5976882
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)
4011615
bootstrap
false
6902
class_weight
null
6902
criterion
"entropy"
6902
max_depth
null
6902
max_features
0.44223410820422193
6902
max_leaf_nodes
null
6902
min_impurity_split
1e-07
6902
min_samples_leaf
12
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
24486
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
"median"
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
12877111
description
https://api.openml.org/data/download/12877111/description.xml
-1
12877112
predictions
https://api.openml.org/data/download/12877112/predictions.arff
area_under_roc_curve
0.9932496843434341 [0.980193,0.999487,0.999961,1,0.999053,0.991714,0.999448,0.998382,0.996252,0.999724,0.997356,0.999448,0.997711,0.983507,0.999092,0.997711,0.999961,0.981771,0.98548,0.970644,0.99925,0.999605,0.992622,1,0.996686,0.96441,0.983349,0.994476,0.996686,0.999645,0.999763,1,0.994003,0.986545,0.99491,0.998461,0.985835,0.988439,0.998816,0.999842,0.993687,0.998224,0.999842,0.997988,0.998422,0.998895,0.998698,0.99562,0.990688,0.994515,0.991635,0.992069,0.996173,0.978259,0.992306,0.972735,1,0.99929,0.994713,0.980627,1,0.997869,0.993095,0.997199,0.997751,0.993568,0.975418,1,0.978378,0.985717,0.989978,0.997988,0.990846,0.998619,0.968119,0.996173,0.99925,0.978101,0.999448,0.999448,0.992266,0.994949,0.991951,0.994042,0.996962,0.98986,0.999921,0.992266,0.996804,1,0.999803,0.999487,0.99633,0.98694,0.998067,0.998619,0.996054,0.993134,0.959951,0.995975]
average_cost
0
f_measure
0.7080567986716444 [0.538462,0.888889,1,0.941176,0.933333,0.580645,0.857143,0.810811,0.709677,0.967742,0.62069,0.848485,0.717949,0.5,0.941176,0.8,0.8,0.48,0.555556,0.181818,0.810811,0.933333,0.709677,1,0.731707,0.2,0.363636,0.756757,0.848485,0.864865,0.848485,0.969697,0.848485,0.551724,0.769231,0.7,0.529412,0.512821,0.909091,0.888889,0.666667,0.8,0.882353,0.727273,0.764706,0.83871,0.83871,0.774194,0.758621,0.774194,0.625,0.666667,0.742857,0.384615,0.645161,0.181818,1,0.909091,0.571429,0.538462,0.914286,0.717949,0.689655,0.8,0.769231,0.666667,0.222222,0.864865,0.454545,0.416667,0.6,0.769231,0.5,0.888889,0.48,0.866667,0.842105,0.3,0.909091,0.967742,0.571429,0.666667,0.75,0.666667,0.823529,0.875,0.969697,0.529412,0.666667,1,0.820513,0.780488,0.714286,0.3,0.709677,0.705882,0.787879,0.516129,0.111111,0.689655]
kappa
0.7241161616161617
kb_relative_information_score
1088.3407666027224
mean_absolute_error
0.014389284038757964
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
0.725481690392735 [0.7,0.8,1,0.888889,1,0.6,0.789474,0.714286,0.733333,1,0.692308,0.823529,0.608696,0.75,0.888889,0.857143,0.666667,0.666667,0.5,0.333333,0.714286,1,0.733333,1,0.6,0.5,0.352941,0.666667,0.823529,0.761905,0.823529,0.941176,0.823529,0.615385,0.652174,0.583333,0.5,0.434783,0.882353,0.8,0.6,0.736842,0.833333,0.705882,0.722222,0.866667,0.866667,0.8,0.846154,0.8,0.625,0.714286,0.684211,0.5,0.666667,0.333333,1,0.882353,0.526316,0.7,0.842105,0.608696,0.769231,0.736842,0.652174,0.6,0.272727,0.761905,0.833333,0.625,0.642857,0.652174,0.416667,0.8,0.666667,0.928571,0.727273,0.75,0.882353,1,0.666667,0.818182,0.75,0.714286,0.777778,0.875,0.941176,0.5,0.818182,1,0.695652,0.64,0.833333,0.75,0.733333,0.666667,0.764706,0.533333,0.5,0.769231]
predictive_accuracy
0.726875
prior_entropy
6.6438561897747395
recall
0.726875 [0.4375,1,1,1,0.875,0.5625,0.9375,0.9375,0.6875,0.9375,0.5625,0.875,0.875,0.375,1,0.75,1,0.375,0.625,0.125,0.9375,0.875,0.6875,1,0.9375,0.125,0.375,0.875,0.875,1,0.875,1,0.875,0.5,0.9375,0.875,0.5625,0.625,0.9375,1,0.75,0.875,0.9375,0.75,0.8125,0.8125,0.8125,0.75,0.6875,0.75,0.625,0.625,0.8125,0.3125,0.625,0.125,1,0.9375,0.625,0.4375,1,0.875,0.625,0.875,0.9375,0.75,0.1875,1,0.3125,0.3125,0.5625,0.9375,0.625,1,0.375,0.8125,1,0.1875,0.9375,0.9375,0.5,0.5625,0.75,0.625,0.875,0.875,1,0.5625,0.5625,1,1,1,0.625,0.1875,0.6875,0.75,0.8125,0.5,0.0625,0.625]
relative_absolute_error
0.7267315171089866
root_mean_prior_squared_error
0.09949874371066209
root_mean_squared_error
0.07744304211967383
root_relative_squared_error
0.7783318585898406
total_cost
0
area_under_roc_curve
0.9920525336358571 [1,1,1,1,0.996835,1,1,1,0.996835,1,0.996835,0.996835,1,0.962025,1,1,1,0.96519,0.96519,0.974843,1,1,1,1,1,0.987342,0.993671,1,0.993671,1,0.996835,1,0.996835,0.990506,1,0.993711,1,0.993711,1,1,1,1,1,1,1,1,1,1,1,0.968354,0.946203,1,0.987421,0.990506,1,1,1,1,0.993711,0.987342,1,1,1,1,1,1,0.993671,1,1,0.968553,0.984177,1,0.987342,1,1,1,1,0.977848,1,1,1,1,1,1,0.996835,0.939873,1,0.996835,0.990506,1,1,1,1,0.981013,1,1,1,0.993671,0.835443,1]
area_under_roc_curve
0.9938383190032638 [0.987421,1,1,1,1,1,0.996835,1,1,1,0.996835,1,0.990506,0.962025,1,1,1,0.977848,0.993671,0.993711,1,1,1,1,1,0.952532,0.987342,0.971519,1,1,1,1,1,0.996835,0.996835,0.993711,0.949686,1,0.993711,1,1,1,1,1,1,1,1,1,0.993671,1,1,0.96519,1,1,0.993711,0.949686,1,1,1,0.943038,1,1,1,0.993671,1,1,0.996835,1,0.937107,1,0.996835,1,0.993671,1,1,1,1,0.971519,1,0.996835,0.993671,0.993671,0.974843,0.993711,1,1,1,0.993671,0.996835,1,1,1,1,0.987342,0.996835,1,1,0.987342,1,1]
area_under_roc_curve
0.9932424767136375 [0.996835,1,1,1,0.996835,0.984177,1,1,0.984177,1,1,1,1,0.996835,0.996835,1,1,0.990506,0.993711,0.93038,1,1,0.955696,1,0.974843,0.971519,1,1,0.996835,1,1,1,1,0.971519,0.993711,1,0.993711,0.943396,1,1,1,1,1,1,0.996835,1,0.996835,1,0.962025,1,0.996835,1,1,0.990506,1,1,1,1,0.987421,0.958861,1,0.993711,0.993671,1,1,0.981013,0.987342,1,0.981132,0.977848,0.996835,0.996835,0.993711,0.996835,1,1,1,0.977848,1,1,1,0.996835,1,0.996835,1,1,1,0.996835,0.996835,1,1,1,0.993711,0.984177,1,1,0.993671,0.996835,0.981132,1]
area_under_roc_curve
0.9927685395271076 [0.996835,0.996835,1,1,0.996835,0.990506,1,1,0.993671,1,0.996835,1,1,1,1,1,1,0.984177,0.91195,0.990506,1,1,1,1,0.993711,0.962025,0.955696,1,1,1,1,1,1,0.990506,1,0.987421,1,1,1,1,1,1,1,1,1,1,1,1,0.996835,1,0.993671,1,0.993711,0.936709,1,0.990506,1,1,1,0.990506,1,1,0.993671,1,0.993671,0.993671,0.955696,1,1,0.955696,0.990506,0.993671,0.981132,1,1,0.977848,1,0.962025,1,1,0.981132,0.984177,1,0.987342,1,1,1,1,1,1,1,1,0.968553,1,1,0.993711,0.993671,0.996835,1,0.974684]
area_under_roc_curve
0.9909546413502108 [0.984177,1,1,1,1,0.996835,1,1,1,1,0.996835,0.996835,1,0.930818,1,1,1,1,1,0.990506,0.993671,1,1,1,0.996835,0.962025,0.984177,1,1,1,1,1,0.996835,0.974684,1,1,0.987342,0.990506,1,1,1,1,1,1,1,1,1,1,1,0.996835,1,0.981132,0.996835,0.981132,0.955696,0.949367,1,0.990506,0.993671,0.974843,1,1,1,1,0.996835,1,0.874214,1,0.924051,0.993671,1,1,0.993711,1,0.860759,1,0.996835,0.968354,1,1,1,1,0.996835,0.993671,0.987421,1,1,1,1,1,1,0.996835,1,0.987421,0.990506,1,0.996835,1,0.955975,0.993671]
area_under_roc_curve
0.9913432449645729 [0.901899,1,1,1,1,0.984177,1,1,1,0.996835,0.996835,1,1,1,1,0.996835,1,0.996835,1,0.933544,1,1,0.984177,1,0.993671,0.990506,0.977848,0.993711,1,1,1,1,0.952532,0.993671,0.949686,1,0.958861,0.984177,1,1,1,0.984177,1,1,1,1,1,0.996835,0.987342,0.977848,1,1,1,1,0.990506,0.96519,1,1,0.996835,1,1,0.993671,0.987421,1,1,1,0.981132,1,0.990506,1,0.977848,0.990506,1,1,0.952532,1,1,0.984177,1,1,1,0.984177,1,0.993671,1,1,1,0.981132,0.987342,1,1,1,0.993711,1,1,1,1,0.974843,0.981132,0.990506]
area_under_roc_curve
0.9945545736804391 [1,1,1,1,1,1,1,1,0.993711,1,1,1,0.987342,0.987421,1,0.990506,1,0.987421,0.996835,0.96519,0.993671,1,1,1,0.993671,0.861635,0.987421,0.981013,1,1,1,1,1,0.974843,1,1,0.990506,1,1,1,0.993671,1,1,1,1,0.993671,0.993671,0.987342,1,1,1,1,1,1,0.996835,0.996835,1,1,0.993671,0.993711,1,1,1,0.977848,1,0.993711,0.968553,1,0.996835,0.990506,0.993711,1,0.996835,1,0.996835,1,1,0.981132,1,1,0.990506,1,0.990506,1,1,1,1,0.968553,1,1,1,1,0.987342,0.974843,1,1,1,0.993711,0.952532,1]
area_under_roc_curve
0.9946685176339466 [1,1,1,1,1,0.993671,1,1,1,1,0.993711,1,1,1,1,0.996835,1,0.981132,0.990506,0.987342,1,1,1,1,1,0.974843,0.974843,0.993671,1,0.996835,1,1,1,1,1,1,0.981013,0.996835,1,1,1,1,1,0.996835,1,1,1,1,1,1,0.993711,1,0.987342,1,1,0.936709,1,1,0.990506,1,1,0.993671,0.993711,1,1,0.962264,0.962264,1,0.987342,0.987342,1,1,1,1,0.987342,1,1,0.974843,1,1,0.984177,1,0.96519,0.996835,0.990506,0.981013,1,0.993711,1,1,1,1,1,0.974843,1,1,0.987342,1,0.974684,1]
area_under_roc_curve
0.9959330964891331 [0.962264,1,1,1,1,1,1,1,0.993671,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.993711,1,0.996835,1,1,1,1,0.993711,1,1,0.993671,0.987342,1,1,0.955975,1,1,0.990506,1,0.993671,1,1,0.993711,1,1,0.993671,1,0.933544,1,0.955975,1,1,0.996835,1,1,1,1,1,1,1,0.996835,1,0.990506,0.981132,1,0.993711,0.974684,1,0.993671,0.987342,1,1,1,0.996835,0.996835,1,1,1,1,1,1,0.987342,1,1,1,1,1,0.981013,0.987421,0.996835,0.993711,0.996835,0.990506,1]
area_under_roc_curve
0.99660805270281 [0.974843,1,1,1,1,1,1,0.987421,0.996835,1,1,1,0.996835,0.990506,1,1,1,0.987421,0.993671,0.993711,1,1,1,1,1,0.949686,1,1,0.993671,1,1,1,1,0.974843,0.996835,0.996835,0.987342,1,0.996835,1,0.993711,1,1,0.996835,1,1,1,0.996835,1,1,1,0.993671,1,0.984177,1,0.987421,1,1,0.993671,1,1,1,0.974684,1,0.987421,1,1,1,1,0.993711,0.981132,1,0.987342,1,0.993671,0.996835,1,1,0.981132,1,1,0.981132,1,0.974843,1,1,0.996835,0.990506,1,1,1,1,1,1,1,1,1,1,1,1]
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
0.7157632939876041
kappa
0.7726285872182529
kappa
0.6652983896431954
kappa
0.7094469227428842
kappa
0.7283424149095791
kappa
0.6841689696012634
kappa
0.7409367348550667
kappa
0.7346076379289918
kappa
0.7409571947559628
kappa
0.7472753119570368
kb_relative_information_score
108.34812718764775
kb_relative_information_score
108.79071115079627
kb_relative_information_score
107.44472673011552
kb_relative_information_score
108.25050730103841
kb_relative_information_score
108.01654180798438
kb_relative_information_score
107.28218863690584
kb_relative_information_score
110.13165127144181
kb_relative_information_score
109.51476565456876
kb_relative_information_score
110.49725220061683
kb_relative_information_score
110.06429466160695
mean_absolute_error
0.014370277102367846
mean_absolute_error
0.014395545740441199
mean_absolute_error
0.014525834595083633
mean_absolute_error
0.014499193409784209
mean_absolute_error
0.01432813962878996
mean_absolute_error
0.014507123328128568
mean_absolute_error
0.014249760113871215
mean_absolute_error
0.014279658553473486
mean_absolute_error
0.014317729475725974
mean_absolute_error
0.014419578439913459
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
0.71875
predictive_accuracy
0.775
predictive_accuracy
0.66875
predictive_accuracy
0.7125
predictive_accuracy
0.73125
predictive_accuracy
0.6875
predictive_accuracy
0.74375
predictive_accuracy
0.7375
predictive_accuracy
0.74375
predictive_accuracy
0.75
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
0.71875 [1,1,1,1,0.5,1,1,1,1,1,0.5,1,1,0,1,1,1,0,0.5,0,1,0,1,1,1,0,0,1,0.5,1,1,1,0.5,0,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,0.5,0.5,0.5,1,0,1,0,1,1,1,1,1,1,0.5,1,1,1,0.5,1,0,0,0.5,1,0.5,1,1,1,1,0.5,1,1,0,1,1,1,0.5,0.5,1,0.5,0,1,1,1,1,0.5,1,0,1,0.5,0,1]
recall
0.775 [0,1,1,1,1,1,0.5,1,0.5,1,0.5,1,1,0.5,1,1,1,0,0.5,1,1,1,1,1,1,0.5,0.5,0.5,1,1,1,1,1,0.5,1,1,0,1,1,1,1,1,1,1,0.5,1,1,1,0.5,1,1,0.5,1,1,1,0,1,1,1,0.5,1,1,1,1,1,1,0,1,0,0,1,1,0.5,1,1,1,1,0.5,1,0.5,0.5,0.5,0,1,1,1,1,1,1,1,1,1,0.5,0,0.5,1,1,0,0,1]
recall
0.66875 [0.5,1,1,1,0.5,0,1,1,0,1,0.5,1,1,0.5,1,0.5,1,0.5,0,0,1,0,0.5,1,0,0,0.5,1,1,1,1,1,1,0.5,1,1,1,0,1,1,0,1,1,1,0.5,1,0.5,1,0.5,0.5,1,1,1,0.5,1,0,1,1,1,0,1,1,0.5,1,1,0.5,0.5,1,0,0,0.5,1,0,1,0,1,1,0,0.5,1,1,0.5,1,0.5,1,1,1,0.5,1,1,1,1,1,0,1,1,0.5,0.5,0,0.5]
recall
0.7125 [0.5,1,1,1,1,0,1,1,0.5,1,0,0.5,1,0.5,1,1,1,0.5,0,0,1,1,0.5,1,1,0,0.5,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0,1,1,0,1,0.5,1,1,1,0.5,1,1,1,1,0.5,1,0,1,0,0.5,0,0.5,0,1,1,0.5,1,0,1,1,0,0.5,1,0.5,1,1,1,1,1,1,1,1,0,0,1,0,1,1,0,0]
recall
0.73125 [0.5,1,1,1,1,0.5,1,1,1,1,1,0.5,1,0,1,0.5,1,1,0,0,0.5,1,1,1,1,0,0.5,1,1,1,1,1,1,0.5,1,1,1,0.5,1,1,1,1,1,1,1,1,1,0.5,0.5,0.5,0,0,0,0,0,0,1,0.5,1,0,1,1,1,1,1,0,0,1,0.5,0.5,1,1,1,1,0,1,1,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,0,0.5,1,1,1,0,0.5]
recall
0.6875 [0,1,1,1,1,0.5,1,1,1,0.5,0,1,1,1,1,1,1,0.5,1,0,1,1,0.5,1,1,0.5,0.5,1,1,1,0,1,0.5,1,0,0.5,0.5,0.5,1,1,1,0.5,1,1,1,1,1,0,0.5,0.5,1,0,1,1,0.5,0,1,1,0,1,1,0.5,0,1,1,1,0,1,0.5,0.5,0.5,1,1,1,0,1,1,0,1,1,1,0,1,0.5,1,1,1,0,0,1,1,1,0,1,0.5,1,1,0,0,0.5]
recall
0.74375 [0.5,1,1,1,1,1,1,1,1,1,1,1,0.5,0,1,0.5,1,0,1,0.5,1,1,0.5,1,1,0,0,0.5,1,1,0.5,1,1,0,1,1,0.5,1,1,1,0.5,0.5,1,1,1,0.5,0.5,0.5,1,1,0,1,1,0,0.5,0.5,1,1,0,0,1,1,1,0.5,1,1,0,1,0.5,0,1,1,1,1,1,1,1,0,1,1,0.5,1,0.5,1,1,1,1,0,0,1,1,1,0.5,0,1,0.5,1,0,0,1]
recall
0.7375 [1,1,1,1,1,0.5,1,1,1,1,1,1,1,0,1,0.5,1,0,1,0,1,1,0.5,1,1,0,0,1,0,1,1,1,1,1,1,1,0.5,0.5,1,1,1,1,1,0,1,1,1,1,1,1,0,0.5,0.5,1,1,0,1,1,0.5,1,1,0.5,1,1,1,0,0,1,0,1,0,1,1,1,0,1,1,0,1,1,0,0,0,1,0.5,0.5,1,0,1,1,1,1,1,0,0,1,0.5,1,0,1]
recall
0.74375 [0,1,1,1,1,1,1,1,0.5,1,1,1,1,0.5,1,1,1,1,1,0,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,0,1,1,0,1,1,0.5,0.5,0.5,1,1,0,1,1,0.5,1,0,0.5,0,1,1,0.5,0,1,1,0.5,0.5,1,1,0,1,0.5,0,1,1,0.5,1,0.5,0.5,1,1,1,1,0.5,1,1,1,1,1,1,0.5,0,1,1,1,0,0,0,1,0,0.5,0.5,1]
recall
0.75 [0,1,1,1,1,1,1,0,1,1,1,1,0.5,0.5,1,1,1,0,0.5,0,1,1,1,1,1,0,1,1,1,1,1,1,1,0,1,1,0,1,0.5,1,1,1,0.5,0.5,1,0.5,1,1,1,1,1,1,1,0,0.5,0,1,1,1,0.5,1,1,0,1,1,1,0.5,1,0.5,0,0,1,0.5,1,0,0.5,1,0,1,1,1,0,1,0,1,1,1,0.5,0,1,1,1,1,0.5,1,1,1,0.5,0,0]
relative_absolute_error
0.7257715708266577
relative_absolute_error
0.7270477646687462
relative_absolute_error
0.7336280098527075
relative_absolute_error
0.7322824954436455
relative_absolute_error
0.7236434155954514
relative_absolute_error
0.7326829963701285
relative_absolute_error
0.7196848542359188
relative_absolute_error
0.7211948764380537
relative_absolute_error
0.7231176502891894
relative_absolute_error
0.7282615373693653
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
0.07729352033222983
root_mean_squared_error
0.07732122369475425
root_mean_squared_error
0.07822259156091682
root_mean_squared_error
0.07777413753232472
root_mean_squared_error
0.0773762581693923
root_mean_squared_error
0.07827390561503945
root_mean_squared_error
0.07688645719312465
root_mean_squared_error
0.07698220905326247
root_mean_squared_error
0.07675426399297611
root_mean_squared_error
0.07753001373034353
root_relative_squared_error
0.7768291080839771
root_relative_squared_error
0.7771075373534458
root_relative_squared_error
0.7861666252629748
root_relative_squared_error
0.7816594926915709
root_relative_squared_error
0.7776606546349875
root_relative_squared_error
0.7866823509114498
root_relative_squared_error
0.7727379696039889
root_relative_squared_error
0.773700312007188
root_relative_squared_error
0.7714093779532947
root_relative_squared_error
0.7792059561656113
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
5605.972623000071
usercpu_time_millis
5542.473944000221
usercpu_time_millis
5598.849026999915
usercpu_time_millis
5682.362812000065
usercpu_time_millis
5703.29671200011
usercpu_time_millis
5700.167487000272
usercpu_time_millis
5713.273281999818
usercpu_time_millis
5722.658256000159
usercpu_time_millis
5731.617814000174
usercpu_time_millis
5749.752551000256
usercpu_time_millis_testing
41.25723900006051
usercpu_time_millis_testing
39.68293700017966
usercpu_time_millis_testing
40.984627999932854
usercpu_time_millis_testing
41.015745000095194
usercpu_time_millis_testing
40.75161600007959
usercpu_time_millis_testing
40.92011100010495
usercpu_time_millis_testing
41.080556999986584
usercpu_time_millis_testing
41.05417000005218
usercpu_time_millis_testing
45.30403800004024
usercpu_time_millis_testing
40.987166000149955
usercpu_time_millis_training
5564.71538400001
usercpu_time_millis_training
5502.791007000042
usercpu_time_millis_training
5557.864398999982
usercpu_time_millis_training
5641.34706699997
usercpu_time_millis_training
5662.545096000031
usercpu_time_millis_training
5659.247376000167
usercpu_time_millis_training
5672.192724999832
usercpu_time_millis_training
5681.604086000107
usercpu_time_millis_training
5686.313776000134
usercpu_time_millis_training
5708.765385000106