8958316
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)
6893923
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
93.21828698117817
7650
cache_size
200
7650
class_weight
null
7650
coef0
0.5771270548215587
7650
decision_function_shape
"ovr"
7650
degree
3
7650
gamma
0.04090120015751121
7650
kernel
"rbf"
7650
max_iter
-1
7650
probability
false
7650
random_state
1
7650
shrinking
false
7650
tol
0.0020347367041112013
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
18831900
description
https://api.openml.org/data/download/18831900/description.xml
-1
18831901
predictions
https://api.openml.org/data/download/18831901/predictions.arff
area_under_roc_curve
0.920770202020202 [0.874369,0.96875,1,0.9375,0.937184,0.874053,1,1,0.905934,0.9375,0.968119,0.968434,1,0.90625,0.99779,1,1,0.747159,0.745896,0.588699,0.874369,0.96875,0.967172,1,0.937184,0.746212,0.74779,0.967487,0.937184,1,0.968434,0.96875,0.999369,0.809975,0.905619,0.936869,0.77904,0.685606,0.968119,1,0.935606,0.936869,1,0.936553,0.968434,0.96875,0.937184,0.968119,0.904987,0.905619,0.904672,0.905619,0.937184,0.842803,0.905303,0.748106,1,0.968434,0.873106,0.842172,0.936869,0.96875,0.842487,0.968119,0.968119,0.841856,0.717172,1,0.968119,0.905303,0.874369,0.937184,0.93529,0.96875,0.904987,0.96875,0.968434,0.842172,1,1,0.937184,0.936553,0.90625,0.779672,0.905619,0.968434,1,0.936237,0.937184,1,0.936869,0.999684,0.937184,0.968434,0.96875,0.936869,0.936869,0.936553,0.779672,0.937184]
average_cost
0
f_measure
0.844400352374752 [0.8,0.967742,1,0.933333,0.903226,0.774194,1,1,0.866667,0.933333,0.909091,0.9375,1,0.896552,0.820513,1,1,0.484848,0.432432,0.171429,0.8,0.967742,0.833333,1,0.903226,0.444444,0.516129,0.857143,0.903226,1,0.9375,0.967742,0.941176,0.588235,0.83871,0.875,0.5625,0.428571,0.909091,1,0.777778,0.875,1,0.848485,0.9375,0.967742,0.903226,0.909091,0.787879,0.83871,0.764706,0.83871,0.903226,0.733333,0.8125,0.533333,1,0.9375,0.705882,0.6875,0.875,0.967742,0.709677,0.909091,0.909091,0.666667,0.5,1,0.909091,0.8125,0.8,0.903226,0.756757,0.967742,0.787879,0.967742,0.9375,0.6875,1,1,0.903226,0.848485,0.896552,0.6,0.83871,0.9375,1,0.823529,0.903226,1,0.875,0.969697,0.903226,0.9375,0.967742,0.875,0.875,0.848485,0.6,0.903226]
kappa
0.8415404040404041
kb_relative_information_score
1348.452216921983
mean_absolute_error
0.003137499999999988
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
0.8497254907302356 [0.857143,1,1,1,0.933333,0.8,1,1,0.928571,1,0.882353,0.9375,1,1,0.695652,1,1,0.470588,0.380952,0.157895,0.857143,1,0.75,1,0.933333,0.4,0.533333,0.789474,0.933333,1,0.9375,1,0.888889,0.555556,0.866667,0.875,0.5625,0.5,0.882353,1,0.7,0.875,1,0.823529,0.9375,1,0.933333,0.882353,0.764706,0.866667,0.722222,0.866667,0.933333,0.785714,0.8125,0.571429,1,0.9375,0.666667,0.6875,0.875,1,0.733333,0.882353,0.882353,0.647059,0.583333,1,0.882353,0.8125,0.857143,0.933333,0.666667,1,0.764706,1,0.9375,0.6875,1,1,0.933333,0.823529,1,0.642857,0.866667,0.9375,1,0.777778,0.933333,1,0.875,0.941176,0.933333,0.9375,1,0.875,0.875,0.823529,0.642857,0.933333]
predictive_accuracy
0.843125
prior_entropy
6.6438561897747395
recall
0.843125 [0.75,0.9375,1,0.875,0.875,0.75,1,1,0.8125,0.875,0.9375,0.9375,1,0.8125,1,1,1,0.5,0.5,0.1875,0.75,0.9375,0.9375,1,0.875,0.5,0.5,0.9375,0.875,1,0.9375,0.9375,1,0.625,0.8125,0.875,0.5625,0.375,0.9375,1,0.875,0.875,1,0.875,0.9375,0.9375,0.875,0.9375,0.8125,0.8125,0.8125,0.8125,0.875,0.6875,0.8125,0.5,1,0.9375,0.75,0.6875,0.875,0.9375,0.6875,0.9375,0.9375,0.6875,0.4375,1,0.9375,0.8125,0.75,0.875,0.875,0.9375,0.8125,0.9375,0.9375,0.6875,1,1,0.875,0.875,0.8125,0.5625,0.8125,0.9375,1,0.875,0.875,1,0.875,1,0.875,0.9375,0.9375,0.875,0.875,0.875,0.5625,0.875]
relative_absolute_error
0.15845959595959505
root_mean_prior_squared_error
0.09949874371066209
root_mean_squared_error
0.05601339125602009
root_relative_squared_error
0.5629557637320983
total_cost
0
area_under_roc_curve
0.9148156993869916 [0.996855,0.75,1,1,0.75,1,1,1,1,1,0.75,1,1,1,1,1,1,0.75,0.496835,0.490566,0.5,1,0.996855,1,1,0.743671,0.743671,0.996835,1,1,1,1,0.996835,0.496835,0.75,0.996855,1,0.996855,1,1,0.996855,0.996855,1,1,1,1,1,0.996855,1,0.75,1,1,1,1,0.996855,0.496855,1,1,1,1,1,1,0.75,1,1,1,0.5,1,1,0.5,0.75,1,1,1,1,1,0.75,0.5,1,1,1,1,1,0.996855,1,1,1,0.996835,0.75,1,0.996835,1,1,0.996835,1,0.75,0.5,0.993671,0.746835,1]
area_under_roc_curve
0.9179205477270915 [1,1,1,1,1,1,1,1,1,1,1,1,1,0.75,1,1,1,0.75,0.746835,0.487421,1,1,0.996855,1,1,0.746835,0.493671,1,0.996835,1,1,1,1,0.996835,0.75,0.496855,0.496855,0.5,1,1,1,1,1,0.75,1,1,1,1,0.746835,0.996835,0.993671,1,1,0.75,1,0.496855,1,1,1,0.5,1,1,0.75,1,1,0.996835,0.75,1,1,1,0.996835,1,1,1,0.996855,1,1,0.993671,1,1,0.75,0.996835,1,1,0.75,1,1,0.996835,0.75,1,0.75,1,0.75,1,1,1,1,1,0.75,0.496855]
area_under_roc_curve
0.9368879866252685 [1,1,1,1,1,0.746835,1,1,1,1,1,0.75,1,1,0.996835,1,1,0.743671,1,0.496835,1,1,0.75,1,1,0.746835,1,0.996855,1,1,1,1,1,0.75,0.993711,1,0.993711,0.5,1,1,0.746835,0.5,1,1,0.996835,1,0.75,1,0.75,1,1,1,1,1,1,1,1,1,0.996855,0.496835,1,1,0.75,0.5,1,1,1,1,1,0.75,1,0.996835,1,1,0.993711,1,1,0.996835,1,1,1,1,1,0.75,1,1,1,1,1,1,1,1,1,1,1,1,1,0.75,0.996855,1]
area_under_roc_curve
0.9148156993869915 [0.75,1,1,1,0.75,0.75,1,1,0.746835,1,1,1,1,1,1,1,1,0.743671,0.493711,0.746835,1,1,0.993671,1,0.5,1,1,1,1,1,1,1,1,0.75,1,1,1,0.496855,1,1,0.996835,0.996855,1,0.996855,1,1,1,1,0.996835,1,0.996835,1,1,0.75,1,0.743671,1,1,0.996855,1,0.996855,1,1,1,0.75,0.5,0.496835,1,1,0.746835,0.5,1,0.990566,1,1,1,1,0.75,1,1,1,1,0.75,0.75,0.5,1,1,1,1,1,0.75,1,1,1,1,0.996855,0.75,0.996835,0.993711,0.75]
area_under_roc_curve
0.9147161850171166 [0.75,1,1,1,1,0.75,1,1,1,1,0.996835,1,1,0.5,0.996855,1,1,0.746835,0.990566,0.743671,0.75,1,1,1,1,0.987342,0.5,1,1,1,1,0.5,1,0.496835,1,1,0.746835,0.5,1,1,0.996835,1,1,0.5,1,1,1,1,1,1,0.496855,0.496855,0.75,0.996855,0.496835,0.5,1,0.996835,0.746835,1,1,1,1,1,1,1,1,1,1,0.996835,0.996835,1,1,1,0.75,1,0.996835,1,1,1,1,1,1,0.746835,0.996855,1,1,1,1,1,1,1,1,1,0.75,1,0.996835,1,0.5,1]
area_under_roc_curve
0.9178807419791417 [0.75,1,1,0.75,1,0.75,1,1,1,0.75,1,0.996835,1,1,0.993711,1,1,0.996835,1,0.5,0.75,0.75,0.996835,1,0.996835,0.743671,0.746835,0.5,1,1,1,1,1,0.996835,1,0.75,0.75,0.743671,1,1,0.996835,1,1,0.996855,1,1,1,1,0.75,0.75,1,1,1,1,0.996835,0.996835,1,1,0.75,0.996855,1,0.75,0.996855,1,1,0.75,1,1,0.996835,1,0.75,1,0.996855,1,0.75,1,1,0.746835,1,1,0.996855,0.746835,0.75,0.746835,1,1,1,0.996855,0.996835,1,1,1,1,1,1,1,1,1,0.5,1]
area_under_roc_curve
0.9242098559031922 [1,1,1,1,0.996855,1,1,1,1,1,1,1,1,1,1,1,1,1,0.496835,0.5,0.993671,1,1,1,1,0.5,0.496855,1,1,1,0.746835,1,1,0.996855,1,1,0.493671,0.746835,0.993671,1,1,0.75,1,1,0.5,0.75,0.75,0.996835,1,1,1,0.996835,0.996835,0.5,1,0.75,1,1,0.5,1,0.996835,1,0.996855,0.996835,1,0.496855,0.993711,1,1,1,1,1,0.996835,1,1,1,1,1,1,1,1,1,1,0.996835,1,1,1,0.5,1,1,0.996855,1,0.75,1,1,0.75,1,1,0.5,1]
area_under_roc_curve
0.9242297587771677 [0.75,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.496855,0.984177,0.496835,0.75,1,1,1,0.75,0.5,1,1,0.5,1,1,1,0.996855,1,1,1,0.5,0.746835,1,1,1,1,1,1,1,1,1,0.75,0.996855,0.5,0.996855,0.75,0.75,0.996855,1,0.746835,1,1,0.996835,0.990566,1,1,1,1,1,0.496855,0.5,1,1,0.996835,1,1,0.996835,1,0.996835,1,1,0.5,1,1,0.75,1,0.75,0.75,0.75,0.75,1,1,1,1,1,1,0.996835,1,1,0.996835,1,1,0.996835,1]
area_under_roc_curve
0.9369277923732187 [0.996855,1,1,0.75,1,0.996855,1,1,0.75,1,1,1,1,1,0.996835,1,1,0.493711,1,0.496855,1,1,1,1,1,0.496855,0.996855,0.996835,1,1,1,1,1,0.996855,1,1,1,0.5,0.75,1,0.5,1,1,0.996835,1,1,0.996855,1,1,1,0.75,1,1,0.75,0.75,0.5,1,0.5,0.996835,1,0.75,1,0.996835,0.996835,1,0.996855,0.743671,1,0.996835,1,1,0.5,0.75,1,1,1,1,0.996855,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.75,1]
area_under_roc_curve
0.9054215428707904 [1,1,1,1,1,0.996855,1,1,0.75,0.5,0.996855,1,1,0.75,0.993671,1,1,0.5,0.5,0.990566,1,1,1,1,1,0.496855,0.5,0.996835,0.75,1,1,1,1,0.993711,0.75,1,0.996835,1,1,1,0.996855,1,1,1,1,1,1,1,0.996855,0.996855,0.75,0.75,1,0.746835,1,1,1,1,0.996835,0.75,0.75,1,0.496835,1,0.993711,0.993711,0.5,1,0.75,1,1,0.5,0.746835,0.75,0.75,0.75,1,1,1,1,1,0.496855,1,0.496855,0.996835,0.996835,1,0.746835,1,1,1,0.996835,1,0.75,1,1,0.996855,0.75,1,1]
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
0.8294377763739735
kappa
0.8357289527720739
kappa
0.8736476348416646
kappa
0.8294445102451735
kappa
0.829397361977727
kappa
0.8357419252941641
kappa
0.8483532106468683
kappa
0.8483532106468683
kappa
0.8736326659558504
kappa
0.8105088626584027
kb_relative_information_score
132.94107512706694
kb_relative_information_score
133.94325752976818
kb_relative_information_score
139.95635194597548
kb_relative_information_score
132.94107512706694
kb_relative_information_score
132.94107512706694
kb_relative_information_score
133.94325752976815
kb_relative_information_score
135.9476223351706
kb_relative_information_score
135.9476223351706
kb_relative_information_score
139.95635194597548
kb_relative_information_score
129.93452791896325
mean_absolute_error
0.003375000000000001
mean_absolute_error
0.0032500000000000007
mean_absolute_error
0.0025000000000000005
mean_absolute_error
0.003375000000000001
mean_absolute_error
0.003375000000000001
mean_absolute_error
0.0032500000000000007
mean_absolute_error
0.003000000000000001
mean_absolute_error
0.003000000000000001
mean_absolute_error
0.0025000000000000005
mean_absolute_error
0.003750000000000001
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
0.83125
predictive_accuracy
0.8375
predictive_accuracy
0.875
predictive_accuracy
0.83125
predictive_accuracy
0.83125
predictive_accuracy
0.8375
predictive_accuracy
0.85
predictive_accuracy
0.85
predictive_accuracy
0.875
predictive_accuracy
0.8125
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
0.83125 [1,0.5,1,1,0.5,1,1,1,1,1,0.5,1,1,1,1,1,1,0.5,0,0,0,1,1,1,1,0.5,0.5,1,1,1,1,1,1,0,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,0,1,1,1,1,1,1,0.5,1,1,1,0,1,1,0,0.5,1,1,1,1,1,0.5,0,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,0.5,0,1,0.5,1]
recall
0.8375 [1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0.5,0.5,0,1,1,1,1,1,0.5,0,1,1,1,1,1,1,1,0.5,0,0,0,1,1,1,1,1,0.5,1,1,1,1,0.5,1,1,1,1,0.5,1,0,1,1,1,0,1,1,0.5,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0.5,1,1,1,0.5,1,0.5,1,0.5,1,1,1,1,1,0.5,0]
recall
0.875 [1,1,1,1,1,0.5,1,1,1,1,1,0.5,1,1,1,1,1,0.5,1,0,1,1,0.5,1,1,0.5,1,1,1,1,1,1,1,0.5,1,1,1,0,1,1,0.5,0,1,1,1,1,0.5,1,0.5,1,1,1,1,1,1,1,1,1,1,0,1,1,0.5,0,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1]
recall
0.83125 [0.5,1,1,1,0.5,0.5,1,1,0.5,1,1,1,1,1,1,1,1,0.5,0,0.5,1,1,1,1,0,1,1,1,1,1,1,1,1,0.5,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,0.5,1,1,1,1,1,1,1,1,0.5,0,0,1,1,0.5,0,1,1,1,1,1,1,0.5,1,1,1,1,0.5,0.5,0,1,1,1,1,1,0.5,1,1,1,1,1,0.5,1,1,0.5]
recall
0.83125 [0.5,1,1,1,1,0.5,1,1,1,1,1,1,1,0,1,1,1,0.5,1,0.5,0.5,1,1,1,1,1,0,1,1,1,1,0,1,0,1,1,0.5,0,1,1,1,1,1,0,1,1,1,1,1,1,0,0,0.5,1,0,0,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0,1]
recall
0.8375 [0.5,1,1,0.5,1,0.5,1,1,1,0.5,1,1,1,1,1,1,1,1,1,0,0.5,0.5,1,1,1,0.5,0.5,0,1,1,1,1,1,1,1,0.5,0.5,0.5,1,1,1,1,1,1,1,1,1,1,0.5,0.5,1,1,1,1,1,1,1,1,0.5,1,1,0.5,1,1,1,0.5,1,1,1,1,0.5,1,1,1,0.5,1,1,0.5,1,1,1,0.5,0.5,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1]
recall
0.85 [1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,0,0,1,1,1,0.5,1,1,1,1,1,0,0.5,1,1,1,0.5,1,1,0,0.5,0.5,1,1,1,1,1,1,0,1,0.5,1,1,0,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,0.5,1,1,0.5,1,1,0,1]
recall
0.85 [0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,0.5,1,1,1,0.5,0,1,1,0,1,1,1,1,1,1,1,0,0.5,1,1,1,1,1,1,1,1,1,0.5,1,0,1,0.5,0.5,1,1,0.5,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,0,1,1,0.5,1,0.5,0.5,0.5,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1]
recall
0.875 [1,1,1,0.5,1,1,1,1,0.5,1,1,1,1,1,1,1,1,0,1,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,0,0.5,1,0,1,1,1,1,1,1,1,1,1,0.5,1,1,0.5,0.5,0,1,0,1,1,0.5,1,1,1,1,1,0.5,1,1,1,1,0,0.5,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1]
recall
0.8125 [1,1,1,1,1,1,1,1,0.5,0,1,1,1,0.5,1,1,1,0,0,1,1,1,1,1,1,0,0,1,0.5,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,0.5,1,0.5,1,1,1,1,1,0.5,0.5,1,0,1,1,1,0,1,0.5,1,1,0,0.5,0.5,0.5,0.5,1,1,1,1,1,0,1,0,1,1,1,0.5,1,1,1,1,1,0.5,1,1,1,0.5,1,1]
relative_absolute_error
0.17045454545454522
relative_absolute_error
0.1641414141414139
relative_absolute_error
0.12626262626262608
relative_absolute_error
0.17045454545454522
relative_absolute_error
0.17045454545454522
relative_absolute_error
0.1641414141414139
relative_absolute_error
0.1515151515151513
relative_absolute_error
0.1515151515151513
relative_absolute_error
0.12626262626262608
relative_absolute_error
0.18939393939393911
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
0.058094750193111264
root_mean_squared_error
0.0570087712549569
root_mean_squared_error
0.05
root_mean_squared_error
0.058094750193111264
root_mean_squared_error
0.058094750193111264
root_mean_squared_error
0.0570087712549569
root_mean_squared_error
0.05477225575051662
root_mean_squared_error
0.05477225575051662
root_mean_squared_error
0.05
root_mean_squared_error
0.061237243569579464
root_relative_squared_error
0.5838742081211419
root_relative_squared_error
0.5729597091269403
root_relative_squared_error
0.5025189076296057
root_relative_squared_error
0.5838742081211419
root_relative_squared_error
0.5838742081211419
root_relative_squared_error
0.5729597091269403
root_relative_squared_error
0.5504818825631801
root_relative_squared_error
0.5504818825631801
root_relative_squared_error
0.5025189076296057
root_relative_squared_error
0.6154574548966634
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
638.456731000133
usercpu_time_millis
651.5611680000575
usercpu_time_millis
634.927016000006
usercpu_time_millis
642.9227910000463
usercpu_time_millis
660.475910999935
usercpu_time_millis
659.1885289999482
usercpu_time_millis
645.3607160000274
usercpu_time_millis
665.58395200002
usercpu_time_millis
649.9334110000063
usercpu_time_millis
644.3683219999912
usercpu_time_millis_testing
53.784304000032535
usercpu_time_millis_testing
57.93827499996951
usercpu_time_millis_testing
53.06515400002354
usercpu_time_millis_testing
55.38878000004388
usercpu_time_millis_testing
55.78324399994017
usercpu_time_millis_testing
55.75922299999547
usercpu_time_millis_testing
54.635092000012264
usercpu_time_millis_testing
56.01129599995147
usercpu_time_millis_testing
55.62622900004044
usercpu_time_millis_testing
55.120883999961734
usercpu_time_millis_training
584.6724270001005
usercpu_time_millis_training
593.622893000088
usercpu_time_millis_training
581.8618619999825
usercpu_time_millis_training
587.5340110000025
usercpu_time_millis_training
604.6926669999948
usercpu_time_millis_training
603.4293059999527
usercpu_time_millis_training
590.7256240000152
usercpu_time_millis_training
609.5726560000685
usercpu_time_millis_training
594.3071819999659
usercpu_time_millis_training
589.2474380000294