8958597
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)
6894202
categorical_features
[]
7644
dtype
{"oml-python:serialized_object": "type", "value": "np.float64"}
7644
handle_unknown
"ignore"
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n_values
"auto"
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sparse
true
7644
threshold
0.0
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copy
true
7646
with_mean
false
7646
with_std
true
7646
C
0.1372762723401639
7650
cache_size
200
7650
class_weight
null
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coef0
0.10675770940117879
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decision_function_shape
"ovr"
7650
degree
3
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gamma
0.00011561680810550799
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kernel
"rbf"
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max_iter
-1
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probability
false
7650
random_state
1
7650
shrinking
true
7650
tol
2.6731962154534592e-05
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
18832458
description
https://api.openml.org/data/download/18832458/description.xml
-1
18832459
predictions
https://api.openml.org/data/download/18832459/predictions.arff
area_under_roc_curve
0.5994318181818183 [0.553977,0.618687,0.623422,0.561869,0.62279,0.623106,0.623737,0.618371,0.592172,0.625,0.618371,0.618371,0.618056,0.592487,0.5,0.590909,0.625,0.585543,0.611742,0.558081,0.560922,0.530619,0.589331,0.623422,0.559028,0.528725,0.525253,0.622475,0.59154,0.587753,0.623106,0.59375,0.622159,0.619318,0.61553,0.620581,0.620896,0.585227,0.622159,0.624369,0.587753,0.619634,0.623422,0.621843,0.559343,0.622159,0.622159,0.619949,0.618056,0.585543,0.558712,0.589015,0.619003,0.621843,0.620896,0.525568,0.624684,0.621843,0.614583,0.620896,0.619634,0.590909,0.618056,0.622475,0.619003,0.588068,0.585227,0.624053,0.592487,0.588384,0.622159,0.560922,0.619634,0.59375,0.557765,0.621843,0.620896,0.589015,0.623737,0.62279,0.529672,0.592172,0.620896,0.59154,0.620896,0.620896,0.625,0.554924,0.592487,0.587437,0.588699,0.625,0.621528,0.614899,0.617424,0.623737,0.612689,0.620896,0.497475,0.559343]
average_cost
0
kappa
0.19886363636363635
kb_relative_information_score
328.2305309721471
mean_absolute_error
0.015862499999999717
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
0.206875
prior_entropy
6.6438561897747395
recall
0.206875 [0.125,0.25,0.25,0.125,0.25,0.25,0.25,0.25,0.1875,0.25,0.25,0.25,0.25,0.1875,0,0.1875,0.25,0.1875,0.25,0.125,0.125,0.0625,0.1875,0.25,0.125,0.0625,0.0625,0.25,0.1875,0.1875,0.25,0.1875,0.25,0.25,0.25,0.25,0.25,0.1875,0.25,0.25,0.1875,0.25,0.25,0.25,0.125,0.25,0.25,0.25,0.25,0.1875,0.125,0.1875,0.25,0.25,0.25,0.0625,0.25,0.25,0.25,0.25,0.25,0.1875,0.25,0.25,0.25,0.1875,0.1875,0.25,0.1875,0.1875,0.25,0.125,0.25,0.1875,0.125,0.25,0.25,0.1875,0.25,0.25,0.0625,0.1875,0.25,0.1875,0.25,0.25,0.25,0.125,0.1875,0.1875,0.1875,0.25,0.25,0.25,0.25,0.25,0.25,0.25,0,0.125]
relative_absolute_error
0.8011363636363478
root_mean_prior_squared_error
0.09949874371066209
root_mean_squared_error
0.12594641717809887
root_relative_squared_error
1.2658091196040169
total_cost
0
area_under_roc_curve
0.5911949685534589 [0.465409,0.5,0.5,0.5,0.5,0.993711,0.5,0.987421,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.977987,0.496855,0.496855,0.977987,0.993711,0.496855,0.5,0.5,0.5,0.5,0.471698,0.5,0.5,0.5,0.5,0.5,0.987421,0.996855,0.987421,0.993711,0.5,0.977987,0.981132,0.5,0.5,0.5,0.5,0.993711,0.990566,0.5,0.5,0.5,0.5,0.987421,0.5,0.993711,0.484277,0.5,0.987421,0.990566,0.5,0.993711,0.984277,0.5,0.5,0.990566,0.5,0.5,1,0.993711,0.493711,0.5,0.993711,0.5,0.5,0.490566,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.993711,0.996855,0.5,0.5,0.5,0.5,0.5,0.984277,0.5,1,0.5,0.5,0.5,0.5,0.971698,0.5,0.5,0.993711]
area_under_roc_curve
0.6037735849056602 [0.974843,0.5,0.5,0.5,0.5,1,0.5,0.981132,0.5,1,0.5,0.5,0.5,0.5,0.5,0.996855,0.5,0.5,0.5,0.984277,1,0.496855,0.987421,0.993711,0.996855,0.5,0.5,0.5,0.5,0.981132,0.5,0.5,0.5,0.5,0.5,0.990566,0.996855,0.977987,0.996855,0.5,0.981132,0.987421,0.5,0.5,0.5,0.5,0.996855,0.987421,0.5,0.5,0.5,0.5,0.974843,0.5,0.996855,0.481132,0.5,0.981132,0.977987,0.5,0.987421,0.990566,0.5,0.5,0.984277,0.5,0.5,0.996855,0.5,0.981132,0.5,1,0.5,0.5,0.496855,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.990566,1,0.5,0.5,0.5,0.5,0.5,0.984277,0.5,1,0.5,0.5,0.5,0.5,0.984277,0.5,0.5,0.487421]
area_under_roc_curve
0.6069182389937107 [0.5,0.5,0.5,0.996855,0.5,0.5,0.996855,0.5,0.5,0.5,0.5,0.5,0.981132,0.5,0.5,0.5,0.5,0.5,0.993711,0.5,0.996855,0.5,0.5,0.996855,0.984277,0.5,0.5,0.993711,0.5,0.5,1,0.5,0.5,0.5,0.977987,0.993711,0.974843,0.981132,0.990566,0.5,0.5,0.990566,0.996855,0.984277,0.5,0.987421,0.5,0.981132,0.5,0.5,0.5,0.993711,0.987421,0.5,0.984277,0.5,1,0.5,0.965409,0.5,0.987421,0.496855,0.5,0.990566,0.5,0.5,0.5,0.5,0.996855,0.5,0.5,0.5,0.971698,0.5,0.984277,0.5,0.5,0.5,0.5,0.5,0.496855,0.5,0.5,0.5,0.990566,0.987421,1,0.5,0.5,0.484277,0.5,1,0.993711,0.5,0.5,1,0.5,0.5,0.496855,0.5]
area_under_roc_curve
0.6069182389937106 [0.5,0.5,0.5,0.996855,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.971698,0.5,0.5,0.5,0.5,0.5,0.987421,0.5,0.490566,1,0.5,1,0.487421,0.5,0.5,0.987421,0.5,0.5,0.996855,0.5,0.5,0.5,0.987421,0.984277,0.990566,0.468553,0.990566,0.5,0.5,0.987421,0.990566,0.993711,0.5,0.993711,0.5,0.990566,0.5,0.5,0.5,0.990566,0.990566,0.5,0.984277,0.5,1,0.5,0.962264,0.5,0.977987,1,0.5,0.996855,0.5,0.5,0.5,0.5,0.996855,0.5,0.5,0.5,0.990566,0.5,0.981132,0.5,0.5,0.5,0.5,0.5,0.496855,0.5,0.5,0.5,0.984277,0.993711,1,0.5,0.5,0.984277,0.5,1,0.990566,0.5,0.5,0.996855,0.5,0.5,0.493711,0.5]
area_under_roc_curve
0.5974842767295595 [0.5,0.984277,0.5,0.5,0.993711,0.5,0.996855,0.5,0.493711,0.5,0.5,0.5,0.993711,0.493711,0.5,0.5,0.5,0.5,0.940252,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.996855,0.996855,0.5,0.993711,0.5,0.5,0.5,0.971698,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.996855,0.993711,0.996855,0.5,0.5,0.5,0.5,0.496855,0.484277,0.5,0.990566,0.5,0.5,0.996855,0.5,0.5,0.993711,0.5,0.5,0.971698,0.996855,0.5,0.5,0.468553,0.5,0.5,0.5,0.5,0.5,0.987421,1,0.5,1,0.5,0.5,0.5,0.987421,0.993711,0.5,0.5,0.5,0.990566,0.990566,1,0.977987,0.5,0.5,0.984277,0.5,0.987421,0.984277,0.5,0.993711,0.5,0.981132,0.496855,0.5]
area_under_roc_curve
0.6132075471698113 [0.5,0.993711,0.5,0.5,0.990566,0.5,0.993711,0.5,1,0.5,0.5,0.5,0.984277,0.993711,0.5,0.5,0.5,0.5,0.946541,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.996855,1,0.5,0.990566,1,0.5,0.5,0.968553,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.996855,0.993711,0.990566,0.993711,0.5,0.5,0.5,0.5,1,0.984277,0.5,0.987421,0.5,0.5,1,0.5,0.5,0.993711,0.5,0.5,0.977987,0.990566,0.5,0.5,0.971698,0.5,0.5,0.5,0.5,0.5,0.996855,1,0.5,0.996855,0.5,0.5,0.5,0.990566,0.496855,0.5,0.5,0.5,0.993711,0.987421,1,0.987421,0.5,0.5,0.977987,0.5,0.993711,0.984277,0.5,0.996855,0.5,0.984277,0.487421,0.5]
area_under_roc_curve
0.6006289308176099 [0.5,0.981132,1,0.5,0.996855,0.5,0.5,0.5,0.993711,0.5,0.987421,0.977987,0.5,1,0.5,0.5,1,0.977987,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.496855,0.481132,0.5,0.993711,0.5,0.5,1,0.990566,0.977987,0.5,0.5,0.5,0.5,0.5,0.996855,0.5,0.5,0.5,0.5,0.490566,0.5,0.5,0.5,0.987421,0.984277,0.487421,0.5,0.5,0.993711,0.5,0.5,0.5,0.5,0.5,0.984277,0.5,0.5,0.987421,0.5,0.5,0.981132,0.990566,0.5,0.5,0.5,0.990566,0.5,0.5,1,0.5,0.987421,0.987421,0.987421,1,1,0.5,0.996855,0.5,0.5,0.5,0.5,0.5,0.481132,0.496855,0.5,0.990566,0.5,0.5,0.955975,0.990566,0.5,0.5,0.996855,0.5,0.5]
area_under_roc_curve
0.591194968553459 [0.5,0.977987,0.996855,0.5,0.996855,0.5,0.5,0.5,0.996855,0.5,0.984277,0.971698,0.5,1,0.5,0.5,1,0.977987,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.990566,0.484277,0.5,0.487421,0.5,0.5,1,0.993711,0.987421,0.5,0.5,0.5,0.5,0.5,0.996855,0.5,0.5,0.5,0.5,0.493711,0.5,0.5,0.5,0.990566,0.481132,0.977987,0.5,0.5,0.996855,0.5,0.5,0.5,0.5,0.5,0.987421,0.5,0.5,0.993711,0.5,0.5,0.474843,0.984277,0.5,0.5,0.5,0.993711,0.5,0.5,0.5,0.5,0.984277,0.984277,0.481132,1,1,0.5,0.993711,0.5,0.5,0.5,0.5,0.5,0.477987,1,0.5,0.496855,0.5,0.5,0.974843,0.984277,0.5,0.5,0.996855,0.5,0.5]
area_under_roc_curve
0.5974842767295594 [0.477987,0.5,1,0.5,0.5,0.993711,0.5,0.984277,0.5,1,0.977987,0.987421,0.5,0.5,0.5,0.990566,1,0.987421,0.5,0.496855,0.5,0.5,0.493711,0.5,0.5,0.490566,0.984277,0.5,0.5,0.996855,0.5,0.5,0.990566,0.987421,0.5,0.5,0.5,0.5,0.5,1,0.496855,0.5,0.5,0.5,0.5,0.5,0.990566,0.5,0.971698,0.974843,0.5,0.5,0.5,0.5,0.5,0.493711,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5,0.984277,0.993711,0.5,0.996855,0.5,0.990566,0.993711,0.493711,0.5,0.5,0.5,0.5,0.993711,0.990566,0.993711,0.5,0.5,1,0.990566,0.990566,0.5,0.5,0.5,0.5,0.993711,0.5,0.5,0.5,0.5,0.5,0.968553,0.5,0.959119,0.5,0.5,0.496855]
area_under_roc_curve
0.6006289308176098 [0.996855,0.5,0.987421,0.5,0.5,0.993711,0.5,0.981132,0.5,1,0.984277,0.996855,0.5,0.5,0.5,0.984277,1,0.474843,0.5,0.496855,0.5,0.5,0.996855,0.5,0.5,0.496855,0.490566,0.5,0.5,0.990566,0.5,0.5,0.996855,0.990566,0.5,0.5,0.5,0.5,0.5,1,0.984277,0.5,0.5,0.5,0.5,0.5,0.990566,0.5,0.981132,0.977987,0.5,0.5,0.5,0.5,0.5,0.984277,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5,0.981132,0.993711,0.5,0.996855,0.5,0.981132,0.993711,0.496855,0.5,0.5,0.5,0.5,0.993711,0.993711,0.993711,0.5,0.5,0.493711,0.984277,0.490566,0.5,0.5,0.5,0.5,0.996855,0.5,0.5,0.5,0.5,0.5,0.981132,0.5,0.962264,0.5,0.5,0.990566]
average_cost
0
average_cost
0
average_cost
0
average_cost
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average_cost
0
average_cost
0
average_cost
0
average_cost
0
average_cost
0
average_cost
0
kappa
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kappa
0.20754716981132074
kappa
0.21383647798742136
kappa
0.21383647798742136
kappa
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kappa
0.22641509433962265
kappa
0.2012578616352201
kappa
0.18238993710691823
kappa
0.1949685534591195
kappa
0.2012578616352201
kb_relative_information_score
29.716287648840638
kb_relative_information_score
33.72501725964554
kb_relative_information_score
34.72719966234676
kb_relative_information_score
34.72719966234676
kb_relative_information_score
31.72065245424309
kb_relative_information_score
36.731564467749216
kb_relative_information_score
32.72283485694432
kb_relative_information_score
29.71628764884065
kb_relative_information_score
31.72065245424309
kb_relative_information_score
32.72283485694432
mean_absolute_error
0.01625000000000001
mean_absolute_error
0.01575000000000001
mean_absolute_error
0.01562500000000001
mean_absolute_error
0.01562500000000001
mean_absolute_error
0.01600000000000001
mean_absolute_error
0.01537500000000001
mean_absolute_error
0.01587500000000001
mean_absolute_error
0.01625000000000001
mean_absolute_error
0.01600000000000001
mean_absolute_error
0.01587500000000001
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
0.1875
predictive_accuracy
0.2125
predictive_accuracy
0.21875
predictive_accuracy
0.21875
predictive_accuracy
0.2
predictive_accuracy
0.23125
predictive_accuracy
0.20625
predictive_accuracy
0.1875
predictive_accuracy
0.2
predictive_accuracy
0.20625
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
0.1875 [0,0,0,0,0,1,0,1,0,1,0,0,0,0,0,0,0,0,0,1,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,0,1,1,0,0,0,0,1,1,0,0,0,0,1,0,1,0,0,1,1,0,1,1,0,0,1,0,0,1,1,0,0,1,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,1,0,1,0,0,0,0,1,0,0,1]
recall
0.2125 [1,0,0,0,0,1,0,1,0,1,0,0,0,0,0,1,0,0,0,1,1,0,1,1,1,0,0,0,0,1,0,0,0,0,0,1,1,1,1,0,1,1,0,0,0,0,1,1,0,0,0,0,1,0,1,0,0,1,1,0,1,1,0,0,1,0,0,1,0,1,0,1,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,1,0,1,0,0,0,0,1,0,0,0]
recall
0.21875 [0,0,0,1,0,0,1,0,0,0,0,0,1,0,0,0,0,0,1,0,1,0,0,1,1,0,0,1,0,0,1,0,0,0,1,1,1,1,1,0,0,1,1,1,0,1,0,1,0,0,0,1,1,0,1,0,1,0,1,0,1,0,0,1,0,0,0,0,1,0,0,0,1,0,1,0,0,0,0,0,0,0,0,0,1,1,1,0,0,0,0,1,1,0,0,1,0,0,0,0]
recall
0.21875 [0,0,0,1,0,0,1,0,0,0,0,0,1,0,0,0,0,0,1,0,0,1,0,1,0,0,0,1,0,0,1,0,0,0,1,1,1,0,1,0,0,1,1,1,0,1,0,1,0,0,0,1,1,0,1,0,1,0,1,0,1,1,0,1,0,0,0,0,1,0,0,0,1,0,1,0,0,0,0,0,0,0,0,0,1,1,1,0,0,1,0,1,1,0,0,1,0,0,0,0]
recall
0.2 [0,1,0,0,1,0,1,0,0,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1,1,0,1,0,0,0,1,0,0,0,0,0,0,0,1,1,1,1,0,0,0,0,0,0,0,1,0,0,1,0,0,1,0,0,1,1,0,0,0,0,0,0,0,0,1,1,0,1,0,0,0,1,1,0,0,0,1,1,1,1,0,0,1,0,1,1,0,1,0,1,0,0]
recall
0.23125 [0,1,0,0,1,0,1,0,1,0,0,0,1,1,0,0,0,0,1,0,0,0,0,0,0,0,0,1,1,0,1,1,0,0,1,0,0,0,0,0,0,0,1,1,1,1,0,0,0,0,1,1,0,1,0,0,1,0,0,1,0,0,1,1,0,0,1,0,0,0,0,0,1,1,0,1,0,0,0,1,0,0,0,0,1,1,1,1,0,0,1,0,1,1,0,1,0,1,0,0]
recall
0.20625 [0,1,1,0,1,0,0,0,1,0,1,1,0,1,0,0,1,1,0,0,0,0,0,0,0,0,0,0,1,0,0,1,1,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1,1,0,0,0,1,0,0,0,0,0,1,0,0,1,0,0,1,1,0,0,0,1,0,0,1,0,1,1,1,1,1,0,1,0,0,0,0,0,0,0,0,1,0,0,1,1,0,0,1,0,0]
recall
0.1875 [0,1,1,0,1,0,0,0,1,0,1,1,0,1,0,0,1,1,0,0,0,0,0,0,0,1,0,0,0,0,0,1,1,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1,0,1,0,0,1,0,0,0,0,0,1,0,0,1,0,0,0,1,0,0,0,1,0,0,0,0,1,1,0,1,1,0,1,0,0,0,0,0,0,1,0,0,0,0,1,1,0,0,1,0,0]
recall
0.2 [0,0,1,0,0,1,0,1,0,1,1,1,0,0,0,1,1,1,0,0,0,0,0,0,0,0,1,0,0,1,0,0,1,1,0,0,0,0,0,1,0,0,0,0,0,0,1,0,1,1,0,0,0,0,0,0,0,1,0,0,0,0,0,0,1,1,0,1,0,1,1,0,0,0,0,0,1,1,1,0,0,1,1,1,0,0,0,0,1,0,0,0,0,0,1,0,1,0,0,0]
recall
0.20625 [1,0,1,0,0,1,0,1,0,1,1,1,0,0,0,1,1,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0,1,1,0,0,0,0,0,1,1,0,0,0,0,0,1,0,1,1,0,0,0,0,0,1,0,1,0,0,0,0,0,0,1,1,0,1,0,1,1,0,0,0,0,0,1,1,1,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,1,0,1,0,0,1]
relative_absolute_error
0.8207070707070698
relative_absolute_error
0.7954545454545446
relative_absolute_error
0.7891414141414134
relative_absolute_error
0.7891414141414134
relative_absolute_error
0.8080808080808072
relative_absolute_error
0.7765151515151507
relative_absolute_error
0.801767676767676
relative_absolute_error
0.8207070707070698
relative_absolute_error
0.8080808080808072
relative_absolute_error
0.801767676767676
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
0.12747548783981966
root_mean_squared_error
0.12549900398011138
root_mean_squared_error
0.12500000000000003
root_mean_squared_error
0.12500000000000003
root_mean_squared_error
0.12649110640673522
root_mean_squared_error
0.12399596767637248
root_mean_squared_error
0.12599603168354157
root_mean_squared_error
0.12747548783981966
root_mean_squared_error
0.12649110640673522
root_mean_squared_error
0.12599603168354157
root_relative_squared_error
1.2811768579763452
root_relative_squared_error
1.2613124477737823
root_relative_squared_error
1.2562972690740146
root_relative_squared_error
1.2562972690740146
root_relative_squared_error
1.271283452327456
root_relative_squared_error
1.246206364544132
root_relative_squared_error
1.26630776414557
root_relative_squared_error
1.2811768579763452
root_relative_squared_error
1.271283452327456
root_relative_squared_error
1.26630776414557
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
716.7975950001164
usercpu_time_millis
685.4039820000253
usercpu_time_millis
689.4929860000047
usercpu_time_millis
675.241116000052
usercpu_time_millis
702.8868049999346
usercpu_time_millis
677.9756020002878
usercpu_time_millis
665.080976000354
usercpu_time_millis
662.1583849998842
usercpu_time_millis
657.468855000161
usercpu_time_millis
678.1480749998536
usercpu_time_millis_testing
55.31545899998491
usercpu_time_millis_testing
53.87889000007817
usercpu_time_millis_testing
54.73596900014854
usercpu_time_millis_testing
53.75637299994196
usercpu_time_millis_testing
53.90231399996992
usercpu_time_millis_testing
53.133832000185066
usercpu_time_millis_testing
52.058774000215635
usercpu_time_millis_testing
53.473755999903005
usercpu_time_millis_testing
50.50581700015755
usercpu_time_millis_testing
51.71769599996878
usercpu_time_millis_training
661.4821360001315
usercpu_time_millis_training
631.5250919999471
usercpu_time_millis_training
634.7570169998562
usercpu_time_millis_training
621.48474300011
usercpu_time_millis_training
648.9844909999647
usercpu_time_millis_training
624.8417700001028
usercpu_time_millis_training
613.0222020001383
usercpu_time_millis_training
608.6846289999812
usercpu_time_millis_training
606.9630380000035
usercpu_time_millis_training
626.4303789998849