,1,1,0.875,0.875,1,0.75,1,0.9375,0.875,0.9375,0.875,0.8125,0.8125,0.375,0.875]
relative_absolute_error
0.15909090909090817
root_mean_prior_squared_error
0.09949874371066209
root_mean_squared_error
0.056124860801609014
root_relative_squared_error
0.5640760748177647
total_cost
0
area_under_roc_curve
0.9084666825889659 [1,0.75,1,1,1,1,1,1,1,1,0.75,1,1,1,1,0.5,1,0.75,0.496835,0.490566,0.5,1,0.996855,1,1,0.740506,0.743671,0.996835,1,1,1,1,0.996835,0.5,1,0.996855,1,0.996855,1,1,0.496855,1,1,1,1,1,1,0.996855,1,0.75,1,1,1,1,0.996855,0.496855,1,1,1,1,1,1,0.75,1,1,0.996835,0.5,1,1,0.5,0.75,1,1,1,1,1,0.75,0.493671,1,1,1,1,0.5,0.996855,1,1,1,0.996835,0.75,1,0.996835,1,1,0.996835,1,0.75,0.496855,0.993671,0.496835,1]
area_under_roc_curve
0.9273744128652176 [1,1,1,1,1,1,0.996835,1,1,1,1,1,1,0.75,1,1,1,0.746835,0.746835,0.496855,1,1,0.996855,1,1,0.746835,0.490506,1,1,1,1,1,1,1,0.75,0.996855,0.496855,0.496855,1,1,1,1,1,1,1,1,1,1,0.996835,1,0.996835,1,1,0.75,1,0.496855,1,1,1,0.75,1,1,1,0.996835,1,0.75,0.75,1,1,1,0.996835,1,1,1,1,1,1,0.993671,1,1,0.75,1,0.996855,1,0.746835,1,1,0.996835,0.75,1,0.75,1,1,0.75,1,1,1,1,0.5,0.496855]
area_under_roc_curve
0.9368680837512935 [1,1,1,1,1,0.996835,1,1,1,1,1,0.75,1,0.75,1,1,1,0.993671,1,0.496835,1,1,1,1,1,0.746835,1,0.996855,1,1,1,1,1,0.496835,0.996855,0.996855,0.993711,1,1,1,0.743671,0.5,1,1,0.996835,1,0.75,1,0.75,1,0.996835,1,1,1,1,0.75,1,1,0.996855,0.496835,1,1,1,0.5,1,1,0.75,1,1,0.75,1,1,1,1,0.996855,1,1,0.996835,1,1,1,1,1,0.75,1,1,1,1,1,1,1,0.996855,1,1,1,1,1,0.75,0.5,1]
area_under_roc_curve
0.9084865854629406 [0.5,1,1,1,0.75,0.75,1,1,0.746835,1,1,0.75,1,0.75,1,1,1,0.743671,0.493711,0.75,1,1,0.996835,1,0.5,0.75,1,1,1,1,1,1,1,0.75,1,1,1,0.496855,1,1,0.996835,0.996855,1,1,1,1,1,1,0.996835,1,0.996835,1,1,0.75,1,0.990506,1,1,0.996855,1,0.996855,1,1,1,1,0.496835,0.493671,1,1,0.743671,0.5,1,0.990566,1,0.996855,1,1,0.75,1,1,1,1,0.75,0.75,0.5,1,1,1,1,1,0.75,1,0.996855,1,1,0.996855,0.75,0.996835,0.996855,0.75]
area_under_roc_curve
0.9115715309290661 [0.746835,1,1,1,1,0.75,1,1,1,1,0.996835,1,1,0.5,1,1,1,0.496835,0.987421,0.746835,0.75,1,1,1,1,0.993671,0.5,1,1,1,1,1,1,0.746835,1,1,0.496835,0.746835,1,1,0.746835,1,1,0.5,1,1,1,1,1,1,0.496855,0.496855,0.75,0.996855,0.496835,0.5,1,0.996835,0.75,1,1,1,0.5,1,1,1,1,1,0.75,0.996835,0.996835,1,1,1,0.75,1,0.996835,0.996835,1,1,1,1,1,0.993671,0.996855,1,1,1,1,1,1,1,1,1,0.75,1,0.996835,1,0.496855,1]
area_under_roc_curve
0.9179205477270918 [0.75,1,1,1,1,0.75,1,1,0.996855,0.75,1,0.996835,1,1,1,1,1,0.996835,0.996855,0.5,0.75,0.75,0.996835,1,0.996835,0.743671,0.746835,0.5,1,1,1,1,1,0.996835,1,0.75,0.75,0.490506,1,1,0.996835,1,1,0.996855,1,1,1,1,0.75,0.75,1,1,1,0.993711,0.996835,0.996835,1,1,0.75,0.996855,1,0.75,0.996855,1,1,0.75,0.996855,1,0.746835,1,1,1,1,1,0.75,1,1,0.75,1,1,0.996855,0.75,0.75,0.996835,1,1,1,0.996855,1,1,0.5,1,1,1,1,1,1,1,0.5,1]
area_under_roc_curve
0.9210851046891172 [1,1,1,1,1,0.75,1,1,0.996855,1,1,1,1,1,1,1,1,1,0.5,0.5,0.743671,1,1,1,1,0.5,0.493711,0.75,1,1,0.996835,1,1,0.993711,1,1,0.493671,0.746835,0.993671,1,1,1,1,1,0.5,0.75,0.75,0.996835,0.996855,0.996855,1,1,0.996835,0.5,1,1,1,1,0.5,1,0.996835,0.996835,0.996855,0.996835,1,0.496855,0.996855,1,1,1,1,1,0.996835,1,1,1,1,1,1,1,0.75,1,1,0.996835,1,1,1,0.5,1,1,1,1,0.75,1,1,0.75,1,1,0.5,1]
area_under_roc_curve
0.9337433325372183 [0.75,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.996855,0.984177,0.5,0.75,1,1,1,0.75,0.5,1,1,0.5,1,1,1,0.996855,1,1,1,0.5,0.746835,1,1,1,1,1,1,1,1,1,0.75,0.996855,1,0.996855,0.75,0.75,0.996855,1,0.746835,1,1,1,0.993711,1,1,1,1,1,0.496855,0.496855,1,1,0.746835,1,1,0.996835,1,1,1,1,0.5,1,1,0.75,1,0.75,1,0.75,1,1,0.996855,1,1,1,1,0.996835,1,1,0.996835,1,1,1,1]
area_under_roc_curve
0.9369078894992438 [0.996855,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.493711,0.75,0.493711,0.996835,1,1,1,1,0.496855,0.496855,1,1,1,1,1,1,0.996855,1,1,1,0.5,1,1,1,1,1,0.996835,1,1,1,1,0.5,1,0.75,0.996835,1,0.75,0.75,0.5,1,0.5,0.993671,1,1,1,1,0.996835,1,1,0.743671,1,0.996835,1,0.996855,0.5,0.75,1,1,1,1,0.996855,1,1,1,1,1,0.5,1,1,1,1,1,1,0.75,1,1,0.996835,1,1,0.5,1,0.75,1]
area_under_roc_curve
0.9022768887827401 [0.996855,1,1,1,1,0.996855,1,1,0.75,1,0.993711,1,1,0.746835,1,1,1,1,0.5,0.993711,1,1,1,1,1,0.496855,0.5,0.996835,0.75,1,1,1,1,0.996855,0.75,1,0.746835,1,1,1,1,1,1,1,1,1,1,1,0.996855,0.996855,0.75,0.75,1,0.75,0.75,0.996855,1,1,0.993671,0.75,0.75,1,0.496835,1,0.993711,0.993711,0.496835,1,0.75,0.996855,1,0.5,0.496835,0.75,1,0.75,1,1,1,1,1,0.496855,1,0.496855,0.996835,1,1,0.746835,1,1,1,0.996835,1,0.75,1,1,0.996855,0.5,0.996835,1]
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
0.8167746011688517
kappa
0.8546775658492279
kappa
0.8736426456071076
kappa
0.8168107702633345
kappa
0.8230857323381905
kappa
0.8357484107869073
kappa
0.842047069973148
kappa
0.867324777887463
kappa
0.8736176935229067
kappa
0.8042156785347754
kb_relative_information_score
130.93671032166446
kb_relative_information_score
136.94980473787183
kb_relative_information_score
139.95635194597548
kb_relative_information_score
130.93671032166446
kb_relative_information_score
131.9388927243657
kb_relative_information_score
133.94325752976815
kb_relative_information_score
134.94543993246936
kb_relative_information_score
138.95416954327425
kb_relative_information_score
139.95635194597548
kb_relative_information_score
128.93234551626202
mean_absolute_error
0.003625000000000001
mean_absolute_error
0.002875000000000001
mean_absolute_error
0.0025000000000000005
mean_absolute_error
0.003625000000000001
mean_absolute_error
0.003500000000000001
mean_absolute_error
0.0032500000000000007
mean_absolute_error
0.0031250000000000006
mean_absolute_error
0.0026250000000000006
mean_absolute_error
0.0025000000000000005
mean_absolute_error
0.0038750000000000013
mean_prior_absolute_error
0.019800000000000033
mean_prior_absolute_error
0.019800000000000033
mean_prior_absolute_error
0.019800000000000033
mean_prior_absolute_error
0.019800000000000033
mean_prior_absolute_error
0.019800000000000033
mean_prior_absolute_error
0.019800000000000033
mean_prior_absolute_error
0.019800000000000033
mean_prior_absolute_error
0.019800000000000033
mean_prior_absolute_error
0.019800000000000033
mean_prior_absolute_error
0.019800000000000033
number_of_instances
160 [1,2,2,1,2,1,2,1,2,1,2,2,2,2,2,1,2,2,2,1,1,1,1,1,1,2,2,2,2,1,2,2,2,2,2,1,1,1,1,2,1,1,2,2,2,2,1,1,2,2,2,2,1,2,1,1,2,1,1,2,1,1,2,2,1,2,2,1,1,1,2,1,2,2,1,2,2,2,2,2,2,2,1,1,2,2,2,2,2,1,2,1,2,2,2,2,1,2,2,1]
number_of_instances
160 [1,2,2,1,2,1,2,1,2,1,2,2,2,2,2,1,2,2,2,1,1,1,1,1,1,2,2,2,2,1,2,2,2,2,2,1,1,1,1,2,1,1,2,2,2,2,1,1,2,2,2,2,1,2,1,1,2,1,1,2,1,1,2,2,1,2,2,1,1,1,2,1,2,2,1,2,2,2,2,2,2,2,1,1,2,2,2,2,2,1,2,1,2,2,2,2,1,2,2,1]
number_of_instances
160 [2,2,2,1,2,2,1,2,2,2,2,2,1,2,2,2,2,2,1,2,1,1,2,1,1,2,2,1,2,2,1,2,2,2,1,1,1,1,1,2,2,1,1,1,2,1,2,1,2,2,2,1,1,2,1,2,1,2,1,2,1,1,2,1,2,2,2,2,1,2,2,2,1,2,1,2,2,2,2,2,1,2,2,2,1,1,1,2,2,1,2,1,1,2,2,1,2,2,1,2]
number_of_instances
160 [2,2,2,1,2,2,1,2,2,2,2,2,1,2,2,2,2,2,1,2,1,1,2,1,1,2,2,1,2,2,1,2,2,2,1,1,1,1,1,2,2,1,1,1,2,1,2,1,2,2,2,1,1,2,1,2,1,2,1,2,1,1,2,1,2,2,2,2,1,2,2,2,1,2,1,2,2,2,2,2,1,2,2,2,1,1,1,2,2,1,2,1,1,2,2,1,2,2,1,2]
number_of_instances
160 [2,1,2,2,1,2,1,2,1,2,2,2,1,1,1,2,2,2,1,2,2,2,2,2,2,2,2,1,1,2,1,1,2,2,1,2,2,2,2,2,2,2,1,1,1,1,2,2,2,2,1,1,2,1,2,2,1,2,2,1,2,2,1,1,2,2,1,2,2,2,2,2,1,1,2,1,2,2,2,1,1,2,2,2,1,1,1,1,2,2,1,2,1,1,2,1,2,1,1,2]
number_of_instances
160 [2,1,2,2,1,2,1,2,1,2,2,2,1,1,1,2,2,2,1,2,2,2,2,2,2,2,2,1,1,2,1,1,2,2,1,2,2,2,2,2,2,2,1,1,1,1,2,2,2,2,1,1,2,1,2,2,1,2,2,1,2,2,1,1,2,2,1,2,2,2,2,2,1,1,2,1,2,2,2,1,1,2,2,2,1,1,1,1,2,2,1,2,1,1,2,1,2,1,1,2]
number_of_instances
160 [2,1,1,2,1,2,2,2,1,2,1,1,2,1,1,2,1,1,2,2,2,2,2,2,2,1,1,2,1,2,2,1,1,1,2,2,2,2,2,1,2,2,2,2,1,2,2,2,1,1,1,2,2,1,2,2,2,2,2,1,2,2,1,2,2,1,1,2,2,2,1,2,2,1,2,1,1,1,1,1,2,1,2,2,2,2,2,1,1,2,1,2,2,1,1,2,2,1,2,2]
number_of_instances
160 [2,1,1,2,1,2,2,2,1,2,1,1,2,1,1,2,1,1,2,2,2,2,2,2,2,1,1,2,1,2,2,1,1,1,2,2,2,2,2,1,2,2,2,2,1,2,2,2,1,1,1,2,2,1,2,2,2,2,2,1,2,2,1,2,2,1,1,2,2,2,1,2,2,1,2,1,1,1,1,1,2,1,2,2,2,2,2,1,1,2,1,2,2,1,1,2,2,1,2,2]
number_of_instances
160 [1,2,1,2,2,1,2,1,2,1,1,1,2,2,2,1,1,1,2,1,2,2,1,2,2,1,1,2,2,1,2,2,1,1,2,2,2,2,2,1,1,2,2,2,2,2,1,2,1,1,2,2,2,2,2,1,2,1,2,2,2,2,2,2,1,1,2,1,2,1,1,1,2,2,2,2,1,1,1,2,2,1,1,1,2,2,2,2,1,2,2,2,2,2,1,2,1,2,2,1]
number_of_instances
160 [1,2,1,2,2,1,2,1,2,1,1,1,2,2,2,1,1,1,2,1,2,2,1,2,2,1,1,2,2,1,2,2,1,1,2,2,2,2,2,1,1,2,2,2,2,2,1,2,1,1,2,2,2,2,2,1,2,1,2,2,2,2,2,2,1,1,2,1,2,1,1,1,2,2,2,2,1,1,1,2,2,1,1,1,2,2,2,2,1,2,2,2,2,2,1,2,1,2,2,1]
predictive_accuracy
0.81875
predictive_accuracy
0.85625
predictive_accuracy
0.875
predictive_accuracy
0.81875
predictive_accuracy
0.825
predictive_accuracy
0.8375
predictive_accuracy
0.84375
predictive_accuracy
0.86875
predictive_accuracy
0.875
predictive_accuracy
0.80625
prior_entropy
6.6438561897747395
prior_entropy
6.6438561897747395
prior_entropy
6.6438561897747395
prior_entropy
6.6438561897747395
prior_entropy
6.6438561897747395
prior_entropy
6.6438561897747395
prior_entropy
6.6438561897747395
prior_entropy
6.6438561897747395
prior_entropy
6.6438561897747395
prior_entropy
6.6438561897747395
recall
0.81875 [1,0.5,1,1,1,1,1,1,1,1,0.5,1,1,1,1,0,1,0.5,0,0,0,1,1,1,1,0.5,0.5,1,1,1,1,1,1,0,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,0,1,1,1,1,1,1,0.5,1,1,1,0,1,1,0,0.5,1,1,1,1,1,0.5,0,1,1,1,1,0,1,1,1,1,1,0.5,1,1,1,1,1,1,0.5,0,1,0,1]
recall
0.85625 [1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0.5,0.5,0,1,1,1,1,1,0.5,0,1,1,1,1,1,1,1,0.5,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,0,1,1,1,0.5,1,1,1,1,1,0.5,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0.5,1,1,1,0.5,1,0.5,1,1,0.5,1,1,1,1,0,0]
recall
0.875 [1,1,1,1,1,1,1,1,1,1,1,0.5,1,0.5,1,1,1,1,1,0,1,1,1,1,1,0.5,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0.5,0,1,1,1,1,0.5,1,0.5,1,1,1,1,1,1,0.5,1,1,1,0,1,1,1,0,1,1,0.5,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,0,1]
recall
0.81875 [0,1,1,1,0.5,0.5,1,1,0.5,1,1,0.5,1,0.5,1,1,1,0.5,0,0.5,1,1,1,1,0,0.5,1,1,1,1,1,1,1,0.5,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,0.5,0,1,1,1,1,1,1,0.5,1,1,1,1,0.5,0.5,0,1,1,1,1,1,0.5,1,1,1,1,1,0.5,1,1,0.5]
recall
0.825 [0.5,1,1,1,1,0.5,1,1,1,1,1,1,1,0,1,1,1,0,1,0.5,0.5,1,1,1,1,1,0,1,1,1,1,1,1,0.5,1,1,0,0.5,1,1,0.5,1,1,0,1,1,1,1,1,1,0,0,0.5,1,0,0,1,1,0.5,1,1,1,0,1,1,1,1,1,0.5,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0,1]
recall
0.8375 [0.5,1,1,1,1,0.5,1,1,1,0.5,1,1,1,1,1,1,1,1,1,0,0.5,0.5,1,1,1,0.5,0.5,0,1,1,1,1,1,1,1,0.5,0.5,0,1,1,1,1,1,1,1,1,1,1,0.5,0.5,1,1,1,1,1,1,1,1,0.5,1,1,0.5,1,1,1,0.5,1,1,0.5,1,1,1,1,1,0.5,1,1,0.5,1,1,1,0.5,0.5,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,0,1]
recall
0.84375 [1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0.5,1,1,1,1,0,0,0.5,1,1,1,1,1,1,1,1,0,0.5,1,1,1,1,1,1,0,0.5,0.5,1,1,1,1,1,1,0,1,1,1,1,0,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,0,1,1,1,1,0.5,1,1,0.5,1,1,0,1]
recall
0.86875 [0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0.5,1,1,1,0.5,0,1,1,0,1,1,1,1,1,1,1,0,0.5,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0.5,0.5,1,1,0.5,1,1,1,1,1,1,1,1,1,0,0,1,1,0.5,1,1,1,1,1,1,1,0,1,1,0.5,1,0.5,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1]
recall
0.875 [1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0.5,0,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,0,1,0.5,1,1,0.5,0.5,0,1,0,1,1,1,1,1,1,1,1,0.5,1,1,1,1,0,0.5,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0.5,1,1,1,1,1,0,1,0.5,1]
recall
0.80625 [1,1,1,1,1,1,1,1,0.5,1,1,1,1,0.5,1,1,1,1,0,1,1,1,1,1,1,0,0,1,0.5,1,1,1,1,1,0.5,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,0.5,1,0.5,0.5,1,1,1,1,0.5,0.5,1,0,1,1,1,0,1,0.5,1,1,0,0,0.5,1,0.5,1,1,1,1,1,0,1,0,1,1,1,0.5,1,1,1,1,1,0.5,1,1,1,0,1,1]
relative_absolute_error
0.18308080808080782
relative_absolute_error
0.14520202020202
relative_absolute_error
0.12626262626262608
relative_absolute_error
0.18308080808080782
relative_absolute_error
0.17676767676767655
relative_absolute_error
0.1641414141414139
relative_absolute_error
0.1578282828282826
relative_absolute_error
0.13257575757575737
relative_absolute_error
0.12626262626262608
relative_absolute_error
0.19570707070707044
root_mean_prior_squared_error
0.09949874371066206
root_mean_prior_squared_error
0.09949874371066206
root_mean_prior_squared_error
0.09949874371066206
root_mean_prior_squared_error
0.09949874371066206
root_mean_prior_squared_error
0.09949874371066206
root_mean_prior_squared_error
0.09949874371066206
root_mean_prior_squared_error
0.09949874371066206
root_mean_prior_squared_error
0.09949874371066206
root_mean_prior_squared_error
0.09949874371066206
root_mean_prior_squared_error
0.09949874371066206
root_mean_squared_error
0.06020797289396149
root_mean_squared_error
0.05361902647381805
root_mean_squared_error
0.05
root_mean_squared_error
0.06020797289396149
root_mean_squared_error
0.05916079783099617
root_mean_squared_error
0.0570087712549569
root_mean_squared_error
0.05590169943749475
root_mean_squared_error
0.051234753829797995
root_mean_squared_error
0.05
root_mean_squared_error
0.06224949798994367
root_relative_squared_error
0.6051128953853288
root_relative_squared_error
0.5388914922357191
root_relative_squared_error
0.5025189076296057
root_relative_squared_error
0.6051128953853288
root_relative_squared_error
0.5945883900105629
root_relative_squared_error
0.5729597091269403
root_relative_squared_error
0.5618332187193681
root_relative_squared_error
0.5149286505444369
root_relative_squared_error
0.5025189076296057
root_relative_squared_error
0.6256309946079566
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
475.69599799999196
usercpu_time_millis
470.06035699996573
usercpu_time_millis
466.9689079998989
usercpu_time_millis
460.68772600006014
usercpu_time_millis
460.0077299999157
usercpu_time_millis
459.6392930000093
usercpu_time_millis
475.2056239997273
usercpu_time_millis
469.63239199999407
usercpu_time_millis
458.00123899994105
usercpu_time_millis
459.868734000338
usercpu_time_millis_testing
54.90942799997356
usercpu_time_millis_testing
54.05771400000958
usercpu_time_millis_testing
51.46094799988532
usercpu_time_millis_testing
53.085619000057704
usercpu_time_millis_testing
53.84754700003214
usercpu_time_millis_testing
54.851635999966675
usercpu_time_millis_testing
52.47810599985314
usercpu_time_millis_testing
52.58580099985011
usercpu_time_millis_testing
54.04402099998151
usercpu_time_millis_testing
52.35412800016093
usercpu_time_millis_training
420.7865700000184
usercpu_time_millis_training
416.00264299995615
usercpu_time_millis_training
415.50796000001355
usercpu_time_millis_training
407.60210700000243
usercpu_time_millis_training
406.16018299988355
usercpu_time_millis_training
404.7876570000426
usercpu_time_millis_training
422.7275179998742
usercpu_time_millis_training
417.04659100014396
usercpu_time_millis_training
403.95721799995954
usercpu_time_millis_training
407.5146060001771