8958282
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)
6893889
categorical_features
[]
7644
dtype
{"oml-python:serialized_object": "type", "value": "np.float64"}
7644
handle_unknown
"ignore"
7644
n_values
"auto"
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sparse
true
7644
threshold
0.0
7645
copy
true
7646
with_mean
false
7646
with_std
true
7646
C
32359.525567777717
7650
cache_size
200
7650
class_weight
null
7650
coef0
0.9990951417854717
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decision_function_shape
"ovr"
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degree
3
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gamma
7.910191118480936
7650
kernel
"rbf"
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max_iter
-1
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probability
false
7650
random_state
1
7650
shrinking
false
7650
tol
0.09917005797934816
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
18831832
description
https://api.openml.org/data/download/18831832/description.xml
-1
18831833
predictions
https://api.openml.org/data/download/18831833/predictions.arff
area_under_roc_curve
0.5340909090909091 [0.576073,0.5,0.530619,0.624053,0.5,0.61774,0.607639,0.530619,0.618056,0.53125,0.617109,0.620581,0.5,0.565657,0.624684,0.525884,0.530934,0.499369,0.560922,0.499369,0.499684,0.60101,0.5,0.529987,0.5,0.5,0.529356,0.5,0.53125,0.53125,0.5,0.619003,0.53125,0.562184,0.565972,0.499684,0.530619,0.53125,0.53125,0.53125,0.5,0.53125,0.5,0.53125,0.586806,0.53125,0.616793,0.5,0.605114,0.53125,0.5,0.53125,0.52178,0.525253,0.5,0.5,0.5625,0.53125,0.53125,0.562184,0.5625,0.53125,0.499684,0.5625,0.5,0.53125,0.499053,0.528093,0.525568,0.55524,0.5,0.53125,0.530619,0.5,0.5,0.53125,0.5,0.530934,0.5,0.5,0.5,0.5,0.5,0.499684,0.5,0.53125,0.615215,0.5,0.5,0.5,0.5,0.5,0.5,0.596591,0.5,0.5625,0.576389,0.5,0.530303,0.573232]
average_cost
0
kappa
0.06818181818181819
kb_relative_information_score
120.77877361299527
mean_absolute_error
0.01844999999999966
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
0.0775
prior_entropy
6.6438561897747395
recall
0.0775 [0.25,0,0.0625,0.25,0,0.25,0.25,0.0625,0.25,0.0625,0.25,0.25,0,0.1875,0.25,0.0625,0.0625,0,0.125,0,0,0.25,0,0.0625,0,0,0.0625,0,0.0625,0.0625,0,0.25,0.0625,0.125,0.25,0,0.0625,0.0625,0.0625,0.0625,0,0.0625,0,0.0625,0.1875,0.0625,0.25,0,0.25,0.0625,0,0.0625,0.0625,0.0625,0,0,0.125,0.0625,0.0625,0.25,0.125,0.0625,0,0.125,0,0.0625,0,0.0625,0.0625,0.125,0,0.0625,0.0625,0,0,0.0625,0,0.0625,0,0,0,0,0,0,0,0.0625,0.25,0,0,0,0,0,0,0.25,0,0.125,0.1875,0,0.0625,0.25]
relative_absolute_error
0.931818181818163
root_mean_prior_squared_error
0.09949874371066209
root_mean_squared_error
0.13583077707206
root_relative_squared_error
1.3651506743346413
total_cost
0
area_under_roc_curve
0.5377358490566039 [0.823899,0.5,0.5,0.996855,0.5,0.974843,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.496855,0.962264,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.496855,1,1,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.981132,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.930818,0.5,0.5,0.874214]
area_under_roc_curve
0.5314465408805031 [0.874214,0.5,0.5,1,0.5,0.981132,0.5,0.993711,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.946541,0.5,0.5,0.5,0.496855,0.5,0.984277,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.496855,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,0.977987,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.968553,0.943396,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.867925]
area_under_roc_curve
0.5283018867924529 [0.5,0.5,0.5,0.996855,0.5,0.5,0.946541,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.996855,0.5,0.5,0.924528,0.5,0.987421,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.827044,0.5,0.496855,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.90566,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.949686,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0.996855,0.5]
area_under_roc_curve
0.5345911949685533 [0.5,0.5,0.5,0.996855,0.5,0.5,0.90566,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.496855,0.5,0.5,0.889937,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.786164,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,1,1,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.496855,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.965409,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0.496855,0.5]
area_under_roc_curve
0.5283018867924529 [0.5,0.5,0.5,0.5,0.5,0.5,0.987421,0.5,0.974843,0.5,0.5,0.5,0.5,0.449686,1,0.5,0.5,0.5,0.496855,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.981132,0.5,0.5,0.899371,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.981132,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0.836478,0.5,0.5,0.5,0.5,0.5,0.5,0.490566,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.996855,0.5,0.5,0.5,0.5,0.5,0.5,0.937107,0.5,0.5,0.5,0.5,0.496855,0.5]
area_under_roc_curve
0.550314465408805 [0.5,0.5,0.5,0.5,0.5,0.5,0.987421,0.5,0.974843,0.5,0.5,0.5,0.5,0.955975,0.996855,0.5,0.5,0.5,0.993711,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0.984277,0.5,0.5,0.899371,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.984277,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,1,0.5,0.5,0.849057,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.996855,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.990566,0.5,0.5,0.5,0.5,0.5,0.5,0.937107,0.5,0.5,0.5,0.5,0.5,0.5]
area_under_roc_curve
0.5283018867924528 [0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.990566,0.5,0.984277,0.987421,0.5,0.893082,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.496855,0.5,0.5,0.5,0.5,0.987421,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.490566,0.5,0.5,0.5,0.962264,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.827044,0.5,0.5,0.496855,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.91195,0.5,0.5,0.5,0.5,0.5,0.5]
area_under_roc_curve
0.5471698113207547 [0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.990566,0.5,0.987421,0.990566,0.5,0.921384,1,0.5,0.5,0.496855,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.993711,0.5,0.5,0.5,0.5,0.987421,1,1,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,0.974843,0.5,0.5,0.5,0.974843,0.5,0.5,0.5,0.5,0.940252,0.5,0.5,0.5,0.5,0.5,0.861635,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,0.496855,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.930818,0.5,0.5,0.5,0.5,0.5,0.5]
area_under_roc_curve
0.5440251572327044 [0.940252,0.5,0.993711,0.5,0.5,0.987421,0.5,0.5,0.5,1,0.974843,0.990566,0.5,0.5,0.5,0.5,0.996855,0.5,0.5,0.496855,0.5,0.5,0.5,0.5,0.5,0.5,0.493711,0.5,0.5,1,0.5,0.5,0.5,0.996855,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.977987,0.5,0.940252,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.927673,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.940252,0.5,0.5,0.886792]
area_under_roc_curve
0.5283018867924528 [0.874214,0.5,0.5,0.5,0.5,0.984277,0.5,0.5,0.5,0.5,0.974843,0.987421,0.5,0.5,0.5,0.5,0.5,0.496855,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.496855,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.981132,0.5,0.924528,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.496855,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.955975,0.5,0.5,0.855346]
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
0.07547169811320754
kappa
0.06289308176100629
kappa
0.05660377358490566
kappa
0.0691823899371069
kappa
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kappa
0.10062893081761005
kappa
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kappa
0.09433962264150943
kappa
0.0880503144654088
kappa
0.05660377358490566
kb_relative_information_score
12.679186802919855
kb_relative_information_score
10.674821997517387
kb_relative_information_score
9.672639594816188
kb_relative_information_score
11.677004400218612
kb_relative_information_score
9.67263959481618
kb_relative_information_score
16.687916413724732
kb_relative_information_score
9.672639594816184
kb_relative_information_score
15.685734011023515
kb_relative_information_score
14.683551608322285
kb_relative_information_score
9.672639594816184
mean_absolute_error
0.018375000000000013
mean_absolute_error
0.018625000000000013
mean_absolute_error
0.018750000000000013
mean_absolute_error
0.018500000000000013
mean_absolute_error
0.018750000000000013
mean_absolute_error
0.017875000000000012
mean_absolute_error
0.018750000000000013
mean_absolute_error
0.018000000000000013
mean_absolute_error
0.018125000000000013
mean_absolute_error
0.018750000000000013
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
0.08125
predictive_accuracy
0.06875
predictive_accuracy
0.0625
predictive_accuracy
0.075
predictive_accuracy
0.0625
predictive_accuracy
0.10625
predictive_accuracy
0.0625
predictive_accuracy
0.1
predictive_accuracy
0.09375
predictive_accuracy
0.0625
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
0.08125 [1,0,0,1,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,1,0,0,1,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,1]
recall
0.06875 [1,0,0,1,0,1,0,1,0,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1]
recall
0.0625 [0,0,0,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,1,0,0,1,0,1,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1,0,0,1,0]
recall
0.075 [0,0,0,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1,0,1,0,0,0,0,0,0,0,0,0,0,0,0,1,0,1,1,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1,0,0,0,0]
recall
0.0625 [0,0,0,0,0,0,1,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,1,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0]
recall
0.10625 [0,0,0,0,0,0,1,0,1,0,0,0,0,1,1,0,0,0,1,0,0,0,0,0,0,0,0,0,1,0,0,1,0,0,1,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0,0,0,1,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0]
recall
0.0625 [0,0,0,0,0,0,0,0,1,0,1,1,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0]
recall
0.1 [0,0,0,0,0,0,0,0,1,0,1,1,0,1,1,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,1,1,1,0,0,0,0,0,1,0,0,0,0,1,0,0,0,1,0,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0]
recall
0.09375 [1,0,1,0,0,1,0,0,0,1,1,1,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,1,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,1]
recall
0.0625 [1,0,0,0,0,1,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,1]
relative_absolute_error
0.9280303030303021
relative_absolute_error
0.9406565656565649
relative_absolute_error
0.946969696969696
relative_absolute_error
0.9343434343434334
relative_absolute_error
0.946969696969696
relative_absolute_error
0.9027777777777769
relative_absolute_error
0.946969696969696
relative_absolute_error
0.9090909090909082
relative_absolute_error
0.9154040404040396
relative_absolute_error
0.946969696969696
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
0.13555441711725963
root_mean_squared_error
0.13647344063956185
root_mean_squared_error
0.13693063937629157
root_mean_squared_error
0.13601470508735447
root_mean_squared_error
0.13693063937629157
root_mean_squared_error
0.13369741957120942
root_mean_squared_error
0.13693063937629157
root_mean_squared_error
0.13416407864998742
root_mean_squared_error
0.13462912017836265
root_mean_squared_error
0.13693063937629157
root_relative_squared_error
1.3623731522826648
root_relative_squared_error
1.371609686212929
root_relative_squared_error
1.3762047064079501
root_relative_squared_error
1.366999220441207
root_relative_squared_error
1.3762047064079501
root_relative_squared_error
1.3437096247164246
root_relative_squared_error
1.3762047064079501
root_relative_squared_error
1.3483997249264836
root_relative_squared_error
1.3530735681433144
root_relative_squared_error
1.3762047064079501
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
690.8555709999291
usercpu_time_millis
726.5485279998529
usercpu_time_millis
689.4268050000392
usercpu_time_millis
700.340914000094
usercpu_time_millis
712.9545140001028
usercpu_time_millis
711.4427180000575
usercpu_time_millis
719.6485810000013
usercpu_time_millis
705.5477759998894
usercpu_time_millis
712.1909740000092
usercpu_time_millis
709.4018910000841
usercpu_time_millis_testing
88.55834899998172
usercpu_time_millis_testing
88.99092999990899
usercpu_time_millis_testing
88.37833200004752
usercpu_time_millis_testing
94.380787000091
usercpu_time_millis_testing
92.85687500005224
usercpu_time_millis_testing
93.1166980000171
usercpu_time_millis_testing
102.82019999999648
usercpu_time_millis_testing
91.90278899995974
usercpu_time_millis_testing
94.78632100001505
usercpu_time_millis_testing
93.82824000010714
usercpu_time_millis_training
602.2972219999474
usercpu_time_millis_training
637.5575979999439
usercpu_time_millis_training
601.0484729999916
usercpu_time_millis_training
605.960127000003
usercpu_time_millis_training
620.0976390000505
usercpu_time_millis_training
618.3260200000404
usercpu_time_millis_training
616.8283810000048
usercpu_time_millis_training
613.6449869999296
usercpu_time_millis_training
617.4046529999941
usercpu_time_millis_training
615.573650999977