8958538
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)
6894144
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
45.40591292513625
7650
cache_size
200
7650
class_weight
null
7650
coef0
0.5252404138848334
7650
decision_function_shape
"ovr"
7650
degree
3
7650
gamma
0.02140849886882673
7650
kernel
"rbf"
7650
max_iter
-1
7650
probability
false
7650
random_state
1
7650
shrinking
false
7650
tol
0.0012617161310099273
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
18832340
description
https://api.openml.org/data/download/18832340/description.xml
-1
18832341
predictions
https://api.openml.org/data/download/18832341/predictions.arff
area_under_roc_curve
0.9210858585858582 [0.842487,0.96875,1,0.96875,0.937184,0.936553,0.999684,1,0.905934,0.9375,0.967803,0.937184,1,0.90625,0.999053,0.96875,1,0.81029,0.714646,0.620896,0.874053,0.96875,0.998422,1,0.937184,0.715909,0.779356,0.936553,0.937184,1,0.999684,0.96875,0.999369,0.746528,0.937184,0.936869,0.747475,0.717172,0.968434,1,0.935606,0.936869,1,0.936553,0.968434,0.96875,0.968434,0.968119,0.873422,0.936553,0.904672,0.905619,0.937184,0.843119,0.874053,0.809975,1,0.968434,0.903725,0.842487,0.936869,0.968434,0.842803,0.968119,0.968119,0.810922,0.717172,1,0.936869,0.873422,0.874053,0.968434,0.93529,0.96875,0.936553,0.96875,0.968434,0.841856,1,1,0.905934,0.936553,0.905934,0.748737,0.905303,1,1,0.935922,0.937184,1,0.936869,0.999684,0.968434,0.937184,0.96875,0.936869,0.936553,0.905303,0.748737,0.937184]
average_cost
0
f_measure
0.8440670220974889 [0.709677,0.967742,1,0.967742,0.903226,0.848485,0.969697,1,0.866667,0.933333,0.882353,0.903226,1,0.896552,0.914286,0.967742,1,0.606061,0.388889,0.242424,0.774194,0.967742,0.864865,1,0.903226,0.4375,0.580645,0.848485,0.903226,1,0.969697,0.967742,0.941176,0.457143,0.903226,0.875,0.5,0.5,0.9375,1,0.777778,0.875,1,0.848485,0.9375,0.967742,0.9375,0.909091,0.727273,0.848485,0.764706,0.83871,0.903226,0.758621,0.774194,0.588235,1,0.9375,0.702703,0.709677,0.875,0.9375,0.733333,0.909091,0.909091,0.645161,0.5,1,0.875,0.727273,0.774194,0.9375,0.756757,0.967742,0.848485,0.967742,0.9375,0.666667,1,1,0.866667,0.848485,0.866667,0.571429,0.8125,1,1,0.8,0.903226,1,0.875,0.969697,0.9375,0.903226,0.967742,0.875,0.848485,0.8125,0.571429,0.903226]
kappa
0.8421717171717171
kb_relative_information_score
1349.4543993246841
mean_absolute_error
0.0031249999999999885
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
0.8484534852402501 [0.733333,1,1,1,0.933333,0.823529,0.941176,1,0.928571,1,0.833333,0.933333,1,1,0.842105,1,1,0.588235,0.35,0.235294,0.8,1,0.761905,1,0.933333,0.4375,0.6,0.823529,0.933333,1,0.941176,1,0.888889,0.421053,0.933333,0.875,0.5,0.583333,0.9375,1,0.7,0.875,1,0.823529,0.9375,1,0.9375,0.882353,0.705882,0.823529,0.722222,0.866667,0.933333,0.846154,0.8,0.555556,1,0.9375,0.619048,0.733333,0.875,0.9375,0.785714,0.882353,0.882353,0.666667,0.583333,1,0.875,0.705882,0.8,0.9375,0.666667,1,0.823529,1,0.9375,0.647059,1,1,0.928571,0.823529,0.928571,0.666667,0.8125,1,1,0.736842,0.933333,1,0.875,0.941176,0.9375,0.933333,1,0.875,0.823529,0.8125,0.666667,0.933333]
predictive_accuracy
0.84375
prior_entropy
6.6438561897747395
recall
0.84375 [0.6875,0.9375,1,0.9375,0.875,0.875,1,1,0.8125,0.875,0.9375,0.875,1,0.8125,1,0.9375,1,0.625,0.4375,0.25,0.75,0.9375,1,1,0.875,0.4375,0.5625,0.875,0.875,1,1,0.9375,1,0.5,0.875,0.875,0.5,0.4375,0.9375,1,0.875,0.875,1,0.875,0.9375,0.9375,0.9375,0.9375,0.75,0.875,0.8125,0.8125,0.875,0.6875,0.75,0.625,1,0.9375,0.8125,0.6875,0.875,0.9375,0.6875,0.9375,0.9375,0.625,0.4375,1,0.875,0.75,0.75,0.9375,0.875,0.9375,0.875,0.9375,0.9375,0.6875,1,1,0.8125,0.875,0.8125,0.5,0.8125,1,1,0.875,0.875,1,0.875,1,0.9375,0.875,0.9375,0.875,0.875,0.8125,0.5,0.875]
relative_absolute_error
0.15782828282828196
root_mean_prior_squared_error
0.09949874371066209
root_mean_squared_error
0.05590169943749464
root_relative_squared_error
0.5618332187193669
total_cost
0
area_under_roc_curve
0.9148555051349417 [0.996855,0.75,1,1,0.75,1,1,1,1,1,0.75,1,1,1,1,0.5,1,0.75,0.496835,0.987421,0.5,1,0.996855,1,1,0.743671,0.75,0.996835,1,1,1,1,0.996835,0.496835,1,0.996855,1,0.996855,1,1,0.996855,0.996855,1,1,1,1,1,0.996855,1,0.75,1,1,1,1,0.996855,0.496855,1,1,1,1,1,1,0.75,1,1,1,0.5,1,1,0.5,0.75,1,1,1,1,1,0.75,0.5,1,1,1,1,1,0.996855,1,1,1,0.996835,0.75,1,0.996835,1,1,0.996835,1,0.75,0.496855,0.993671,0.496835,1]
area_under_roc_curve
0.9179006448531165 [1,1,1,1,1,1,0.996835,1,1,1,1,1,1,0.75,1,1,1,0.75,0.75,0.487421,1,1,0.996855,1,1,0.75,0.493671,1,0.996835,1,1,1,1,0.990506,0.75,0.5,0.496855,0.5,1,1,1,1,1,0.75,1,1,1,1,0.746835,0.996835,0.993671,1,1,0.75,1,0.496855,1,1,1,0.5,1,1,0.75,1,1,0.75,0.75,1,1,1,0.996835,1,1,1,1,1,1,0.993671,1,1,0.75,0.996835,0.996855,1,0.746835,1,1,0.996835,0.75,1,1,1,1,0.75,1,1,1,1,0.75,0.496855]
area_under_roc_curve
0.9463816575113443 [1,1,1,1,1,0.996835,1,1,1,1,1,0.75,1,1,1,1,1,0.996835,1,0.5,1,1,1,1,1,0.746835,1,0.996855,1,1,1,1,1,0.75,0.996855,1,0.993711,1,1,1,0.746835,0.5,1,1,0.996835,1,0.75,1,0.75,1,1,1,1,1,1,1,1,1,0.993711,0.496835,1,1,0.75,0.5,1,1,1,1,1,0.75,1,0.996835,1,1,0.993711,1,1,0.996835,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,0.75,0.996855,1]
area_under_roc_curve
0.9084865854629406 [0.5,1,1,1,0.75,0.75,1,1,0.746835,1,1,0.75,1,1,1,1,1,0.743671,0.493711,0.75,1,1,0.993671,1,0.5,0.75,1,1,1,1,1,1,1,0.746835,1,1,0.996855,0.5,1,1,0.996835,0.996855,1,0.996855,1,1,1,1,0.996835,1,0.996835,1,1,0.75,1,0.993671,1,1,0.996855,1,0.996855,1,1,1,0.75,0.5,0.493671,1,1,0.743671,0.5,1,0.990566,1,0.996855,1,1,0.75,1,1,1,1,0.75,0.75,0.5,1,1,1,1,1,0.75,1,1,1,1,0.996855,0.75,0.996835,0.996855,0.75]
area_under_roc_curve
0.9115516280550912 [0.746835,1,1,1,1,0.75,1,1,1,1,0.996835,1,1,0.5,0.996855,1,1,0.746835,0.990566,0.743671,0.75,1,1,1,1,0.990506,0.75,1,1,1,1,0.5,1,0.496835,1,1,0.746835,0.5,1,1,0.746835,1,1,0.5,1,1,1,1,1,1,0.496855,0.496855,0.75,0.996855,0.496835,0.5,1,0.996835,0.993671,1,1,1,0.5,1,1,1,1,1,0.75,0.996835,0.996835,1,1,1,0.75,1,0.996835,0.996835,1,1,1,1,1,0.75,0.996855,1,1,1,1,1,1,1,1,1,0.75,1,0.996835,1,0.5,1]
area_under_roc_curve
0.921025396067192 [0.75,1,1,1,1,1,1,1,1,0.75,1,0.996835,1,1,1,1,1,1,0.996855,0.5,0.75,0.75,0.996835,1,0.996835,0.743671,0.746835,0.5,1,1,1,1,1,0.746835,1,0.75,0.75,0.743671,1,1,0.996835,1,1,0.996855,1,1,1,1,0.75,0.75,1,1,1,1,0.996835,0.993671,1,1,0.75,0.996855,1,0.75,0.996855,1,1,0.75,1,1,0.996835,1,0.75,1,0.996855,1,0.75,1,1,0.746835,1,1,0.996855,0.746835,0.75,0.746835,1,1,1,0.996855,0.996835,1,1,1,1,1,1,1,1,1,0.5,1]
area_under_roc_curve
0.9242297587771674 [1,1,1,1,0.996855,1,1,1,1,1,1,1,1,1,1,1,1,1,0.496835,0.5,0.993671,1,1,1,1,0.5,0.493711,0.75,1,1,0.996835,1,1,0.996855,1,1,0.493671,0.746835,0.996835,1,1,0.75,1,1,0.5,0.75,1,0.996835,0.996855,0.996855,1,1,0.996835,0.5,1,0.75,1,1,0.5,1,0.996835,0.996835,0.996855,0.996835,1,0.496855,0.996855,1,1,1,1,1,0.996835,1,1,1,1,1,1,1,0.75,1,1,0.996835,1,1,1,0.5,1,1,1,1,0.75,1,1,0.75,1,1,0.5,1]
area_under_roc_curve
0.9305588727012181 [0.75,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.996855,0.984177,0.5,0.75,1,1,1,0.75,0.5,1,1,0.5,1,1,1,0.996855,1,1,1,0.5,0.746835,1,1,1,1,1,1,1,1,1,0.75,0.996855,1,0.996855,0.75,0.75,0.996855,1,0.746835,1,1,0.996835,0.993711,1,1,1,1,1,0.496855,0.5,1,1,0.746835,1,1,0.996835,1,1,1,1,0.5,1,1,0.75,1,0.75,0.75,0.75,1,1,0.996855,1,1,1,1,0.996835,1,1,0.996835,1,1,0.996835,1]
area_under_roc_curve
0.9369277923732187 [0.996855,1,1,0.75,1,0.996855,1,1,0.75,1,1,1,1,1,0.996835,1,1,0.493711,0.75,0.496855,0.996835,1,1,1,1,0.5,0.996855,1,1,1,1,1,1,0.996855,1,1,1,0.5,0.75,1,1,1,1,0.996835,1,1,0.996855,1,0.5,1,0.75,0.996835,1,0.75,0.75,1,1,0.5,0.996835,1,0.75,1,1,0.996835,1,0.996855,0.743671,1,0.996835,1,0.996855,1,0.75,1,1,1,1,0.996855,1,1,1,1,1,0.5,1,1,1,1,1,1,0.75,1,1,1,1,1,1,1,0.75,1]
area_under_roc_curve
0.8991521375686651 [0.996855,1,1,1,1,0.996855,1,1,0.75,0.5,0.993711,1,1,0.75,0.996835,1,1,0.5,0.5,0.993711,1,1,1,1,1,0.496855,0.5,0.996835,0.75,1,1,1,1,0.493711,0.75,0.996835,0.746835,1,1,1,0.996855,1,1,1,1,1,1,1,0.996855,0.996855,0.75,0.75,1,0.75,0.75,0.996855,1,1,0.996835,0.75,0.75,1,0.746835,1,0.993711,0.993711,0.5,1,0.75,0.996855,1,0.5,0.746835,0.75,1,0.75,1,1,1,1,1,0.496855,1,0.496855,0.996835,1,1,0.746835,1,1,0.996835,0.996835,1,0.75,1,1,0.996855,0.5,1,1]
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
0.8294512435846823
kappa
0.8357224657426056
kappa
0.8926047301299009
kappa
0.8168107702633345
kappa
0.8230717586193278
kappa
0.8420533070088845
kappa
0.8483591991470205
kappa
0.8610014215763703
kappa
0.8736426456071076
kappa
0.7978920775273359
kb_relative_information_score
132.94107512706694
kb_relative_information_score
133.94325752976818
kb_relative_information_score
142.96289915407914
kb_relative_information_score
130.93671032166446
kb_relative_information_score
131.9388927243657
kb_relative_information_score
134.94543993246936
kb_relative_information_score
135.9476223351706
kb_relative_information_score
137.951987140573
kb_relative_information_score
139.95635194597548
kb_relative_information_score
127.93016311356081
mean_absolute_error
0.003375000000000001
mean_absolute_error
0.0032500000000000007
mean_absolute_error
0.002125
mean_absolute_error
0.003625000000000001
mean_absolute_error
0.003500000000000001
mean_absolute_error
0.0031250000000000006
mean_absolute_error
0.003000000000000001
mean_absolute_error
0.0027500000000000007
mean_absolute_error
0.0025000000000000005
mean_absolute_error
0.004000000000000002
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
0.83125
predictive_accuracy
0.8375
predictive_accuracy
0.89375
predictive_accuracy
0.81875
predictive_accuracy
0.825
predictive_accuracy
0.84375
predictive_accuracy
0.85
predictive_accuracy
0.8625
predictive_accuracy
0.875
predictive_accuracy
0.8
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
0.83125 [1,0.5,1,1,0.5,1,1,1,1,1,0.5,1,1,1,1,0,1,0.5,0,1,0,1,1,1,1,0.5,0.5,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,0,1,1,1,1,1,1,0.5,1,1,1,0,1,1,0,0.5,1,1,1,1,1,0.5,0,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,0.5,0,1,0,1]
recall
0.8375 [1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0.5,0.5,0,1,1,1,1,1,0.5,0,1,1,1,1,1,1,1,0.5,0,0,0,1,1,1,1,1,0.5,1,1,1,1,0.5,1,1,1,1,0.5,1,0,1,1,1,0,1,1,0.5,1,1,0.5,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0.5,1,1,1,0.5,1,1,1,1,0.5,1,1,1,1,0.5,0]
recall
0.89375 [1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,0,1,1,1,1,1,0.5,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,0.5,0,1,1,1,1,0.5,1,0.5,1,1,1,1,1,1,1,1,1,1,0,1,1,0.5,0,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1]
recall
0.81875 [0,1,1,1,0.5,0.5,1,1,0.5,1,1,0.5,1,1,1,1,1,0.5,0,0.5,1,1,1,1,0,0.5,1,1,1,1,1,1,1,0.5,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,0.5,0,0,1,1,0.5,0,1,1,1,1,1,1,0.5,1,1,1,1,0.5,0.5,0,1,1,1,1,1,0.5,1,1,1,1,1,0.5,1,1,0.5]
recall
0.825 [0.5,1,1,1,1,0.5,1,1,1,1,1,1,1,0,1,1,1,0.5,1,0.5,0.5,1,1,1,1,1,0.5,1,1,1,1,0,1,0,1,1,0.5,0,1,1,0.5,1,1,0,1,1,1,1,1,1,0,0,0.5,1,0,0,1,1,1,1,1,1,0,1,1,1,1,1,0.5,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0,1]
recall
0.84375 [0.5,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,0,0.5,0.5,1,1,1,0.5,0.5,0,1,1,1,1,1,0.5,1,0.5,0.5,0.5,1,1,1,1,1,1,1,1,1,1,0.5,0.5,1,1,1,1,1,1,1,1,0.5,1,1,0.5,1,1,1,0.5,1,1,1,1,0.5,1,1,1,0.5,1,1,0.5,1,1,1,0.5,0.5,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1]
recall
0.85 [1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,0,0,0.5,1,1,1,1,1,1,1,1,0,0.5,1,1,1,0.5,1,1,0,0.5,1,1,1,1,1,1,1,0,1,0.5,1,1,0,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,0,1,1,1,1,0.5,1,1,0.5,1,1,0,1]
recall
0.8625 [0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0.5,1,1,1,0.5,0,1,1,0,1,1,1,1,1,1,1,0,0.5,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0.5,0.5,1,1,0.5,1,1,1,1,1,1,1,1,1,0,0,1,1,0.5,1,1,1,1,1,1,1,0,1,1,0.5,1,0.5,0.5,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1]
recall
0.875 [1,1,1,0.5,1,1,1,1,0.5,1,1,1,1,1,1,1,1,0,0.5,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,0,0.5,1,1,1,1,1,1,1,1,1,0,1,0.5,1,1,0.5,0.5,1,1,0,1,1,0.5,1,1,1,1,1,0.5,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,0.5,1]
recall
0.8 [1,1,1,1,1,1,1,1,0.5,0,1,1,1,0.5,1,1,1,0,0,1,1,1,1,1,1,0,0,1,0.5,1,1,1,1,0,0.5,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,0.5,1,0.5,0.5,1,1,1,1,0.5,0.5,1,0.5,1,1,1,0,1,0.5,1,1,0,0.5,0.5,1,0.5,1,1,1,1,1,0,1,0,1,1,1,0.5,1,1,1,1,1,0.5,1,1,1,0,1,1]
relative_absolute_error
0.17045454545454522
relative_absolute_error
0.1641414141414139
relative_absolute_error
0.10732323232323215
relative_absolute_error
0.18308080808080782
relative_absolute_error
0.17676767676767655
relative_absolute_error
0.1578282828282826
relative_absolute_error
0.1515151515151513
relative_absolute_error
0.1388888888888887
relative_absolute_error
0.12626262626262608
relative_absolute_error
0.2020202020202018
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
0.058094750193111264
root_mean_squared_error
0.0570087712549569
root_mean_squared_error
0.046097722286464436
root_mean_squared_error
0.06020797289396149
root_mean_squared_error
0.05916079783099617
root_mean_squared_error
0.05590169943749475
root_mean_squared_error
0.05477225575051662
root_mean_squared_error
0.052440442408507586
root_mean_squared_error
0.05
root_mean_squared_error
0.0632455532033676
root_relative_squared_error
0.5838742081211419
root_relative_squared_error
0.5729597091269403
root_relative_squared_error
0.46329954095214076
root_relative_squared_error
0.6051128953853288
root_relative_squared_error
0.5945883900105629
root_relative_squared_error
0.5618332187193681
root_relative_squared_error
0.5504818825631801
root_relative_squared_error
0.5270462766947296
root_relative_squared_error
0.5025189076296057
root_relative_squared_error
0.6356417261637279
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
558.0472579999878
usercpu_time_millis
586.1958300001788
usercpu_time_millis
567.1064400000887
usercpu_time_millis
574.6081539998613
usercpu_time_millis
566.3797490001343
usercpu_time_millis
568.4598399998322
usercpu_time_millis
573.477862000118
usercpu_time_millis
585.8835690000888
usercpu_time_millis
603.883931999917
usercpu_time_millis
574.5044200000393
usercpu_time_millis_testing
53.63547899992227
usercpu_time_millis_testing
53.19604500004971
usercpu_time_millis_testing
55.23809900000742
usercpu_time_millis_testing
53.79492399993069
usercpu_time_millis_testing
53.49585700014359
usercpu_time_millis_testing
53.306516000020565
usercpu_time_millis_testing
55.678645000170945
usercpu_time_millis_testing
55.6918920001408
usercpu_time_millis_testing
55.18424399997457
usercpu_time_millis_testing
54.63690900000984
usercpu_time_millis_training
504.4117790000655
usercpu_time_millis_training
532.9997850001291
usercpu_time_millis_training
511.8683410000813
usercpu_time_millis_training
520.8132299999306
usercpu_time_millis_training
512.8838919999907
usercpu_time_millis_training
515.1533239998116
usercpu_time_millis_training
517.799216999947
usercpu_time_millis_training
530.191676999948
usercpu_time_millis_training
548.6996879999424
usercpu_time_millis_training
519.8675110000295