5973898
1
Jan van Rijn
9954
Supervised Classification
6969
sklearn.pipeline.Pipeline(imputation=openmlstudy14.preprocessing.ConditionalImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,variencethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,classifier=sklearn.ensemble.forest.RandomForestClassifier)(1)
4008631
bootstrap
false
6902
class_weight
null
6902
criterion
"entropy"
6902
max_depth
null
6902
max_features
0.22700344580582563
6902
max_leaf_nodes
null
6902
min_impurity_split
1e-07
6902
min_samples_leaf
18
6902
min_samples_split
19
6902
min_weight_fraction_leaf
0.0
6902
n_estimators
100
6902
n_jobs
1
6902
oob_score
false
6902
random_state
36699
6902
verbose
0
6902
warm_start
false
6902
axis
0
6947
categorical_features
[]
6947
copy
true
6947
fill_empty
0
6947
missing_values
"NaN"
6947
strategy
"most_frequent"
6947
strategy_nominal
"most_frequent"
6947
verbose
0
6947
categorical_features
[]
6948
dtype
{"oml-python:serialized_object": "type", "value": "np.float64"}
6948
handle_unknown
"ignore"
6948
n_values
"auto"
6948
sparse
false
6948
threshold
0.0
6949
openml-pimp
openml-python
Sklearn_0.18.1.
study_71
1491
one-hundred-plants-margin
https://www.openml.org/data/download/1592283/phpCsX3fx
-1
12871155
description
https://api.openml.org/data/download/12871155/description.xml
-1
12871156
predictions
https://api.openml.org/data/download/12871156/predictions.arff
area_under_roc_curve
0.9941279987373739 [0.984848,0.999487,0.999605,1,0.998185,0.993963,0.999645,0.999408,0.994752,0.999605,0.994752,1,0.99712,0.982363,0.999329,0.998935,0.999763,0.985953,0.987926,0.972104,0.998067,0.999566,0.993766,1,0.996804,0.965002,0.985874,0.997751,0.994831,0.999448,0.999961,1,0.998698,0.987492,0.998224,0.998067,0.992148,0.992661,0.998777,0.999645,0.997435,0.998737,0.999684,0.998146,0.998264,0.999408,0.999053,0.994515,0.996133,0.996252,0.995975,0.992779,0.996883,0.986072,0.994279,0.974116,1,0.999961,0.994239,0.979995,0.999921,0.998658,0.991477,0.998777,0.998737,0.993529,0.974787,1,0.988084,0.981218,0.992977,0.997001,0.993174,0.998303,0.966974,0.998856,0.999014,0.979324,0.999921,0.999092,0.989938,0.995857,0.994476,0.995265,0.996646,0.995344,0.999684,0.992898,0.996725,1,1,0.998856,0.998303,0.989228,0.99858,0.999329,0.995344,0.995107,0.957781,0.997159]
average_cost
0
f_measure
0.7145007979240531 [0.64,0.842105,0.969697,1,0.857143,0.5,0.857143,0.833333,0.571429,0.888889,0.666667,0.882353,0.705882,0.5,0.941176,0.896552,0.842105,0.384615,0.526316,0.307692,0.75,1,0.733333,1,0.75,0.222222,0.322581,0.681818,0.866667,0.8,0.864865,1,0.848485,0.413793,0.866667,0.652174,0.484848,0.578947,0.882353,0.761905,0.606061,0.909091,0.842105,0.733333,0.909091,0.8,0.875,0.740741,0.774194,0.83871,0.666667,0.6875,0.787879,0.5,0.689655,0.1,1,0.914286,0.648649,0.583333,0.857143,0.722222,0.3,0.857143,0.8,0.551724,0.296296,0.914286,0.363636,0.545455,0.642857,0.697674,0.619048,0.875,0.64,0.857143,0.777778,0.210526,0.888889,0.866667,0.521739,0.733333,0.714286,0.642857,0.742857,0.875,0.888889,0.666667,0.833333,1,0.857143,0.714286,0.785714,0.47619,0.742857,0.777778,0.8125,0.647059,0.210526,0.823529]
kappa
0.7316919191919192
kb_relative_information_score
982.9490468876497
mean_absolute_error
0.0161423782713436
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
0.7481961661265402 [0.888889,0.727273,0.941176,1,0.789474,0.5,0.789474,0.75,0.666667,0.8,0.714286,0.833333,0.666667,0.75,0.888889,1,0.727273,0.5,0.454545,0.4,0.625,1,0.785714,1,0.75,1,0.333333,0.535714,0.928571,0.666667,0.761905,1,0.823529,0.461538,0.928571,0.5,0.470588,0.5,0.833333,0.615385,0.588235,0.882353,0.727273,0.785714,0.882353,0.736842,0.875,0.909091,0.8,0.866667,0.714286,0.6875,0.764706,0.75,0.769231,0.25,1,0.842105,0.571429,0.875,0.789474,0.65,0.75,0.789474,0.666667,0.615385,0.363636,0.842105,0.666667,1,0.75,0.555556,0.5,0.875,0.888889,1,0.7,0.666667,0.8,0.928571,0.857143,0.785714,0.833333,0.75,0.684211,0.875,0.8,0.565217,0.75,1,0.789474,0.576923,0.916667,1,0.684211,0.7,0.8125,0.611111,0.666667,0.777778]
predictive_accuracy
0.734375
prior_entropy
6.6438561897747395
recall
0.734375 [0.5,1,1,1,0.9375,0.5,0.9375,0.9375,0.5,1,0.625,0.9375,0.75,0.375,1,0.8125,1,0.3125,0.625,0.25,0.9375,1,0.6875,1,0.75,0.125,0.3125,0.9375,0.8125,1,1,1,0.875,0.375,0.8125,0.9375,0.5,0.6875,0.9375,1,0.625,0.9375,1,0.6875,0.9375,0.875,0.875,0.625,0.75,0.8125,0.625,0.6875,0.8125,0.375,0.625,0.0625,1,1,0.75,0.4375,0.9375,0.8125,0.1875,0.9375,1,0.5,0.25,1,0.25,0.375,0.5625,0.9375,0.8125,0.875,0.5,0.75,0.875,0.125,1,0.8125,0.375,0.6875,0.625,0.5625,0.8125,0.875,1,0.8125,0.9375,1,0.9375,0.9375,0.6875,0.3125,0.8125,0.875,0.8125,0.6875,0.125,0.875]
relative_absolute_error
0.8152716298658368
root_mean_prior_squared_error
0.09949874371066209
root_mean_squared_error
0.08406069575270954
root_relative_squared_error
0.8448417800847244
total_cost
0
area_under_roc_curve
0.9926866889578857 [0.993711,1,1,1,0.996835,1,1,1,0.993671,1,0.993671,1,1,0.987342,1,1,1,0.974684,0.974684,0.987421,1,1,1,1,1,0.990506,0.987342,1,0.974684,0.987421,1,1,1,0.993671,1,0.993711,1,0.993711,1,0.996835,1,1,1,1,1,1,1,1,1,0.977848,0.990506,1,0.993711,1,0.993711,1,1,1,0.987421,0.981013,1,1,0.990506,1,1,0.996835,0.987342,1,1,0.962264,0.990506,0.993711,1,1,1,1,1,0.96519,1,1,0.996835,1,0.993711,1,0.996835,0.968354,1,0.996835,0.990506,1,1,1,1,0.987342,1,0.996835,1,1,0.797468,1]
area_under_roc_curve
0.9936007284451873 [0.981132,1,1,1,1,1,1,1,1,1,0.996835,1,0.987342,0.949367,1,1,1,0.981013,0.993671,0.987421,1,0.993711,1,1,1,0.955696,0.987342,0.993671,1,1,1,1,1,1,0.996835,0.993711,0.981132,1,1,1,1,1,1,1,1,1,1,1,0.996835,1,1,0.971519,1,1,1,0.968553,1,1,1,0.914557,1,1,0.993671,0.993671,1,0.993671,0.993671,1,0.91195,1,1,1,0.996835,1,1,1,1,0.974684,1,0.990506,0.993671,0.996835,0.968553,0.987421,1,1,0.996835,0.996835,0.996835,1,1,1,1,0.977848,1,1,1,0.987342,0.993671,1]
area_under_roc_curve
0.9938330944988454 [1,1,1,1,0.984177,0.996835,1,1,0.987342,1,1,1,1,0.993671,0.996835,1,1,0.990506,0.993711,0.908228,0.993711,1,0.962025,1,0.987421,0.984177,1,1,0.993671,1,1,1,0.996835,0.981013,0.993711,1,0.993711,0.993711,1,1,1,1,1,1,0.993671,1,0.996835,1,0.984177,1,1,1,1,1,1,0.996835,1,1,0.987421,0.971519,1,1,1,1,1,0.984177,0.977848,1,0.981132,0.958861,1,0.993671,0.993711,1,1,1,1,0.968354,1,1,1,0.993671,0.996835,1,1,1,1,1,0.993671,1,1,1,1,0.990506,1,1,0.993671,0.987342,0.981132,1]
area_under_roc_curve
0.9938348360003184 [0.996835,1,1,1,0.996835,0.990506,1,1,0.993671,1,0.987342,1,1,0.990506,1,1,1,0.996835,0.937107,0.993671,1,1,1,1,0.993711,0.946203,0.968354,1,1,1,1,1,1,0.993671,1,0.993711,1,1,1,1,0.996835,1,1,1,1,1,1,1,1,1,1,1,1,0.971519,1,0.990506,1,1,1,0.987342,1,1,0.996835,1,0.996835,0.993671,0.939873,1,1,0.939873,0.990506,0.993671,0.987421,1,0.993711,0.996835,1,0.981013,1,1,0.981132,0.993671,1,0.993671,1,1,1,1,1,1,1,1,0.993711,0.993671,1,0.993711,0.990506,1,0.981132,0.977848]
area_under_roc_curve
0.9916263633468672 [0.993671,1,1,1,1,0.996835,1,1,1,0.996835,0.993671,1,1,0.91195,1,1,1,0.996835,1,0.987342,0.977848,1,1,1,0.993671,0.952532,0.987342,1,1,1,1,1,1,0.968354,1,1,0.990506,0.990506,1,1,0.996835,1,1,1,1,1,1,0.993671,1,1,0.993711,0.981132,0.996835,0.987421,0.974684,0.962025,1,0.996835,0.993671,0.993711,1,1,0.993711,1,1,1,0.91195,1,0.974684,0.987342,1,1,0.987421,0.993711,0.822785,1,0.993671,0.990506,1,1,1,1,1,0.993671,0.981132,1,1,1,1,1,1,0.996835,1,0.981132,0.993671,1,0.996835,1,0.968553,0.996835]
area_under_roc_curve
0.993913203566595 [0.958861,1,1,1,1,0.987342,1,1,1,1,0.996835,1,1,0.987421,1,1,1,1,1,0.917722,1,1,0.993671,1,1,0.984177,0.971519,1,1,1,1,1,0.984177,0.990506,0.987421,0.996835,0.987342,1,1,1,1,1,1,1,0.993711,1,1,0.996835,0.990506,0.990506,1,1,1,1,0.981013,0.958861,1,1,0.993671,1,1,1,0.981132,1,1,1,0.981132,1,0.996835,1,0.96519,0.990506,1,1,0.977848,1,1,0.977848,1,1,1,0.996835,1,0.996835,1,1,1,0.987421,1,1,1,0.996835,1,1,1,1,1,0.974843,0.981132,0.996835]
area_under_roc_curve
0.9955420050155241 [1,1,1,1,1,1,1,1,0.987421,1,1,1,0.981013,1,1,1,1,0.993711,0.993671,0.981013,1,0.996835,1,1,0.996835,0.880503,0.987421,0.993671,1,1,1,1,1,0.974843,1,1,1,1,1,1,1,0.993671,1,1,1,0.993671,0.996835,0.987342,1,1,1,0.996835,1,1,0.993671,0.987342,1,1,0.993671,0.993711,0.996835,1,1,0.984177,1,0.993711,0.962264,1,0.996835,1,1,1,1,1,1,1,1,0.981132,1,1,0.981013,1,0.990506,1,1,1,1,0.943396,1,1,1,1,0.993671,1,1,1,1,1,0.96519,1]
area_under_roc_curve
0.9953402396306028 [1,1,1,1,1,0.996835,1,1,0.993711,1,0.993711,1,1,1,1,0.993671,1,0.981132,0.993671,0.990506,1,1,1,1,0.993671,0.962264,0.987421,0.996835,1,0.996835,1,1,1,0.993711,1,1,0.987342,0.987342,1,1,1,1,1,1,1,1,1,0.987342,1,1,0.981132,1,0.987342,1,0.996835,0.955696,1,1,0.993671,1,1,0.993671,1,1,1,0.974843,0.974843,1,0.987342,0.987342,1,1,1,0.993711,0.996835,1,1,0.987421,1,1,0.962025,1,0.990506,1,0.993671,0.996835,1,0.993711,0.993711,1,1,0.996835,1,0.987421,1,1,0.984177,1,0.981013,1]
area_under_roc_curve
0.9965655103096888 [0.981132,0.996835,1,1,1,0.987421,1,1,1,1,0.981132,1,1,1,1,0.993711,1,1,1,1,1,1,0.993711,1,1,1,0.993711,1,1,1,1,1,1,0.993711,1,1,0.990506,0.984177,1,1,1,0.996835,1,0.993671,1,1,1,0.987342,0.993711,1,1,0.993671,0.996835,0.96519,0.990506,0.943396,1,1,0.993671,0.987342,1,1,1,1,1,1,1,1,0.996835,0.987421,1,0.987421,0.981013,1,0.996835,0.993671,1,1,1,0.996835,0.990506,0.993711,1,1,0.996835,1,1,0.993671,1,1,1,0.993671,1,1,1,1,0.993711,1,0.996835,1]
area_under_roc_curve
0.9965682469548602 [0.930818,1,1,1,1,1,1,0.987421,0.996835,1,0.993711,1,1,0.990506,1,1,1,0.974843,0.990506,0.981132,1,1,1,1,1,0.981132,1,1,0.993671,1,1,1,1,0.987421,0.996835,1,0.993671,1,0.996835,1,1,1,1,1,1,1,1,0.987342,1,0.987421,1,0.990506,1,0.984177,1,1,1,1,0.993671,0.996835,1,1,0.977848,1,0.993711,0.993711,0.996835,1,1,1,1,1,0.993671,1,0.996835,1,1,1,0.993711,1,1,0.981132,1,0.981132,0.996835,1,0.996835,0.981013,1,1,1,1,1,0.996835,1,1,0.987421,1,1,1]
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
0.7032125661062436
kappa
0.7221016066000868
kappa
0.7158642462509865
kappa
0.7157296272899558
kappa
0.7220467466835123
kappa
0.6967303743484441
kappa
0.7725567620927937
kappa
0.7852094602598018
kappa
0.7473152242577384
kappa
0.7346390775548887
kb_relative_information_score
97.76687867394325
kb_relative_information_score
97.56958812854108
kb_relative_information_score
97.31929406137246
kb_relative_information_score
97.75632139428023
kb_relative_information_score
97.72562217665259
kb_relative_information_score
97.84018573363954
kb_relative_information_score
99.52776634420519
kb_relative_information_score
98.83950448892669
kb_relative_information_score
99.2595799558578
kb_relative_information_score
99.3443059302302
mean_absolute_error
0.016147939825121187
mean_absolute_error
0.01618704544149556
mean_absolute_error
0.016222014503732774
mean_absolute_error
0.016192894075305442
mean_absolute_error
0.016127438155071703
mean_absolute_error
0.01617162201968055
mean_absolute_error
0.016026595780776177
mean_absolute_error
0.016085233111179955
mean_absolute_error
0.0161319434032951
mean_absolute_error
0.016131056397777496
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
0.70625
predictive_accuracy
0.725
predictive_accuracy
0.71875
predictive_accuracy
0.71875
predictive_accuracy
0.725
predictive_accuracy
0.7
predictive_accuracy
0.775
predictive_accuracy
0.7875
predictive_accuracy
0.75
predictive_accuracy
0.7375
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
0.70625 [1,1,1,1,1,1,1,1,0,1,0.5,1,1,0,1,1,1,0,0.5,1,1,1,0,1,1,0,0,1,0.5,1,1,1,0.5,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,0.5,0.5,0.5,1,0,1,0,1,1,0,0.5,1,1,0,1,1,0.5,0.5,1,0,0,0,1,1,1,1,1,0.5,0,1,1,0,1,0,1,1,0.5,1,1,0.5,1,1,1,1,0.5,0.5,0.5,1,1,0,1]
recall
0.725 [0,1,1,1,1,1,0.5,1,0.5,1,0.5,1,0.5,0.5,1,1,1,0,0.5,1,1,1,1,1,1,0,0,1,1,1,1,1,1,0.5,0.5,1,0,1,1,1,1,1,1,0.5,0.5,1,1,1,0.5,1,1,0.5,1,1,1,0,1,1,1,0.5,1,1,0.5,1,1,0.5,0.5,1,0,0,1,1,1,1,0,1,0.5,0,1,0.5,0,1,0,0,1,1,1,1,1,1,1,1,0.5,0,0.5,1,1,0,0,1]
recall
0.71875 [0.5,1,1,1,0.5,0.5,1,1,0,1,0.5,1,1,0.5,1,0.5,1,0.5,0,0,1,1,0.5,1,1,0.5,0.5,1,1,1,1,1,1,0,1,1,1,0,1,1,0,1,1,1,1,1,0.5,1,0.5,1,1,1,1,0.5,1,0,1,1,1,0,1,1,0,1,1,0.5,0.5,1,0,0.5,0.5,1,0,1,1,1,1,0,1,1,1,0.5,0.5,0.5,1,1,1,1,1,1,1,1,1,0,1,1,0.5,0.5,0,1]
recall
0.71875 [0.5,1,1,1,1,0,1,1,0.5,1,1,1,1,0.5,1,1,1,0.5,0,0.5,1,1,0.5,1,0,0,0,1,1,1,1,1,1,0,1,1,1,1,1,1,0.5,1,1,1,1,1,0.5,1,1,1,0.5,1,1,0,1,0.5,1,1,0,0.5,1,1,0,1,1,0.5,0,1,0,0,0,1,1,1,0,0.5,1,0.5,1,0.5,1,0.5,1,1,1,1,1,0.5,1,1,1,1,0,1,1,0,0.5,1,0,0.5]
recall
0.725 [0.5,1,1,1,1,0.5,1,1,1,1,1,0.5,1,0,1,1,1,0.5,0,0,0.5,1,1,1,0.5,0,0.5,1,1,1,1,1,1,0,1,1,1,0.5,1,1,1,1,1,0,1,1,1,0,1,0.5,0,0,0.5,0,0,0,1,1,1,1,1,1,0,1,1,0,0,1,0,0.5,1,1,0,0,0.5,1,1,0,1,1,1,1,0.5,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1]
recall
0.7 [0,1,1,1,1,0.5,1,1,0,1,0,1,1,1,1,1,1,0,1,0,1,1,0.5,1,1,0.5,0.5,1,1,1,1,1,0.5,1,0,0.5,0.5,1,1,1,1,1,1,1,1,1,1,0,0.5,0.5,1,1,1,1,0,0,1,1,0,1,1,0.5,0,1,1,0.5,0,1,0,0.5,0.5,1,1,1,0.5,0,1,0,1,1,1,0,1,0.5,0,1,1,1,1,1,1,1,0,0,1,1,1,0,0,0.5]
recall
0.775 [1,1,1,1,1,0.5,1,1,1,1,1,1,0.5,0,1,1,1,0,1,0.5,1,1,1,1,0.5,0,0,0.5,1,1,1,1,1,1,1,1,0.5,1,1,1,0.5,0.5,1,0.5,1,0.5,1,0.5,1,1,0,1,1,0,1,0,1,1,1,0,0.5,0.5,1,0.5,1,1,0,1,0.5,0.5,1,1,1,1,1,1,1,0,1,1,0.5,1,0.5,0.5,1,1,1,0,1,1,1,1,0,0,1,1,1,1,0,1]
recall
0.7875 [0.5,1,1,1,1,0,1,1,1,1,1,1,0.5,0,1,0.5,1,1,1,0,1,1,0.5,1,1,0,1,1,1,1,1,1,1,1,1,1,0.5,0.5,1,1,0.5,1,1,0,1,1,1,1,1,1,0,1,0.5,1,0.5,0,1,1,1,1,1,0.5,1,1,1,0,1,1,0.5,1,0,1,1,1,1,1,1,0,1,1,0,1,0.5,1,0.5,0.5,1,1,1,1,1,1,1,0,1,1,0.5,1,0,1]
recall
0.75 [1,1,1,1,1,1,1,1,0.5,1,0,1,1,0.5,1,0,1,1,1,0,1,1,1,1,0.5,0,0,1,1,1,1,1,1,1,0.5,1,0.5,0,1,1,0,1,1,1,1,1,1,0.5,0,1,1,0.5,1,0.5,0.5,0,1,1,1,0,1,1,0,1,1,1,0,1,0.5,0,1,1,0.5,0.5,0,0.5,1,1,1,0.5,0,1,1,1,1,1,1,1,1,1,1,0.5,1,0,0,1,1,1,0.5,1]
recall
0.7375 [0,1,1,1,1,1,1,0,1,1,1,1,0.5,0.5,1,1,1,0,0.5,0,1,1,1,1,1,0,1,1,0,1,1,1,1,0,1,1,0,1,0.5,1,1,1,1,1,1,0.5,1,1,1,1,0.5,0.5,0.5,0,1,0,1,1,1,0.5,1,1,0,1,1,1,0,1,0.5,0,1,0,1,1,0,0.5,1,0,1,1,0.5,0,1,0,0.5,1,1,0.5,1,1,0.5,1,1,0.5,1,1,1,0.5,0.5,1]
relative_absolute_error
0.8155525164202606
relative_absolute_error
0.8175275475502795
relative_absolute_error
0.8192936618046842
relative_absolute_error
0.8178229330962331
relative_absolute_error
0.8145170785389735
relative_absolute_error
0.8167485868525516
relative_absolute_error
0.8094240293321289
relative_absolute_error
0.8123855106656529
relative_absolute_error
0.8147446163280341
relative_absolute_error
0.8146998180695693
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
0.08410808221625694
root_mean_squared_error
0.08423648621635244
root_mean_squared_error
0.08445920088287599
root_mean_squared_error
0.08432472037522798
root_mean_squared_error
0.08411779108048323
root_mean_squared_error
0.08427022246424609
root_mean_squared_error
0.08348869473301969
root_mean_squared_error
0.08369392335410324
root_mean_squared_error
0.08394477082324484
root_mean_squared_error
0.08395833994524295
root_relative_squared_error
0.8453180319626903
root_relative_squared_error
0.8466085407199553
root_relative_squared_error
0.8488469073386454
root_relative_squared_error
0.8474953273826304
root_relative_squared_error
0.8454156097195965
root_relative_squared_error
0.8469476027687363
root_relative_squared_error
0.8390929535331735
root_relative_squared_error
0.841155578782798
root_relative_squared_error
0.8436766907062919
root_relative_squared_error
0.8438130655135716
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
2700.495576999998
usercpu_time_millis
2621.850932000001
usercpu_time_millis
2622.5539509999862
usercpu_time_millis
2624.7383570000125
usercpu_time_millis
2621.874686999973
usercpu_time_millis
2623.5693880000217
usercpu_time_millis
2620.5766069999754
usercpu_time_millis
2637.9556589999993
usercpu_time_millis
2631.238042000007
usercpu_time_millis
2633.0860260000295
usercpu_time_millis_testing
47.65055400000051
usercpu_time_millis_testing
38.46930099999213
usercpu_time_millis_testing
36.60387599998671
usercpu_time_millis_testing
36.87511300000779
usercpu_time_millis_testing
36.70908199998735
usercpu_time_millis_testing
36.77923600000099
usercpu_time_millis_testing
36.56375099998854
usercpu_time_millis_testing
36.88664500000982
usercpu_time_millis_testing
37.22963399999912
usercpu_time_millis_testing
36.7707070000165
usercpu_time_millis_training
2652.8450229999976
usercpu_time_millis_training
2583.381631000009
usercpu_time_millis_training
2585.9500749999997
usercpu_time_millis_training
2587.8632440000047
usercpu_time_millis_training
2585.165604999986
usercpu_time_millis_training
2586.7901520000205
usercpu_time_millis_training
2584.0128559999866
usercpu_time_millis_training
2601.0690139999897
usercpu_time_millis_training
2594.008408000008
usercpu_time_millis_training
2596.315319000013