8958515
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)
6894121
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
23.775330431771728
7650
cache_size
200
7650
class_weight
null
7650
coef0
0.4785696743411747
7650
decision_function_shape
"ovr"
7650
degree
3
7650
gamma
0.011959112487787894
7650
kernel
"rbf"
7650
max_iter
-1
7650
probability
false
7650
random_state
1
7650
shrinking
true
7650
tol
0.0008208781528809752
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
18832294
description
https://api.openml.org/data/download/18832294/description.xml
-1
18832295
predictions
https://api.openml.org/data/download/18832295/predictions.arff
area_under_roc_curve
0.9226641414141414 [0.842487,0.96875,1,1,0.96875,0.936553,0.999684,1,0.905934,0.96875,0.967803,0.937184,1,0.874684,1,0.96875,1,0.84154,0.744949,0.621528,0.874053,0.96875,0.998737,1,0.937184,0.684343,0.810606,0.936553,0.9375,1,0.999684,1,0.999369,0.747475,0.937184,0.936869,0.716856,0.716856,0.968119,1,0.935922,0.968434,1,0.936869,0.968434,0.96875,0.937184,0.968119,0.873422,0.936553,0.904672,0.905619,0.937184,0.842487,0.874053,0.841225,1,0.968434,0.903093,0.904987,0.968119,0.968434,0.874053,0.999053,0.999369,0.810922,0.71654,1,0.905619,0.873422,0.905303,0.9375,0.90404,0.96875,0.936869,0.96875,0.968434,0.842172,1,1,0.905934,0.936553,0.874684,0.717487,0.905303,1,1,0.935922,0.9375,1,0.937184,0.999684,0.967803,0.936869,0.96875,0.936869,0.905303,0.905303,0.717803,0.937184]
average_cost
0
f_measure
0.8468469414460382 [0.709677,0.967742,1,1,0.967742,0.848485,0.969697,1,0.866667,0.967742,0.882353,0.903226,1,0.827586,1,0.967742,1,0.647059,0.4,0.258065,0.774194,0.967742,0.888889,1,0.903226,0.375,0.625,0.848485,0.933333,1,0.969697,1,0.941176,0.5,0.903226,0.875,0.482759,0.482759,0.909091,1,0.8,0.9375,1,0.875,0.9375,0.967742,0.903226,0.909091,0.727273,0.848485,0.764706,0.83871,0.903226,0.709677,0.774194,0.628571,1,0.9375,0.666667,0.787879,0.909091,0.9375,0.774194,0.914286,0.941176,0.645161,0.466667,1,0.83871,0.727273,0.8125,0.933333,0.722222,0.967742,0.875,0.967742,0.9375,0.6875,1,1,0.866667,0.848485,0.827586,0.518519,0.8125,1,1,0.8,0.933333,1,0.903226,0.969697,0.882353,0.875,0.967742,0.875,0.8125,0.8125,0.538462,0.903226]
kappa
0.8453282828282829
kb_relative_information_score
1354.4653113381896
mean_absolute_error
0.0030624999999999897
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
0.8514549189835904 [0.733333,1,1,1,1,0.823529,0.941176,1,0.928571,1,0.833333,0.933333,1,0.923077,1,1,1,0.611111,0.333333,0.266667,0.8,1,0.8,1,0.933333,0.375,0.625,0.823529,1,1,0.941176,1,0.888889,0.5,0.933333,0.875,0.538462,0.538462,0.882353,1,0.736842,0.9375,1,0.875,0.9375,1,0.933333,0.882353,0.705882,0.823529,0.722222,0.866667,0.933333,0.733333,0.8,0.578947,1,0.9375,0.565217,0.764706,0.882353,0.9375,0.8,0.842105,0.888889,0.666667,0.5,1,0.866667,0.705882,0.8125,1,0.65,1,0.875,1,0.9375,0.6875,1,1,0.928571,0.823529,0.923077,0.636364,0.8125,1,1,0.736842,1,1,0.933333,0.941176,0.833333,0.875,1,0.875,0.8125,0.8125,0.7,0.933333]
predictive_accuracy
0.846875
prior_entropy
6.6438561897747395
recall
0.846875 [0.6875,0.9375,1,1,0.9375,0.875,1,1,0.8125,0.9375,0.9375,0.875,1,0.75,1,0.9375,1,0.6875,0.5,0.25,0.75,0.9375,1,1,0.875,0.375,0.625,0.875,0.875,1,1,1,1,0.5,0.875,0.875,0.4375,0.4375,0.9375,1,0.875,0.9375,1,0.875,0.9375,0.9375,0.875,0.9375,0.75,0.875,0.8125,0.8125,0.875,0.6875,0.75,0.6875,1,0.9375,0.8125,0.8125,0.9375,0.9375,0.75,1,1,0.625,0.4375,1,0.8125,0.75,0.8125,0.875,0.8125,0.9375,0.875,0.9375,0.9375,0.6875,1,1,0.8125,0.875,0.75,0.4375,0.8125,1,1,0.875,0.875,1,0.875,1,0.9375,0.875,0.9375,0.875,0.8125,0.8125,0.4375,0.875]
relative_absolute_error
0.15467171717171635
root_mean_prior_squared_error
0.09949874371066209
root_mean_squared_error
0.05533985905294655
root_relative_squared_error
0.5561865103932607
total_cost
0
area_under_roc_curve
0.9211448133110423 [0.996855,0.75,1,1,1,1,1,1,1,1,0.75,1,1,1,1,0.5,1,0.75,0.496835,0.990566,0.5,1,0.996855,1,1,0.743671,0.746835,0.996835,1,1,1,1,0.996835,0.5,1,0.996855,1,0.996855,1,1,0.996855,1,1,1,1,1,1,0.996855,1,0.75,1,1,1,1,0.996855,0.996855,1,1,1,1,1,1,0.75,1,1,1,0.5,1,1,0.5,0.75,1,1,1,1,1,0.75,0.5,1,1,1,1,1,0.996855,1,1,1,0.996835,0.75,1,0.996835,1,1,0.996835,1,0.75,0.496855,0.993671,0.496835,1]
area_under_roc_curve
0.9147559907650663 [1,1,1,1,1,1,0.996835,1,1,1,1,1,1,0.75,1,1,1,0.75,0.746835,0.487421,1,1,0.996855,1,1,0.75,0.493671,1,1,1,1,1,1,0.993671,0.75,0.5,0.496855,0.5,1,1,1,1,1,0.75,1,1,1,1,0.746835,0.996835,0.993671,1,1,0.75,1,0.496855,1,1,0.996855,0.75,1,1,0.75,0.996835,1,0.75,0.75,1,1,1,0.996835,1,1,1,1,1,1,0.993671,1,1,0.75,0.996835,0.996855,0.5,0.746835,1,1,0.996835,0.75,1,1,1,1,0.75,1,1,1,1,0.5,0.496855]
area_under_roc_curve
0.9558355226494705 [1,1,1,1,1,0.996835,1,1,1,1,1,0.75,1,1,1,1,1,0.996835,1,0.5,1,1,1,1,1,0.746835,1,0.996855,1,1,1,1,1,0.75,0.996855,1,0.993711,1,1,1,0.746835,0.5,1,1,0.996835,1,0.75,1,0.75,1,1,1,1,1,1,1,1,1,0.993711,0.746835,1,1,1,1,1,1,1,1,1,0.75,1,1,1,1,0.996855,1,1,0.996835,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,0.75,1,1]
area_under_roc_curve
0.9053220285009151 [0.5,1,1,1,0.75,0.75,1,1,0.746835,1,1,0.75,1,0.75,1,1,1,0.743671,0.493711,0.75,1,1,0.996835,1,0.5,0.5,1,1,1,1,1,1,1,0.746835,1,1,1,0.496855,1,1,0.996835,0.996855,1,1,1,1,1,1,0.996835,1,0.996835,1,1,0.75,1,0.993671,1,1,0.996855,1,0.996855,1,1,1,1,0.496835,0.490506,1,1,0.743671,0.5,1,0.990566,1,0.996855,1,1,0.75,1,1,1,1,0.75,0.75,0.5,1,1,1,1,1,0.75,1,0.996855,1,1,0.996855,0.75,0.996835,0.996855,0.75]
area_under_roc_curve
0.9147161850171164 [0.746835,1,1,1,1,0.75,1,1,1,1,0.996835,1,1,0.5,1,1,1,0.746835,0.987421,0.746835,0.75,1,1,1,1,0.990506,1,1,1,1,1,1,1,0.496835,1,1,0.496835,0.5,1,1,0.746835,1,1,0.5,1,1,1,1,1,1,0.496855,0.496855,0.75,0.996855,0.496835,0.5,1,0.996835,0.993671,1,1,1,0.5,1,1,1,1,1,0.75,0.996835,0.996835,1,1,1,0.75,1,0.996835,0.996835,1,1,1,1,1,0.75,0.996855,1,1,1,1,1,1,1,1,1,0.75,1,0.996835,1,0.5,1]
area_under_roc_curve
0.921065201815142 [0.75,1,1,1,1,1,1,1,1,0.75,1,0.996835,1,1,1,1,1,1,0.996855,0.5,0.75,0.75,0.996835,1,0.996835,0.743671,0.746835,0.5,1,1,1,1,1,0.746835,1,0.75,0.75,0.743671,1,1,0.996835,1,1,0.996855,1,1,1,1,0.75,0.75,1,1,1,0.993711,0.996835,0.993671,1,1,0.75,0.996855,1,0.75,0.996855,1,1,0.75,1,1,0.746835,1,1,1,0.996855,1,0.75,1,1,0.75,1,1,0.996855,0.746835,0.75,0.746835,1,1,1,0.996855,1,1,1,1,1,1,1,1,1,1,0.5,1]
area_under_roc_curve
0.9273545099912427 [1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.743671,0.5,0.993671,1,1,1,1,0.5,0.496855,0.75,1,1,0.996835,1,1,0.996855,1,1,0.496835,0.746835,0.993671,1,1,1,1,1,0.5,0.75,0.75,0.996835,0.996855,0.996855,1,1,0.996835,0.5,1,0.75,1,1,0.5,1,0.996835,0.996835,0.996855,0.996835,1,0.496855,0.996855,1,1,1,1,1,0.996835,1,1,1,1,1,1,1,0.75,1,1,0.996835,1,1,1,0.5,1,1,1,1,0.75,1,1,0.75,1,1,0.5,1]
area_under_roc_curve
0.9273943157391926 [0.75,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.996855,0.984177,0.5,0.75,1,1,1,0.75,0.5,1,1,0.5,1,1,1,0.996855,1,1,1,0.5,0.746835,1,1,1,1,1,1,1,1,1,0.75,0.996855,1,0.996855,0.75,0.75,0.996855,1,0.746835,1,1,0.996835,0.993711,1,1,1,1,1,0.496855,0.5,1,1,0.746835,1,1,0.996835,1,1,1,1,0.5,1,1,0.75,1,0.5,0.75,0.75,1,1,0.996855,1,1,1,1,0.993671,1,1,0.996835,1,1,0.996835,1]
area_under_roc_curve
0.9369078894992438 [0.996855,1,1,1,1,0.996855,1,1,0.75,1,1,1,1,1,1,1,1,0.493711,0.75,0.496855,0.996835,1,1,1,1,0.5,0.996855,1,1,1,1,1,1,0.996855,1,1,1,0.5,0.75,1,1,1,1,0.996835,1,1,0.996855,1,0.5,1,0.75,0.996835,1,0.75,0.75,1,1,0.5,0.993671,1,1,1,1,0.996835,1,1,0.743671,1,0.996835,1,0.996855,0.5,0.75,1,1,1,1,0.996855,1,1,1,1,1,0.5,1,1,1,1,1,1,0.75,1,1,0.996835,1,1,0.5,1,0.75,1]
area_under_roc_curve
0.9022967916567153 [0.996855,1,1,1,1,0.996855,1,1,0.75,1,0.993711,1,1,0.746835,1,1,1,1,0.5,0.993711,1,1,1,1,1,0.493711,0.5,0.996835,0.75,1,1,1,1,0.496855,0.75,0.996835,0.746835,1,1,1,1,1,1,1,1,1,1,1,0.996855,0.996855,0.75,0.75,1,0.75,0.75,0.996855,1,1,0.996835,0.75,0.75,1,0.746835,1,0.993711,0.993711,0.496835,1,0.75,0.996855,1,0.5,0.496835,0.75,1,0.75,1,1,1,1,1,0.496855,1,0.496855,0.996835,1,1,0.746835,1,1,1,0.996835,1,0.75,1,1,0.996855,0.5,1,1]
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
0.8420782502270125
kappa
0.8294040990403981
kappa
0.9115533443891652
kappa
0.810493900272415
kappa
0.829397361977727
kappa
0.8420657796027955
kappa
0.854666087437305
kappa
0.8546833043752962
kappa
0.873627675539057
kappa
0.8042156785347754
kb_relative_information_score
134.94543993246936
kb_relative_information_score
132.94107512706694
kb_relative_information_score
145.9694463621828
kb_relative_information_score
129.93452791896325
kb_relative_information_score
132.94107512706694
kb_relative_information_score
134.94543993246936
kb_relative_information_score
136.9498047378718
kb_relative_information_score
136.9498047378718
kb_relative_information_score
139.95635194597548
kb_relative_information_score
128.93234551626202
mean_absolute_error
0.0031250000000000006
mean_absolute_error
0.003375000000000001
mean_absolute_error
0.0017499999999999998
mean_absolute_error
0.003750000000000001
mean_absolute_error
0.003375000000000001
mean_absolute_error
0.0031250000000000006
mean_absolute_error
0.002875000000000001
mean_absolute_error
0.002875000000000001
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
0.84375
predictive_accuracy
0.83125
predictive_accuracy
0.9125
predictive_accuracy
0.8125
predictive_accuracy
0.83125
predictive_accuracy
0.84375
predictive_accuracy
0.85625
predictive_accuracy
0.85625
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
0.84375 [1,0.5,1,1,1,1,1,1,1,1,0.5,1,1,1,1,0,1,0.5,0,1,0,1,1,1,1,0.5,0.5,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0,1,1,0,0.5,1,1,1,1,1,0.5,0,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,0.5,0,1,0,1]
recall
0.83125 [1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0.5,0.5,0,1,1,1,1,1,0.5,0,1,1,1,1,1,1,1,0.5,0,0,0,1,1,1,1,1,0.5,1,1,1,1,0.5,1,1,1,1,0.5,1,0,1,1,1,0.5,1,1,0.5,1,1,0.5,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,0,0.5,1,1,1,0.5,1,1,1,1,0.5,1,1,1,1,0,0]
recall
0.9125 [1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,0,1,1,1,1,1,0.5,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,0.5,0,1,1,1,1,0.5,1,0.5,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1]
recall
0.8125 [0,1,1,1,0.5,0.5,1,1,0.5,1,1,0.5,1,0.5,1,1,1,0.5,0,0.5,1,1,1,1,0,0,1,1,1,1,1,1,1,0.5,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,0.5,0,1,1,1,1,1,1,0.5,1,1,1,1,0.5,0.5,0,1,1,1,1,1,0.5,1,1,1,1,1,0.5,1,1,0.5]
recall
0.83125 [0.5,1,1,1,1,0.5,1,1,1,1,1,1,1,0,1,1,1,0.5,1,0.5,0.5,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,0,0,1,1,0.5,1,1,0,1,1,1,1,1,1,0,0,0.5,1,0,0,1,1,1,1,1,1,0,1,1,1,1,1,0.5,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0,1]
recall
0.84375 [0.5,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,0,0.5,0.5,1,1,1,0.5,0.5,0,1,1,1,1,1,0.5,1,0.5,0.5,0.5,1,1,1,1,1,1,1,1,1,1,0.5,0.5,1,1,1,1,1,1,1,1,0.5,1,1,0.5,1,1,1,0.5,1,1,0.5,1,1,1,1,1,0.5,1,1,0.5,1,1,1,0.5,0.5,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1]
recall
0.85625 [1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,0,1,1,1,1,1,0,0,0.5,1,1,1,1,1,1,1,1,0,0.5,1,1,1,1,1,1,0,0.5,0.5,1,1,1,1,1,1,0,1,0.5,1,1,0,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,0,1,1,1,1,0.5,1,1,0.5,1,1,0,1]
recall
0.85625 [0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0.5,1,1,1,0.5,0,1,1,0,1,1,1,1,1,1,1,0,0.5,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0.5,0.5,1,1,0.5,1,1,1,1,1,1,1,1,1,0,0,1,1,0.5,1,1,1,1,1,1,1,0,1,1,0.5,1,0,0.5,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1]
recall
0.875 [1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,0,0.5,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,0,0.5,1,1,1,1,1,1,1,1,1,0,1,0.5,1,1,0.5,0.5,1,1,0,1,1,1,1,1,1,1,1,0.5,1,1,1,1,0,0.5,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0.5,1,1,1,1,1,0,1,0.5,1]
recall
0.80625 [1,1,1,1,1,1,1,1,0.5,1,1,1,1,0.5,1,1,1,1,0,1,1,1,1,1,1,0,0,1,0.5,1,1,1,1,0,0.5,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,0.5,1,0.5,0.5,1,1,1,1,0.5,0.5,1,0.5,1,1,1,0,1,0.5,1,1,0,0,0.5,1,0.5,1,1,1,1,1,0,1,0,1,1,1,0.5,1,1,1,1,1,0.5,1,1,1,0,1,1]
relative_absolute_error
0.1578282828282826
relative_absolute_error
0.17045454545454522
relative_absolute_error
0.08838383838383823
relative_absolute_error
0.18939393939393911
relative_absolute_error
0.17045454545454522
relative_absolute_error
0.1578282828282826
relative_absolute_error
0.14520202020202
relative_absolute_error
0.14520202020202
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
0.05590169943749475
root_mean_squared_error
0.058094750193111264
root_mean_squared_error
0.04183300132670378
root_mean_squared_error
0.061237243569579464
root_mean_squared_error
0.058094750193111264
root_mean_squared_error
0.05590169943749475
root_mean_squared_error
0.05361902647381805
root_mean_squared_error
0.05361902647381805
root_mean_squared_error
0.05
root_mean_squared_error
0.06224949798994367
root_relative_squared_error
0.5618332187193681
root_relative_squared_error
0.5838742081211419
root_relative_squared_error
0.4204374825912606
root_relative_squared_error
0.6154574548966634
root_relative_squared_error
0.5838742081211419
root_relative_squared_error
0.5618332187193681
root_relative_squared_error
0.5388914922357191
root_relative_squared_error
0.5388914922357191
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
586.4865089999967
usercpu_time_millis
583.559169000182
usercpu_time_millis
575.6807370000843
usercpu_time_millis
582.2157919999427
usercpu_time_millis
588.3162549998815
usercpu_time_millis
613.1356100001994
usercpu_time_millis
580.2620610002123
usercpu_time_millis
569.6479150001323
usercpu_time_millis
575.3605959998822
usercpu_time_millis
569.4337940001333
usercpu_time_millis_testing
58.12841500005561
usercpu_time_millis_testing
55.81786700008706
usercpu_time_millis_testing
56.394404000002396
usercpu_time_millis_testing
55.816458999970564
usercpu_time_millis_testing
55.850974999884784
usercpu_time_millis_testing
54.38182400007463
usercpu_time_millis_testing
54.76869200015244
usercpu_time_millis_testing
55.00793100009105
usercpu_time_millis_testing
55.16264199991383
usercpu_time_millis_testing
54.600353000068935
usercpu_time_millis_training
528.358093999941
usercpu_time_millis_training
527.741302000095
usercpu_time_millis_training
519.2863330000819
usercpu_time_millis_training
526.3993329999721
usercpu_time_millis_training
532.4652799999967
usercpu_time_millis_training
558.7537860001248
usercpu_time_millis_training
525.4933690000598
usercpu_time_millis_training
514.6399840000413
usercpu_time_millis_training
520.1979539999684
usercpu_time_millis_training
514.8334410000643