8958969
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)
6894573
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
1002.3609892875838
7650
cache_size
200
7650
class_weight
null
7650
coef0
0.7484593228765275
7650
decision_function_shape
"ovr"
7650
degree
3
7650
gamma
0.34682211793029805
7650
kernel
"rbf"
7650
max_iter
-1
7650
probability
false
7650
random_state
1
7650
shrinking
false
7650
tol
0.009859100450812775
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
18833194
description
https://api.openml.org/data/download/18833194/description.xml
-1
18833195
predictions
https://api.openml.org/data/download/18833195/predictions.arff
area_under_roc_curve
0.6265782828282828 [0.561553,0.562184,0.59375,0.498106,0.625,0.56029,0.625,0.53125,0.593119,0.71875,0.530619,0.625,0.718434,0.561553,0.505366,0.5625,0.65625,0.622475,0.591225,0.526831,0.65625,0.53125,0.65625,0.59375,0.655934,0.717172,0.590278,0.655934,0.625,0.78125,0.8125,0.5625,0.687184,0.779356,0.589331,0.874369,0.71654,0.62279,0.625,0.5625,0.593119,0.5625,0.75,0.749684,0.530934,0.65625,0.562184,0.53125,0.592172,0.624684,0.624684,0.593119,0.625,0.623737,0.561237,0.685606,0.59375,0.625,0.654987,0.592172,0.749369,0.780934,0.624053,0.5625,0.624684,0.624053,0.62279,0.59375,0.59375,0.592803,0.718119,0.5625,0.77904,0.5625,0.530934,0.593434,0.71875,0.592172,0.59375,0.59375,0.593434,0.749369,0.625,0.779987,0.687184,0.65625,0.5625,0.593434,0.59375,0.65625,0.8125,0.5625,0.59375,0.593434,0.5625,0.625,0.592803,0.624684,0.559659,0.623737]
average_cost
0
f_measure
0.35354592294362325 [0.190476,0.210526,0.315789,0.018957,0.4,0.035556,0.4,0.117647,0.285714,0.608696,0.105263,0.4,0.583333,0.190476,0.02005,0.222222,0.47619,0.285714,0.222222,0.064516,0.47619,0.117647,0.47619,0.315789,0.454545,0.5,0.2,0.454545,0.4,0.72,0.769231,0.222222,0.521739,0.580645,0.181818,0.8,0.466667,0.296296,0.4,0.222222,0.285714,0.222222,0.666667,0.64,0.111111,0.47619,0.210526,0.117647,0.25,0.380952,0.380952,0.285714,0.4,0.333333,0.181818,0.428571,0.315789,0.4,0.4,0.25,0.615385,0.692308,0.347826,0.222222,0.380952,0.347826,0.296296,0.315789,0.315789,0.272727,0.56,0.222222,0.5625,0.222222,0.111111,0.3,0.608696,0.25,0.315789,0.315789,0.3,0.615385,0.4,0.62069,0.521739,0.47619,0.222222,0.3,0.315789,0.47619,0.769231,0.222222,0.315789,0.3,0.222222,0.4,0.272727,0.380952,0.148148,0.333333]
kappa
0.25315656565656564
kb_relative_information_score
414.4182176044539
mean_absolute_error
0.01478749999999974
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
0.7435332495011422 [0.4,0.666667,1,0.009852,1,0.019139,1,1,0.6,1,0.333333,1,0.875,0.4,0.010444,1,1,0.333333,0.272727,0.066667,1,1,1,1,0.833333,0.583333,0.214286,0.833333,1,1,1,1,0.857143,0.6,0.176471,0.857143,0.5,0.363636,1,1,0.6,1,1,0.888889,0.5,1,0.666667,1,0.375,0.8,0.8,0.6,1,0.5,0.333333,0.5,1,1,0.555556,0.375,0.8,0.9,0.571429,1,0.8,0.571429,0.363636,1,1,0.5,0.777778,1,0.5625,1,0.5,0.75,1,0.375,1,1,0.75,0.8,1,0.692308,0.857143,1,1,0.75,1,1,1,1,1,0.75,1,1,0.5,0.8,0.181818,0.5]
predictive_accuracy
0.260625
prior_entropy
6.6438561897747395
recall
0.260625 [0.125,0.125,0.1875,0.25,0.25,0.25,0.25,0.0625,0.1875,0.4375,0.0625,0.25,0.4375,0.125,0.25,0.125,0.3125,0.25,0.1875,0.0625,0.3125,0.0625,0.3125,0.1875,0.3125,0.4375,0.1875,0.3125,0.25,0.5625,0.625,0.125,0.375,0.5625,0.1875,0.75,0.4375,0.25,0.25,0.125,0.1875,0.125,0.5,0.5,0.0625,0.3125,0.125,0.0625,0.1875,0.25,0.25,0.1875,0.25,0.25,0.125,0.375,0.1875,0.25,0.3125,0.1875,0.5,0.5625,0.25,0.125,0.25,0.25,0.25,0.1875,0.1875,0.1875,0.4375,0.125,0.5625,0.125,0.0625,0.1875,0.4375,0.1875,0.1875,0.1875,0.1875,0.5,0.25,0.5625,0.375,0.3125,0.125,0.1875,0.1875,0.3125,0.625,0.125,0.1875,0.1875,0.125,0.25,0.1875,0.25,0.125,0.25]
relative_absolute_error
0.7468434343434198
root_mean_prior_squared_error
0.09949874371066209
root_mean_squared_error
0.12160386507015203
root_relative_squared_error
1.222164828771815
total_cost
0
area_under_roc_curve
0.6351803200382135 [0.5,0.5,0.5,0.698113,0.5,0.990566,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.993711,1,1,1,0.5,0.5,0.75,0.5,0.75,0.5,0.5,0.75,0.5,0.75,0.496835,0.5,0.996855,0.996855,0.993711,1,0.75,1,1,0.5,0.75,0.5,0.5,1,1,0.5,0.5,0.75,0.5,1,0.5,0.493711,0.493711,0.5,1,0.5,0.5,1,0.996855,0.5,0.5,1,0.75,0.5,1,1,0.996855,0.5,1,0.75,0.5,0.496855,0.5,0.5,0.5,0.75,0.5,0.5,0.996835,0.5,1,0.5,0.5,0.5,0.75,0.5,1,1,0.5,0.75,0.5,0.5,0.5,1,0.5,0.5,0.993711]
area_under_roc_curve
0.6225818008120372 [0.493711,0.5,0.5,0.669811,0.5,1,0.5,1,0.5,1,0.5,0.5,1,0.5,0.5,1,0.5,0.5,0.5,0.484277,1,0.5,1,1,1,0.746835,0.496835,0.5,0.75,1,0.75,0.5,0.5,1,0.5,0.496855,0.496855,0.5,0.5,0.5,0.993711,1,0.75,0.5,0.5,0.75,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,0.496855,0.5,1,1,0.5,1,1,0.5,0.5,1,0.5,0.496835,1,1,0.5,0.75,1,0.75,0.5,0.5,0.75,0.5,0.5,0.75,0.5,0.5,0.75,0.5,0.5,0.75,0.75,0.5,0.5,0.5,0.5,0.75,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1]
area_under_roc_curve
0.6320356659501631 [0.5,0.5,0.5,0.68239,0.5,0.5,1,0.5,0.5,1,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,1,0.496835,0.5,0.5,0.5,1,0.996855,0.746835,0.5,0.996855,0.5,0.75,1,0.5,0.75,0.5,0.487421,1,0.996855,1,1,0.5,0.5,0.5,1,0.5,0.5,1,0.5,0.5,0.5,0.75,0.5,0.996855,1,0.75,0.996855,1,1,0.5,0.493711,0.5,1,1,0.5,0.5,0.5,0.75,0.75,0.5,0.5,0.5,0.75,0.5,0.993711,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,0.75,0.5,0.5,1,1,1,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,1,0.5,0.75,0.996855,0.5]
area_under_roc_curve
0.6351604171642384 [0.5,0.5,0.5,0.685535,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.493711,0.496835,1,0.5,0.75,1,1,0.746835,0.5,1,0.75,1,0.5,0.5,0.75,0.75,0.993711,0.5,0.5,0.493711,1,0.5,0.75,0.5,1,1,0.5,1,0.5,0.5,0.5,0.5,0.5,1,1,0.5,0.996855,0.746835,1,0.75,1,0.5,0.996855,1,0.5,1,0.75,0.5,0.5,0.5,1,0.5,0.5,0.5,0.996855,0.5,1,0.5,0.5,0.75,0.5,0.75,0.5,1,0.5,0.75,0.496855,1,0.5,0.75,0.5,1,0.5,1,0.5,0.5,0.5,1,0.5,0.5,0.490566,0.5]
area_under_roc_curve
0.613127935673911 [0.5,0.496855,0.5,0.5,1,0.5,1,0.5,1,0.75,0.5,0.5,0.5,0.493711,0.676101,0.5,0.75,0.746835,0.993711,0.5,0.75,0.5,0.75,0.5,0.5,0.75,0.5,1,0.5,0.5,1,0.5,0.5,0.746835,0.996855,1,1,0.5,0.5,0.5,0.5,0.5,1,0.5,0.496855,0.5,0.5,0.5,0.5,0.5,0.5,0.496855,0.5,1,0.5,0.5,0.5,0.5,0.746835,0.996855,0.5,0.75,0.496855,0.5,0.5,0.5,0.993711,0.5,0.5,0.5,0.75,0.5,0.993711,0.5,0.5,0.5,0.75,0.5,0.5,1,1,0.75,0.75,0.746835,1,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,1,0.5,1,0.493711,0.5]
area_under_roc_curve
0.6287914974922378 [0.5,1,0.5,0.5,1,0.5,1,0.5,1,0.5,0.5,0.5,0.496855,0.5,0.720126,0.5,0.5,0.746835,0.987421,0.5,0.5,0.5,0.5,0.5,0.5,0.746835,0.5,0.5,1,1,1,1,0.5,0.746835,0.977987,0.75,0.496835,0.5,0.5,0.5,0.5,0.5,0.5,0.996855,0.5,0.5,0.5,0.5,0.5,0.75,1,1,0.5,1,0.5,0.496835,1,0.5,0.5,0.996855,0.75,0.75,0.996855,1,0.5,0.5,0.996855,0.5,0.5,0.5,0.75,0.5,0.996855,0.5,0.5,1,0.75,0.5,0.5,0.5,0.996855,0.496835,0.5,0.746835,0.5,1,1,0.996855,0.5,0.75,1,0.5,1,1,0.5,1,0.5,0.496855,0.493711,0.5]
area_under_roc_curve
0.6351604171642384 [0.5,0.5,1,0.5,1,0.5,0.5,0.5,0.496855,0.5,0.5,1,0.75,1,0.679245,0.5,1,1,0.5,0.5,0.5,0.5,0.75,0.5,0.5,0.5,0.993711,0.5,0.5,0.75,0.5,0.5,1,0.996855,0.5,1,0.496835,0.496835,0.75,0.5,0.5,0.5,0.75,1,0.5,0.5,0.5,0.5,1,0.996855,0.5,0.5,0.75,0.5,0.5,1,0.5,0.5,0.5,0.996855,0.746835,0.5,0.996855,0.5,0.5,0.5,0.993711,0.5,0.5,0.5,1,0.5,0.75,1,0.5,0.5,1,0.996855,0.5,0.5,0.5,0.5,0.75,1,1,0.5,0.5,0.5,0.5,1,1,0.5,0.5,0.996855,1,0.5,0.5,1,0.5,0.5]
area_under_roc_curve
0.65088368760449 [0.5,1,1,0.5,1,0.5,0.5,0.5,0.996855,0.75,0.5,1,0.75,0.996855,0.732704,0.5,1,0.993711,0.5,0.5,0.5,0.5,0.5,0.5,0.75,0.5,0.984277,0.5,0.5,0.75,1,1,1,1,0.5,1,0.996835,0.746835,0.5,1,0.5,0.5,0.75,0.5,1,0.5,0.5,0.5,0.990566,0.5,0.496855,0.5,0.5,0.987421,0.5,0.75,0.5,0.75,0.746835,0.493711,0.75,0.75,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,1,1,0.5,0.996855,1,0.490566,1,1,0.5,0.5,0.5,0.75,0.5,0.5,0.5,0.5,1,0.5,1,0.5,0.5,1,1,0.5,0.5,0.5,0.75,0.5]
area_under_roc_curve
0.6351604171642387 [0.996855,0.5,1,0.5,0.5,0.704403,0.5,0.5,0.5,1,0.496855,1,0.5,0.5,0.5,1,1,0.493711,0.5,0.493711,0.75,0.5,0.5,0.5,0.5,0.5,0.990566,0.75,0.75,1,1,0.5,0.496855,0.996855,0.5,1,0.75,0.496835,0.5,0.5,0.5,0.5,0.75,0.75,0.5,0.75,0.5,0.5,0.996855,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.75,0.5,0.5,0.75,0.75,0.5,1,0.996855,0.496835,1,0.5,0.996855,0.996855,0.5,0.496835,0.5,0.5,0.5,1,0.996855,0.5,0.5,0.5,1,1,0.996855,0.75,0.75,0.5,0.5,1,0.5,0.75,0.5,0.75,0.5,0.5,0.5,0.996855,0.75,0.5,0.996855]
area_under_roc_curve
0.591155162805509 [1,0.5,0.5,0.5,0.5,0.660377,0.5,0.5,0.5,0.5,0.996855,1,0.75,0.5,0.5,0.5,1,0.493711,0.5,0.490566,0.5,0.5,0.5,0.5,0.75,0.996855,0.5,0.5,0.5,0.5,0.75,0.5,1,0.996855,0.5,0.75,0.496835,0.75,0.5,0.5,0.5,0.5,0.75,1,0.5,0.75,0.996855,0.5,0.496855,0.5,0.5,0.5,0.5,0.5,0.5,0.496855,0.5,0.5,0.5,0.5,0.75,0.75,0.5,0.5,0.496855,0.993711,0.5,0.5,0.5,0.996855,0.496855,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.75,0.5,1,0.996855,0.5,0.5,0.5,0.5,1,0.5,1,0.5,0.5,0.5,0.5,0.5,0.993711,0.5,0.496835,0.996855]
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
0.26992368814412715
kappa
0.24462978991266032
kappa
0.2636299268350248
kappa
0.2698662470495673
kappa
0.22574553466047684
kappa
0.2572777340676633
kappa
0.2697513377400063
kappa
0.3012275731822474
kappa
0.2698087969155717
kappa
0.18187539332913782
kb_relative_information_score
43.74684128665785
kb_relative_information_score
39.73811167585295
kb_relative_information_score
42.74465888395661
kb_relative_information_score
43.746841286657855
kb_relative_information_score
36.73156446774922
kb_relative_information_score
41.74247648125538
kb_relative_information_score
43.7468412866579
kb_relative_information_score
48.757753300164076
kb_relative_information_score
43.74684128665785
kb_relative_information_score
29.716287648840638
mean_absolute_error
0.01450000000000001
mean_absolute_error
0.01500000000000001
mean_absolute_error
0.01462500000000001
mean_absolute_error
0.01450000000000001
mean_absolute_error
0.01537500000000001
mean_absolute_error
0.01475000000000001
mean_absolute_error
0.01450000000000001
mean_absolute_error
0.013875000000000009
mean_absolute_error
0.01450000000000001
mean_absolute_error
0.01625000000000001
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
0.275
predictive_accuracy
0.25
predictive_accuracy
0.26875
predictive_accuracy
0.275
predictive_accuracy
0.23125
predictive_accuracy
0.2625
predictive_accuracy
0.275
predictive_accuracy
0.30625
predictive_accuracy
0.275
predictive_accuracy
0.1875
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
0.275 [0,0,0,1,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,1,1,1,1,0,0,0.5,0,0.5,0,0,0.5,0,0.5,0,0,1,1,1,1,0.5,1,1,0,0.5,0,0,1,1,0,0,0.5,0,1,0,0,0,0,1,0,0,1,1,0,0,1,0.5,0,1,1,1,0,1,0.5,0,0,0,0,0,0.5,0,0,1,0,1,0,0,0,0.5,0,1,1,0,0.5,0,0,0,1,0,0,1]
recall
0.25 [0,0,0,1,0,1,0,1,0,1,0,0,1,0,0,1,0,0,0,0,1,0,1,1,1,0.5,0,0,0.5,1,0.5,0,0,1,0,0,0,0,0,0,1,1,0.5,0,0,0.5,0,0,0,0,1,0,0,0,0,0,0,1,1,0,1,1,0,0,1,0,0,1,1,0,0.5,1,0.5,0,0,0.5,0,0,0.5,0,0,0.5,0,0,0.5,0.5,0,0,0,0,0.5,0,0,0,0,0,0,0,0,1]
recall
0.26875 [0,0,0,1,0,0,1,0,0,1,0,0,1,0,0,0,0,0,1,0,0,0,0,1,1,0.5,0,1,0,0.5,1,0,0.5,0,0,1,1,1,1,0,0,0,1,0,0,1,0,0,0,0.5,0,1,1,0.5,1,1,1,0,0,0,1,1,0,0,0,0.5,0.5,0,0,0,0.5,0,1,0,0,0,1,0,0,0,0,0.5,0,0,1,1,1,0,0,0,0,1,0,0,0,1,0,0.5,1,0]
recall
0.275 [0,0,0,1,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0,0.5,1,1,0.5,0,1,0.5,1,0,0,0.5,0.5,1,0,0,0,1,0,0.5,0,1,1,0,1,0,0,0,0,0,1,1,0,1,0.5,1,0.5,1,0,1,1,0,1,0.5,0,0,0,1,0,0,0,1,0,1,0,0,0.5,0,0.5,0,1,0,0.5,0,1,0,0.5,0,1,0,1,0,0,0,1,0,0,0,0]
recall
0.23125 [0,0,0,0,1,0,1,0,1,0.5,0,0,0,0,1,0,0.5,0.5,1,0,0.5,0,0.5,0,0,0.5,0,1,0,0,1,0,0,0.5,1,1,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0.5,1,0,0.5,0,0,0,0,1,0,0,0,0.5,0,1,0,0,0,0.5,0,0,1,1,0.5,0.5,0.5,1,0,0,0,0,0,1,0,0,0,0,1,0,1,0,0]
recall
0.2625 [0,1,0,0,1,0,1,0,1,0,0,0,0,0,1,0,0,0.5,1,0,0,0,0,0,0,0.5,0,0,1,1,1,1,0,0.5,1,0.5,0,0,0,0,0,0,0,1,0,0,0,0,0,0.5,1,1,0,1,0,0,1,0,0,1,0.5,0.5,1,1,0,0,1,0,0,0,0.5,0,1,0,0,1,0.5,0,0,0,1,0,0,0.5,0,1,1,1,0,0.5,1,0,1,1,0,1,0,0,0,0]
recall
0.275 [0,0,1,0,1,0,0,0,0,0,0,1,0.5,1,1,0,1,1,0,0,0,0,0.5,0,0,0,1,0,0,0.5,0,0,1,1,0,1,0,0,0.5,0,0,0,0.5,1,0,0,0,0,1,1,0,0,0.5,0,0,1,0,0,0,1,0.5,0,1,0,0,0,1,0,0,0,1,0,0.5,1,0,0,1,1,0,0,0,0,0.5,1,1,0,0,0,0,1,1,0,0,1,1,0,0,1,0,0]
recall
0.30625 [0,1,1,0,1,0,0,0,1,0.5,0,1,0.5,1,1,0,1,1,0,0,0,0,0,0,0.5,0,1,0,0,0.5,1,1,1,1,0,1,1,0.5,0,1,0,0,0.5,0,1,0,0,0,1,0,0,0,0,1,0,0.5,0,0.5,0.5,0,0.5,0.5,1,0,0,0,0,0,0,0,1,0,1,1,0,1,1,0,1,1,0,0,0,0.5,0,0,0,0,1,0,1,0,0,1,1,0,0,0,0.5,0]
recall
0.275 [1,0,1,0,0,1,0,0,0,1,0,1,0,0,0,1,1,0,0,0,0.5,0,0,0,0,0,1,0.5,0.5,1,1,0,0,1,0,1,0.5,0,0,0,0,0,0.5,0.5,0,0.5,0,0,1,1,0,0,0,0,0,0,0,0,0.5,0,0,0.5,0.5,0,1,1,0,1,0,1,1,0,0,0,0,0,1,1,0,0,0,1,1,1,0.5,0.5,0,0,1,0,0.5,0,0.5,0,0,0,1,0.5,0,1]
recall
0.1875 [1,0,0,0,0,1,0,0,0,0,1,1,0.5,0,0,0,1,0,0,0,0,0,0,0,0.5,1,0,0,0,0,0.5,0,1,1,0,0.5,0,0.5,0,0,0,0,0.5,1,0,0.5,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0.5,0.5,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0.5,0,1,1,0,0,0,0,1,0,1,0,0,0,0,0,1,0,0,1]
relative_absolute_error
0.7323232323232315
relative_absolute_error
0.7575757575757568
relative_absolute_error
0.7386363636363629
relative_absolute_error
0.7323232323232315
relative_absolute_error
0.7765151515151507
relative_absolute_error
0.7449494949494943
relative_absolute_error
0.7323232323232315
relative_absolute_error
0.700757575757575
relative_absolute_error
0.7323232323232315
relative_absolute_error
0.8207070707070698
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
0.12041594578792299
root_mean_squared_error
0.12247448713915894
root_mean_squared_error
0.12093386622447828
root_mean_squared_error
0.12041594578792299
root_mean_squared_error
0.12399596767637248
root_mean_squared_error
0.12144957801491123
root_mean_squared_error
0.12041594578792299
root_mean_squared_error
0.1177921898938975
root_mean_squared_error
0.12041594578792299
root_mean_squared_error
0.12747548783981966
root_relative_squared_error
1.2102257907706577
root_relative_squared_error
1.230914909793327
root_relative_squared_error
1.215431087010994
root_relative_squared_error
1.2102257907706577
root_relative_squared_error
1.246206364544132
root_relative_squared_error
1.2206141855225954
root_relative_squared_error
1.2102257907706577
root_relative_squared_error
1.1838560518556092
root_relative_squared_error
1.2102257907706577
root_relative_squared_error
1.2811768579763452
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
755.9901780000473
usercpu_time_millis
781.0241049996876
usercpu_time_millis
759.1164890000073
usercpu_time_millis
767.3240390001865
usercpu_time_millis
757.5608660001762
usercpu_time_millis
733.2190049999099
usercpu_time_millis
761.4960490000158
usercpu_time_millis
738.8752270001078
usercpu_time_millis
741.2427440001466
usercpu_time_millis
766.5057770000203
usercpu_time_millis_testing
53.03024600016215
usercpu_time_millis_testing
54.644212999846786
usercpu_time_millis_testing
54.14012300002469
usercpu_time_millis_testing
55.22279299998445
usercpu_time_millis_testing
53.65292400006183
usercpu_time_millis_testing
51.41062699999566
usercpu_time_millis_testing
58.35140199997113
usercpu_time_millis_testing
52.29110100003709
usercpu_time_millis_testing
56.25451100013379
usercpu_time_millis_testing
57.151742000087324
usercpu_time_millis_training
702.9599319998852
usercpu_time_millis_training
726.3798919998408
usercpu_time_millis_training
704.9763659999826
usercpu_time_millis_training
712.1012460002021
usercpu_time_millis_training
703.9079420001144
usercpu_time_millis_training
681.8083779999142
usercpu_time_millis_training
703.1446470000446
usercpu_time_millis_training
686.5841260000707
usercpu_time_millis_training
684.9882330000128
usercpu_time_millis_training
709.354034999933