8959021
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)
6894625
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
15.226343639972196
7650
cache_size
200
7650
class_weight
null
7650
coef0
0.4464248819216967
7650
decision_function_shape
"ovr"
7650
degree
3
7650
gamma
0.008007945520279747
7650
kernel
"rbf"
7650
max_iter
-1
7650
probability
false
7650
random_state
1
7650
shrinking
false
7650
tol
0.0006105194828685501
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
18833298
description
https://api.openml.org/data/download/18833298/description.xml
-1
18833299
predictions
https://api.openml.org/data/download/18833299/predictions.arff
area_under_roc_curve
0.9217171717171717 [0.842803,0.96875,1,1,0.96875,0.874369,0.999684,1,0.936553,0.96875,0.967803,0.937184,1,0.843434,1,0.96875,1,0.809659,0.714331,0.590909,0.842803,0.96875,0.998737,1,0.937184,0.746843,0.715909,0.936553,0.9375,1,0.999684,1,0.999369,0.809975,0.937184,0.968119,0.716225,0.71654,0.999369,1,0.904356,0.968434,1,0.936869,0.968434,0.96875,0.9375,0.968119,0.904672,0.936553,0.904672,0.905619,0.937184,0.842487,0.874053,0.81029,1,0.968434,0.87279,0.873737,0.968119,0.968434,0.874053,0.967803,0.999369,0.810606,0.716225,1,0.905619,0.873422,0.905303,0.9375,0.904672,0.96875,0.936869,0.96875,0.968434,0.84154,1,1,0.905934,0.937184,0.874684,0.841856,0.905303,1,1,0.935922,0.9375,1,0.937184,0.999369,0.968119,0.936869,0.96875,0.936869,0.905303,0.905303,0.717487,0.937184]
average_cost
0
f_measure
0.8451829695386914 [0.733333,0.967742,1,1,0.967742,0.8,0.969697,1,0.848485,0.967742,0.882353,0.903226,1,0.785714,1,0.967742,1,0.571429,0.378378,0.214286,0.733333,0.967742,0.888889,1,0.903226,0.470588,0.4375,0.848485,0.933333,1,0.969697,1,0.941176,0.588235,0.903226,0.909091,0.451613,0.466667,0.941176,1,0.742857,0.9375,1,0.875,0.9375,0.967742,0.933333,0.909091,0.764706,0.848485,0.764706,0.83871,0.903226,0.709677,0.774194,0.606061,1,0.9375,0.685714,0.75,0.909091,0.9375,0.774194,0.882353,0.941176,0.625,0.451613,1,0.83871,0.727273,0.8125,0.933333,0.764706,0.967742,0.875,0.967742,0.9375,0.647059,1,1,0.866667,0.903226,0.827586,0.666667,0.8125,1,1,0.8,0.933333,1,0.903226,0.941176,0.909091,0.875,0.967742,0.875,0.8125,0.8125,0.518519,0.903226]
kappa
0.8434343434343434
kb_relative_information_score
1351.4587641300861
mean_absolute_error
0.003099999999999989
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
0.8490239353010248 [0.785714,1,1,1,1,0.857143,0.941176,1,0.823529,1,0.833333,0.933333,1,0.916667,1,1,1,0.526316,0.333333,0.25,0.785714,1,0.8,1,0.933333,0.444444,0.4375,0.823529,1,1,0.941176,1,0.888889,0.555556,0.933333,0.882353,0.466667,0.5,0.888889,1,0.684211,0.9375,1,0.875,0.9375,1,1,0.882353,0.722222,0.823529,0.722222,0.866667,0.933333,0.733333,0.8,0.588235,1,0.9375,0.631579,0.75,0.882353,0.9375,0.8,0.833333,0.888889,0.625,0.466667,1,0.866667,0.705882,0.8125,1,0.722222,1,0.875,1,0.9375,0.611111,1,1,0.928571,0.933333,0.923077,0.647059,0.8125,1,1,0.736842,1,1,0.933333,0.888889,0.882353,0.875,1,0.875,0.8125,0.8125,0.636364,0.933333]
predictive_accuracy
0.845
prior_entropy
6.6438561897747395
recall
0.845 [0.6875,0.9375,1,1,0.9375,0.75,1,1,0.875,0.9375,0.9375,0.875,1,0.6875,1,0.9375,1,0.625,0.4375,0.1875,0.6875,0.9375,1,1,0.875,0.5,0.4375,0.875,0.875,1,1,1,1,0.625,0.875,0.9375,0.4375,0.4375,1,1,0.8125,0.9375,1,0.875,0.9375,0.9375,0.875,0.9375,0.8125,0.875,0.8125,0.8125,0.875,0.6875,0.75,0.625,1,0.9375,0.75,0.75,0.9375,0.9375,0.75,0.9375,1,0.625,0.4375,1,0.8125,0.75,0.8125,0.875,0.8125,0.9375,0.875,0.9375,0.9375,0.6875,1,1,0.8125,0.875,0.75,0.6875,0.8125,1,1,0.875,0.875,1,0.875,1,0.9375,0.875,0.9375,0.875,0.8125,0.8125,0.4375,0.875]
relative_absolute_error
0.15656565656565571
root_mean_prior_squared_error
0.09949874371066209
root_mean_squared_error
0.05567764362830012
root_relative_squared_error
0.5595813731096768
total_cost
0
area_under_roc_curve
0.9116113366770163 [1,0.75,1,1,1,1,1,1,1,1,0.75,1,1,1,1,0.5,1,0.75,0.496835,0.493711,0.5,1,0.996855,1,1,0.743671,0.743671,0.996835,1,1,1,1,0.996835,0.5,1,0.996855,1,0.996855,1,1,0.496855,1,1,1,1,1,1,0.996855,1,0.75,1,1,1,1,0.996855,0.996855,1,1,1,1,1,1,0.75,1,1,0.996835,0.496835,1,1,0.5,0.75,1,1,1,1,1,0.75,0.493671,1,1,1,1,0.5,0.996855,1,1,1,0.996835,0.75,1,0.996835,1,1,0.996835,1,0.75,0.496855,0.993671,0.496835,1]
area_under_roc_curve
0.9241899530292172 [1,1,1,1,1,1,0.996835,1,1,1,1,1,1,0.75,1,1,1,0.746835,0.75,0.493711,1,1,0.996855,1,1,0.746835,0.490506,1,1,1,1,1,1,0.993671,0.75,1,0.496855,0.5,1,1,1,1,1,0.75,1,1,1,1,0.996835,0.996835,0.996835,1,1,0.75,1,0.496855,1,1,1,0.75,1,1,1,0.996835,1,0.75,0.75,1,1,1,0.996835,1,1,1,1,1,1,0.993671,1,1,0.75,1,0.996855,1,0.746835,1,1,0.996835,0.75,1,0.75,1,1,0.75,1,1,1,1,0.5,0.496855]
area_under_roc_curve
0.9432171005493191 [1,1,1,1,1,0.996835,1,1,1,1,1,0.75,1,0.75,1,1,1,0.996835,1,0.5,1,1,1,1,1,0.746835,1,0.996855,1,1,1,1,1,0.5,0.996855,0.996855,0.993711,1,1,1,0.743671,0.5,1,1,0.996835,1,0.75,1,0.75,1,0.996835,1,1,1,1,1,1,1,0.993711,0.496835,1,1,1,0.5,1,1,1,1,1,0.75,1,1,1,1,0.996855,1,1,0.996835,1,1,1,1,1,0.5,1,1,1,1,1,1,1,0.996855,1,1,1,1,1,0.75,1,1]
area_under_roc_curve
0.9147957965130162 [0.5,1,1,1,0.75,0.75,1,1,0.746835,1,1,0.75,1,0.75,1,1,1,0.743671,0.493711,0.75,1,1,0.996835,1,0.5,1,1,1,1,1,1,1,1,0.75,1,1,0.996855,0.5,1,1,0.996835,0.996855,1,1,1,1,1,1,0.996835,1,0.996835,1,1,0.75,1,0.993671,1,1,0.996855,1,0.996855,1,1,1,1,0.496835,0.493671,1,1,0.743671,0.5,1,0.993711,1,0.996855,1,1,0.75,1,1,1,1,0.75,0.75,0.5,1,1,1,1,1,1,1,0.996855,1,1,0.996855,0.75,0.996835,0.996855,0.75]
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
0.921085104689117 [0.75,1,1,1,1,0.75,1,1,0.996855,0.75,1,0.996835,1,1,1,1,1,0.996835,0.996855,0.5,0.75,0.75,0.996835,1,0.996835,0.746835,0.746835,0.5,1,1,1,1,1,0.996835,1,0.75,0.75,0.490506,1,1,0.996835,1,1,0.996855,1,1,1,1,0.75,0.75,1,1,1,0.993711,0.996835,0.996835,1,1,0.75,0.996855,1,0.75,0.996855,1,1,0.75,0.996855,1,0.746835,1,1,1,1,1,0.75,1,1,0.75,1,1,0.996855,0.75,0.75,0.996835,1,1,1,0.996855,1,1,1,1,1,1,1,1,1,1,0.5,1]
area_under_roc_curve
0.9179205477270918 [1,1,1,1,1,0.75,1,1,0.996855,1,1,1,1,1,1,1,1,1,0.496835,0.5,0.743671,1,1,1,1,0.5,0.493711,0.75,1,1,0.996835,1,1,0.993711,1,1,0.493671,0.746835,0.993671,1,1,1,1,1,0.5,0.75,0.75,0.996835,0.996855,0.996855,1,1,0.996835,0.5,1,0.75,1,1,0.5,1,0.996835,0.996835,0.996855,0.996835,1,0.496855,0.996855,1,1,1,1,1,0.996835,1,1,1,1,1,1,1,0.75,1,1,0.996835,1,1,1,0.5,1,1,1,1,0.75,1,1,0.75,1,1,0.5,1]
area_under_roc_curve
0.9337234296632435 [0.75,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.996855,0.984177,0.5,0.75,1,1,1,0.75,0.5,1,1,0.5,1,1,1,0.996855,1,1,1,0.5,0.746835,1,1,1,1,1,1,1,1,1,0.75,0.996855,1,0.996855,0.75,0.75,0.996855,1,0.746835,1,1,1,0.993711,1,1,1,1,1,0.496855,0.5,1,1,0.746835,1,1,0.996835,1,1,1,1,0.5,1,1,0.75,1,0.75,1,0.75,1,1,0.996855,1,1,1,1,0.996835,1,1,0.996835,1,1,0.996835,1]
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
0.9022967916567153 [0.996855,1,1,1,1,0.996855,1,1,0.75,1,0.993711,1,1,0.746835,1,1,1,1,0.5,0.993711,1,1,1,1,1,0.493711,0.5,0.996835,0.75,1,1,1,1,0.996855,0.75,1,0.746835,1,1,1,1,1,1,1,1,1,1,1,0.996855,0.996855,0.75,0.75,1,0.75,0.75,0.996855,1,1,0.993671,0.75,0.75,1,0.496835,1,0.993711,0.993711,0.496835,1,0.75,0.996855,1,0.5,0.496835,0.75,1,0.75,1,1,1,1,1,0.496855,1,0.496855,0.996835,1,1,0.746835,1,1,1,0.996835,1,0.75,1,1,0.996855,0.5,1,1]
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
0.8230927183699257
kappa
0.8483532106468683
kappa
0.8862873613140126
kappa
0.8294377763739735
kappa
0.8230857323381905
kappa
0.8420720151610865
kappa
0.8357289527720739
kappa
0.8673195387774444
kappa
0.8736176935229067
kappa
0.8042234063548451
kb_relative_information_score
131.9388927243657
kb_relative_information_score
135.9476223351706
kb_relative_information_score
141.9607167513779
kb_relative_information_score
132.94107512706694
kb_relative_information_score
131.9388927243657
kb_relative_information_score
134.94543993246936
kb_relative_information_score
133.94325752976815
kb_relative_information_score
138.95416954327425
kb_relative_information_score
139.95635194597548
kb_relative_information_score
128.93234551626202
mean_absolute_error
0.003500000000000001
mean_absolute_error
0.003000000000000001
mean_absolute_error
0.0022500000000000003
mean_absolute_error
0.003375000000000001
mean_absolute_error
0.003500000000000001
mean_absolute_error
0.0031250000000000006
mean_absolute_error
0.0032500000000000007
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
0.825
predictive_accuracy
0.85
predictive_accuracy
0.8875
predictive_accuracy
0.83125
predictive_accuracy
0.825
predictive_accuracy
0.84375
predictive_accuracy
0.8375
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
0.825 [1,0.5,1,1,1,1,1,1,1,1,0.5,1,1,1,1,0,1,0.5,0,0,0,1,1,1,1,0.5,0.5,1,1,1,1,1,1,0,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0,1,1,0,0.5,1,1,1,1,1,0.5,0,1,1,1,1,0,1,1,1,1,1,0.5,1,1,1,1,1,1,0.5,0,1,0,1]
recall
0.85 [1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0.5,0.5,0,1,1,1,1,1,0.5,0,1,1,1,1,1,1,1,0.5,1,0,0,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,0.5,1,0,1,1,1,0.5,1,1,1,1,1,0.5,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0.5,1,1,1,0.5,1,0.5,1,1,0.5,1,1,1,1,0,0]
recall
0.8875 [1,1,1,1,1,1,1,1,1,1,1,0.5,1,0.5,1,1,1,1,1,0,1,1,1,1,1,0.5,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0.5,0,1,1,1,1,0.5,1,0.5,1,1,1,1,1,1,1,1,1,1,0,1,1,1,0,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1]
recall
0.83125 [0,1,1,1,0.5,0.5,1,1,0.5,1,1,0.5,1,0.5,1,1,1,0.5,0,0.5,1,1,1,1,0,1,1,1,1,1,1,1,1,0.5,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,0.5,0,1,1,1,1,1,1,0.5,1,1,1,1,0.5,0.5,0,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,0.5]
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
0.84375 [0.5,1,1,1,1,0.5,1,1,1,0.5,1,1,1,1,1,1,1,1,1,0,0.5,0.5,1,1,1,0.5,0.5,0,1,1,1,1,1,1,1,0.5,0.5,0,1,1,1,1,1,1,1,1,1,1,0.5,0.5,1,1,1,1,1,1,1,1,0.5,1,1,0.5,1,1,1,0.5,1,1,0.5,1,1,1,1,1,0.5,1,1,0.5,1,1,1,0.5,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1]
recall
0.8375 [1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0.5,1,1,1,1,0,0,0.5,1,1,1,1,1,1,1,1,0,0.5,1,1,1,1,1,1,0,0.5,0.5,1,1,1,1,1,1,0,1,0.5,1,1,0,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,0,1,1,1,1,0.5,1,1,0.5,1,1,0,1]
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
0.17676767676767655
relative_absolute_error
0.1515151515151513
relative_absolute_error
0.11363636363636348
relative_absolute_error
0.17045454545454522
relative_absolute_error
0.17676767676767655
relative_absolute_error
0.1578282828282826
relative_absolute_error
0.1641414141414139
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
0.05916079783099617
root_mean_squared_error
0.05477225575051662
root_mean_squared_error
0.047434164902525694
root_mean_squared_error
0.058094750193111264
root_mean_squared_error
0.05916079783099617
root_mean_squared_error
0.05590169943749475
root_mean_squared_error
0.0570087712549569
root_mean_squared_error
0.051234753829797995
root_mean_squared_error
0.05
root_mean_squared_error
0.06224949798994367
root_relative_squared_error
0.5945883900105629
root_relative_squared_error
0.5504818825631801
root_relative_squared_error
0.4767312946227959
root_relative_squared_error
0.5838742081211419
root_relative_squared_error
0.5945883900105629
root_relative_squared_error
0.5618332187193681
root_relative_squared_error
0.5729597091269403
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
469.77259699997376
usercpu_time_millis
477.58256399993115
usercpu_time_millis
474.81244499999775
usercpu_time_millis
480.7856989998527
usercpu_time_millis
488.32102999995186
usercpu_time_millis
472.2232780002287
usercpu_time_millis
484.3912750002346
usercpu_time_millis
478.10306099995614
usercpu_time_millis
489.6718110001075
usercpu_time_millis
488.24846000002253
usercpu_time_millis_testing
53.98987900002794
usercpu_time_millis_testing
56.38235999981589
usercpu_time_millis_testing
53.24294599995483
usercpu_time_millis_testing
55.39799799998946
usercpu_time_millis_testing
57.822310000119614
usercpu_time_millis_testing
53.951894000192624
usercpu_time_millis_testing
55.81965300007141
usercpu_time_millis_testing
54.81100299994068
usercpu_time_millis_testing
55.73941400007243
usercpu_time_millis_testing
55.7208239999909
usercpu_time_millis_training
415.7827179999458
usercpu_time_millis_training
421.20020400011526
usercpu_time_millis_training
421.5694990000429
usercpu_time_millis_training
425.3877009998632
usercpu_time_millis_training
430.49871999983225
usercpu_time_millis_training
418.27138400003605
usercpu_time_millis_training
428.5716220001632
usercpu_time_millis_training
423.29205800001546
usercpu_time_millis_training
433.93239700003505
usercpu_time_millis_training
432.52763600003163