8956150
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)
6891766
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
3074.23836316206
7650
cache_size
200
7650
class_weight
null
7650
coef0
0.8293006657184324
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decision_function_shape
"ovr"
7650
degree
3
7650
gamma
0.9509306147786704
7650
kernel
"rbf"
7650
max_iter
-1
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probability
false
7650
random_state
1
7650
shrinking
false
7650
tol
0.02075881998712856
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
18827588
description
https://api.openml.org/data/download/18827588/description.xml
-1
18827589
predictions
https://api.openml.org/data/download/18827589/predictions.arff
area_under_roc_curve
0.5363005050505051 [0.562184,0.5,0.53125,0.453914,0.5,0.476326,0.625,0.53125,0.562184,0.5625,0.5,0.59375,0.53125,0.5625,0.457386,0.53125,0.5625,0.52904,0.558712,0.498106,0.530934,0.5,0.5625,0.53125,0.561869,0.499369,0.560606,0.530934,0.53125,0.5625,0.5,0.53125,0.5625,0.560922,0.529356,0.530619,0.530303,0.530619,0.59375,0.53125,0.530934,0.53125,0.53125,0.5625,0.53125,0.53125,0.5625,0.53125,0.498422,0.53125,0.530934,0.530934,0.593434,0.529987,0.499684,0.499369,0.5,0.53125,0.530303,0.592172,0.59375,0.5625,0.561869,0.5625,0.5,0.530934,0.498422,0.59375,0.53125,0.5625,0.499684,0.5625,0.529672,0.5,0.5,0.53125,0.5625,0.560922,0.5,0.5,0.562184,0.499684,0.5,0.530934,0.53125,0.53125,0.5625,0.53125,0.562184,0.530934,0.562184,0.5625,0.5,0.59375,0.5,0.5625,0.561553,0.53125,0.528093,0.561237]
average_cost
0
kappa
0.07260101010101011
kb_relative_information_score
127.79405043190425
mean_absolute_error
0.018362499999999664
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]
predictive_accuracy
0.081875
prior_entropy
6.6438561897747395
recall
0.081875 [0.125,0,0.0625,0.25,0,0.125,0.25,0.0625,0.125,0.125,0,0.1875,0.0625,0.125,0.25,0.0625,0.125,0.0625,0.125,0,0.0625,0,0.125,0.0625,0.125,0,0.125,0.0625,0.0625,0.125,0,0.0625,0.125,0.125,0.0625,0.0625,0.0625,0.0625,0.1875,0.0625,0.0625,0.0625,0.0625,0.125,0.0625,0.0625,0.125,0.0625,0,0.0625,0.0625,0.0625,0.1875,0.0625,0,0,0,0.0625,0.0625,0.1875,0.1875,0.125,0.125,0.125,0,0.0625,0,0.1875,0.0625,0.125,0,0.125,0.0625,0,0,0.0625,0.125,0.125,0,0,0.125,0,0,0.0625,0.0625,0.0625,0.125,0.0625,0.125,0.0625,0.125,0.125,0,0.1875,0,0.125,0.125,0.0625,0.0625,0.125]
relative_absolute_error
0.9273989898989713
root_mean_prior_squared_error
0.09949874371066209
root_mean_squared_error
0.13550830232867528
root_relative_squared_error
1.3619096812189648
total_cost
0
area_under_roc_curve
0.5471698113207546 [0.5,0.5,0.5,0.578616,0.5,0.496855,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.996855,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.493711,1,1,1,0.5,1,0.5,0.5,0.5,0.5,0.5,1,1,0.5,0.5,0.5,0.5,1,0.5,0.496855,0.493711,0.5,1,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.990566]
area_under_roc_curve
0.5345911949685535 [0.5,0.5,0.5,0.553459,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,0.493711,0.5,0.5,1,0.5,0.996855,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5,0.496855,0.496855,0.5,0.5,0.496855,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,1,0.5,0.5,0.5,0.5,0.5,1,1,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5]
area_under_roc_curve
0.5440251572327043 [0.5,0.5,0.5,0.591195,0.5,0.5,1,0.5,0.5,0.75,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.993711,0.5,0.5,0.5,0.5,1,0.496855,0.5,0.5,0.996855,0.5,0.5,0.5,0.5,0.5,0.5,0.496855,1,0.496855,0.496855,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.496855,0.996855,0.5,0.5,0.5,0.5,0.5,0.493711,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.496855,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,1,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,1,0.5,0.5,0.990566,0.5]
area_under_roc_curve
0.5440251572327044 [0.5,0.5,0.5,0.572327,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.496855,0.5,0.496855,0.5,1,0.5,0.5,0.5,1,1,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.996855,0.5,1,1,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.496855,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.996855,0.5,1,0.5,0.5,0.5,1,0.5,0.5,0.487421,0.5]
area_under_roc_curve
0.5188679245283019 [0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,1,0.5,0.5,0.5,0.5,0.5,0.559748,0.5,0.5,0.5,0.487421,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.996855,0.5,0.5,0.5,0.5,0.5,0.5,0.490566,0.5,0.5,0.5,0.5,0.5,0.493711,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.496855,0.5,0.5,0.5,0.5,0.5,0.5,1,0.493711,0.5]
area_under_roc_curve
0.5503144654088051 [0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,1,0.5,0.5,0.5,0.5,0.5,0.597484,0.5,0.5,0.5,0.981132,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.487421,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5,1,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.996855,0.5,0.5,0.496855,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.996855,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.996855,0.5,0.5,0.5,0.5,1,1,1,0.5,0.5,1,0.5,0.5,1,0.5,0.5,0.5,0.5,0.496855,0.5]
area_under_roc_curve
0.5314465408805031 [0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.496855,0.5,0.5,1,0.5,1,0.562893,0.5,1,0.496855,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.496855,1,0.5,0.5,0.5,0.5,0.5,1,0.493711,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.496855,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.996855,0.5,0.5,0.996855,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.996855,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.496855,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5]
area_under_roc_curve
0.5408805031446541 [0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.610063,0.5,0.5,0.493711,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.990566,0.5,0.5,0.5,0.5,1,1,1,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,0.490566,0.5,0.5,0.5,0.5,0.987421,0.5,0.5,0.5,0.5,0.5,0.493711,0.5,0.5,1,0.5,0.5,0.5,0.493711,0.5,0.5,0.5,0.496855,0.5,0.5,0.5,0.5,1,1,0.487421,0.5,0.5,0.5,0.496855,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5]
area_under_roc_curve
0.5471698113207547 [0.996855,0.5,1,0.5,0.5,0.575472,0.5,0.5,0.5,1,0.5,1,0.5,0.5,0.5,0.5,1,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.496855,0.490566,0.5,0.5,1,0.5,0.5,0.5,0.993711,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.496855,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5,1,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0.996855]
area_under_roc_curve
0.5220125786163522 [1,0.5,0.5,0.5,0.5,0.569182,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.487421,0.5,0.487421,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.496855,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,0.496855,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.996855,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.496855,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.990566,0.5,0.5,0.5]
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
0.09433962264150943
kappa
0.0691823899371069
kappa
0.08801446597743623
kappa
0.0880503144654088
kappa
0.03773584905660377
kappa
0.10062893081761005
kappa
0.06289308176100629
kappa
0.08176100628930816
kappa
0.09433962264150943
kappa
0.04402515723270441
kb_relative_information_score
15.685734011023504
kb_relative_information_score
11.677004400218607
kb_relative_information_score
14.683551608322295
kb_relative_information_score
14.683551608322277
kb_relative_information_score
6.666092386712543
kb_relative_information_score
16.687916413724732
kb_relative_information_score
10.6748219975174
kb_relative_information_score
13.681369205621065
kb_relative_information_score
15.685734011023506
kb_relative_information_score
7.668274789413723
mean_absolute_error
0.018000000000000013
mean_absolute_error
0.018500000000000013
mean_absolute_error
0.018125000000000013
mean_absolute_error
0.018125000000000013
mean_absolute_error
0.019125000000000014
mean_absolute_error
0.017875000000000012
mean_absolute_error
0.018625000000000013
mean_absolute_error
0.018250000000000013
mean_absolute_error
0.018000000000000013
mean_absolute_error
0.019000000000000013
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
0.1
predictive_accuracy
0.075
predictive_accuracy
0.09375
predictive_accuracy
0.09375
predictive_accuracy
0.04375
predictive_accuracy
0.10625
predictive_accuracy
0.06875
predictive_accuracy
0.0875
predictive_accuracy
0.1
predictive_accuracy
0.05
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
0.1 [0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,0,1,0,0,0,0,0,1,1,0,0,0,0,1,0,0,0,0,1,0,0,1,0,0,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1]
recall
0.075 [0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,1,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,1,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]
recall
0.09375 [0,0,0,1,0,0,1,0,0,0.5,0,0,1,0,0,0,0,0,1,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,1,0,0,0,0,1,0,0,0,1,0,0,1,0]
recall
0.09375 [0,0,0,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,1,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,1,0,1,1,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,1,0,0,0,1,0,0,0,0]
recall
0.04375 [0,0,0,0,0,0,1,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0]
recall
0.10625 [0,0,0,0,0,0,1,0,1,0,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,1,1,0,0,0,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0,0,0,0,1,1,1,0,0,1,0,0,1,0,0,0,0,0,0]
recall
0.06875 [0,0,0,0,0,0,0,0,0,0,0,1,0,1,1,0,1,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0]
recall
0.0875 [0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,1,1,1,0,0,0,0,0,1,0,0,0,0,1,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,1,0,0,0,0,0,0]
recall
0.1 [1,0,1,0,0,1,0,0,0,1,0,1,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,1,0,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0,0,1]
recall
0.05 [1,0,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0,0,0]
relative_absolute_error
0.9090909090909082
relative_absolute_error
0.9343434343434334
relative_absolute_error
0.9154040404040396
relative_absolute_error
0.9154040404040396
relative_absolute_error
0.96590909090909
relative_absolute_error
0.9027777777777769
relative_absolute_error
0.9406565656565649
relative_absolute_error
0.9217171717171708
relative_absolute_error
0.9090909090909082
relative_absolute_error
0.9595959595959586
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
0.13416407864998742
root_mean_squared_error
0.13601470508735447
root_mean_squared_error
0.13462912017836265
root_mean_squared_error
0.13462912017836265
root_mean_squared_error
0.13829316685939336
root_mean_squared_error
0.13369741957120942
root_mean_squared_error
0.13647344063956185
root_mean_squared_error
0.135092560861063
root_mean_squared_error
0.13416407864998742
root_mean_squared_error
0.13784048752090228
root_relative_squared_error
1.3483997249264836
root_relative_squared_error
1.366999220441207
root_relative_squared_error
1.3530735681433144
root_relative_squared_error
1.3530735681433144
root_relative_squared_error
1.389898622856423
root_relative_squared_error
1.3437096247164246
root_relative_squared_error
1.371609686212929
root_relative_squared_error
1.357731322255748
root_relative_squared_error
1.3483997249264836
root_relative_squared_error
1.3853490243227224
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
678.4705440000067
usercpu_time_millis
676.223068000013
usercpu_time_millis
674.6407870000155
usercpu_time_millis
680.3581580000042
usercpu_time_millis
678.2000129999943
usercpu_time_millis
688.2561339999995
usercpu_time_millis
676.3054280000063
usercpu_time_millis
687.461153000001
usercpu_time_millis
702.4159200000071
usercpu_time_millis
696.0041459999928
usercpu_time_millis_testing
49.603500000003464
usercpu_time_millis_testing
49.34652100000392
usercpu_time_millis_testing
49.777013000010584
usercpu_time_millis_testing
49.7630499999957
usercpu_time_millis_testing
49.44797000000278
usercpu_time_millis_testing
49.18016199999897
usercpu_time_millis_testing
50.115306999998666
usercpu_time_millis_testing
52.123249000004535
usercpu_time_millis_testing
51.94908200000725
usercpu_time_millis_testing
53.10445799999286
usercpu_time_millis_training
628.8670440000033
usercpu_time_millis_training
626.876547000009
usercpu_time_millis_training
624.8637740000049
usercpu_time_millis_training
630.5951080000085
usercpu_time_millis_training
628.7520429999915
usercpu_time_millis_training
639.0759720000005
usercpu_time_millis_training
626.1901210000076
usercpu_time_millis_training
635.3379039999965
usercpu_time_millis_training
650.4668379999998
usercpu_time_millis_training
642.899688