6027930
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)
4062615
bootstrap
false
6902
class_weight
null
6902
criterion
"gini"
6902
max_depth
null
6902
max_features
0.3189538637161444
6902
max_leaf_nodes
null
6902
min_impurity_split
1e-07
6902
min_samples_leaf
16
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
1899
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
true
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
12978959
description
https://api.openml.org/data/download/12978959/description.xml
-1
12978960
predictions
https://api.openml.org/data/download/12978960/predictions.arff
area_under_roc_curve
0.9930535827020204 [0.98256,0.998619,0.999329,1,0.999645,0.993292,0.998382,0.99712,0.995896,0.999645,0.995857,0.998816,0.99925,0.987334,0.998974,0.997159,0.999882,0.98331,0.985519,0.974669,0.999171,0.999803,0.995147,1,0.997909,0.963344,0.978575,0.997317,0.987808,0.999763,0.99854,0.999171,0.994555,0.98836,0.998895,0.995147,0.987571,0.982442,0.996133,0.999171,0.999566,0.998895,0.998816,0.99779,0.996488,0.999684,0.996804,0.993687,0.993924,0.995818,0.996133,0.990096,0.995423,0.97964,0.99491,0.981652,0.999724,0.998698,0.987492,0.975655,0.999921,0.998343,0.991004,0.995028,0.996015,0.994555,0.976523,0.998619,0.968947,0.987019,0.990688,0.997475,0.988439,0.998974,0.97313,0.990688,0.999053,0.981929,0.998974,0.996567,0.988439,0.994792,0.998185,0.995344,0.9942,0.993411,1,0.989978,0.996804,0.999684,0.999724,0.998185,0.996686,0.986466,0.99637,0.996291,0.9942,0.990372,0.962831,0.996528]
average_cost
0
f_measure
0.6579344169175053 [0.333333,0.769231,0.941176,0.969697,0.864865,0.692308,0.787879,0.774194,0.742857,0.914286,0.736842,0.8,0.697674,0.521739,0.914286,0.758621,0.8,0.516129,0.444444,0.071429,0.833333,0.866667,0.64,0.969697,0.722222,0.210526,0.16,0.758621,0.777778,0.875,0.875,0.83871,0.823529,0.457143,0.833333,0.585366,0.5,0.45,0.785714,0.8,0.810811,0.903226,0.717949,0.685714,0.642857,0.823529,0.736842,0.666667,0.6875,0.666667,0.8125,0.5625,0.777778,0.4,0.625,0.333333,0.914286,0.727273,0,0.56,0.914286,0.744186,0.466667,0.736842,0.634146,0.666667,0.275862,0.551724,0.2,0.434783,0.3,0.764706,0.457143,0.967742,0.5,0.285714,0.810811,0.666667,0.842105,0.769231,0.347826,0.594595,0.8125,0.590909,0.666667,0.785714,0.914286,0.615385,0.666667,0.857143,0.761905,0.769231,0.785714,0.3,0.875,0.733333,0.62069,0.380952,0.210526,0.647059]
kappa
0.6786616161616161
kb_relative_information_score
1052.9906710856694
mean_absolute_error
0.014940893494486773
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
0.6869474573700581 [0.5,0.652174,0.888889,0.941176,0.761905,0.9,0.764706,0.8,0.684211,0.842105,0.636364,0.736842,0.555556,0.857143,0.842105,0.846154,0.666667,0.533333,0.545455,0.083333,0.75,0.928571,0.888889,0.941176,0.65,0.666667,0.222222,0.846154,0.7,0.875,0.875,0.866667,0.777778,0.421053,0.75,0.48,0.45,0.375,0.916667,0.736842,0.714286,0.933333,0.608696,0.631579,0.75,0.777778,0.636364,0.647059,0.6875,0.6,0.8125,0.5625,0.7,0.555556,0.625,0.5,0.842105,0.705882,0,0.777778,0.842105,0.592593,0.5,0.636364,0.52,0.538462,0.307692,0.615385,0.5,0.714286,0.75,0.722222,0.421053,1,0.75,0.6,0.714286,1,0.727273,1,0.571429,0.52381,0.8125,0.464286,0.647059,0.916667,0.842105,0.521739,0.565217,0.789474,0.615385,0.652174,0.916667,0.75,0.875,0.785714,0.692308,0.8,0.666667,0.611111]
predictive_accuracy
0.681875
prior_entropy
6.6438561897747395
recall
0.681875 [0.25,0.9375,1,1,1,0.5625,0.8125,0.75,0.8125,1,0.875,0.875,0.9375,0.375,1,0.6875,1,0.5,0.375,0.0625,0.9375,0.8125,0.5,1,0.8125,0.125,0.125,0.6875,0.875,0.875,0.875,0.8125,0.875,0.5,0.9375,0.75,0.5625,0.5625,0.6875,0.875,0.9375,0.875,0.875,0.75,0.5625,0.875,0.875,0.6875,0.6875,0.75,0.8125,0.5625,0.875,0.3125,0.625,0.25,1,0.75,0,0.4375,1,1,0.4375,0.875,0.8125,0.875,0.25,0.5,0.125,0.3125,0.1875,0.8125,0.5,0.9375,0.375,0.1875,0.9375,0.5,1,0.625,0.25,0.6875,0.8125,0.8125,0.6875,0.6875,1,0.75,0.8125,0.9375,1,0.9375,0.6875,0.1875,0.875,0.6875,0.5625,0.25,0.125,0.6875]
relative_absolute_error
0.7545905805296336
root_mean_prior_squared_error
0.09949874371066209
root_mean_squared_error
0.08004915586301634
root_relative_squared_error
0.8045242872191001
total_cost
0
area_under_roc_curve
0.992051787278083 [0.993711,0.996835,1,1,1,1,1,1,0.993671,0.993711,0.987342,0.996835,0.996835,0.981013,1,1,1,0.977848,0.962025,0.993711,1,1,0.993711,1,0.993711,0.990506,0.949367,1,0.977848,1,0.987342,1,0.987342,0.984177,1,0.987421,1,1,1,1,1,1,1,0.996835,1,1,1,1,1,0.968354,0.993671,1,0.987421,0.993671,1,1,1,1,0.987421,0.993671,1,1,1,0.990506,1,1,0.987342,1,1,1,0.974684,1,0.974684,1,1,0.996835,1,0.977848,1,1,0.987342,1,1,1,0.981013,0.987342,1,1,0.993671,1,1,1,1,0.993671,1,0.987342,1,0.993671,0.857595,1]
area_under_roc_curve
0.9927717737441286 [0.962264,1,1,1,1,0.993711,1,1,1,1,1,0.993671,1,0.968354,1,1,1,0.974684,0.993671,0.987421,1,1,0.993711,1,1,0.949367,0.987342,0.996835,1,1,1,1,1,0.996835,0.996835,0.987421,0.981132,1,0.993711,1,1,1,1,1,1,1,1,1,0.993671,1,1,0.968354,1,1,0.993711,0.968553,1,1,1,0.898734,1,0.987421,0.996835,0.990506,1,0.996835,1,1,0.899371,1,0.993671,1,0.996835,1,1,0.996835,1,0.952532,1,0.987342,0.984177,1,0.987421,0.993711,0.996835,1,1,1,1,1,0.996835,1,1,0.990506,1,1,1,0.971519,0.987342,1]
area_under_roc_curve
0.9937574635777405 [0.996835,1,1,1,0.996835,0.993671,1,1,0.990506,1,1,1,1,0.993671,1,1,1,0.987342,0.987421,0.920886,0.993711,0.993711,0.993671,1,0.993711,0.993671,1,1,1,1,1,1,0.996835,0.974684,1,1,0.993711,0.949686,1,1,0.996835,1,1,1,0.996835,1,0.993671,1,0.977848,1,0.996835,1,1,0.996835,1,1,1,1,0.962264,0.952532,1,0.987421,0.996835,1,0.993671,0.987342,0.993671,1,0.987421,0.974684,0.993671,1,0.993711,1,1,1,1,0.984177,0.993671,1,1,1,1,1,1,1,1,0.996835,0.993671,1,1,1,1,0.971519,1,1,0.996835,0.981013,0.968553,0.987342]
area_under_roc_curve
0.9944284392166225 [0.971519,1,1,1,1,0.993671,1,1,0.996835,1,0.993671,1,1,0.993671,1,1,1,1,0.930818,0.987342,1,1,1,1,0.993711,0.990506,0.971519,1,0.996835,1,1,1,1,0.987342,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.993671,1,1,0.917722,1,0.990506,1,0.996835,1,0.996835,1,1,0.993671,1,0.996835,1,0.946203,0.993671,1,0.996835,0.993671,1,0.993711,1,0.987421,0.990506,1,0.981013,1,1,0.981132,1,1,0.993671,1,0.987421,1,1,1,1,1,1,0.987421,0.996835,1,1,0.987342,0.996835,0.987421,0.984177]
area_under_roc_curve
0.9922948511265023 [0.990506,1,1,1,1,0.993671,1,0.996835,1,1,0.993671,0.990506,1,0.962264,1,0.996835,1,0.996835,0.993711,0.987342,1,1,1,1,0.996835,0.984177,0.990506,1,1,1,1,1,1,0.977848,1,1,1,0.93038,0.996835,1,1,1,1,1,1,1,1,1,1,1,1,0.962264,0.996835,0.993711,0.981013,0.987342,1,0.990506,0.993671,0.981132,1,1,1,1,0.993671,1,0.955975,0.996835,0.962025,0.958861,0.996835,1,1,1,0.889241,1,1,0.981013,1,1,1,1,0.990506,0.993671,0.981132,0.981132,1,1,1,1,1,0.990506,1,0.987421,0.974684,1,0.996835,1,0.987421,0.993671]
area_under_roc_curve
0.9934785745561658 [0.955696,1,1,1,1,0.990506,1,0.993671,1,1,0.996835,1,1,0.993711,1,1,1,0.996835,1,0.946203,1,1,1,1,0.996835,0.984177,0.96519,1,1,1,1,1,0.981013,0.996835,0.987421,0.993671,0.974684,0.993671,1,1,1,0.996835,1,1,0.993711,1,1,0.974684,1,0.996835,1,1,0.996835,1,0.993671,0.987342,1,1,0.984177,1,1,1,0.987421,1,1,1,0.987421,1,0.968354,1,0.984177,0.990506,1,1,0.968354,0.981132,1,0.981013,1,1,0.993711,0.993671,1,0.996835,1,1,1,0.993711,0.977848,1,1,0.993671,0.981132,1,1,1,1,0.987421,0.974843,0.996835]
area_under_roc_curve
0.9955840498367963 [1,1,1,1,1,1,1,1,0.993711,1,1,1,1,1,1,0.993671,1,0.993711,0.993671,0.974684,0.993671,1,0.993671,1,0.993671,0.91195,0.981132,0.993671,1,1,1,1,1,0.955975,1,1,1,1,1,1,1,1,1,1,0.981132,0.996835,0.993671,0.990506,1,1,0.993711,1,1,1,0.990506,1,1,1,0.993671,0.993711,1,1,1,0.996835,0.996835,1,0.962264,0.996835,0.993671,1,0.993711,1,1,1,1,0.987421,1,1,1,1,0.974684,1,1,1,1,0.996835,1,0.90566,1,1,1,1,0.984177,0.987421,1,1,1,0.993711,0.987342,1]
area_under_roc_curve
0.9929367188121961 [1,1,1,1,1,0.996835,1,1,0.993711,1,0.987421,1,1,1,0.987421,0.993671,1,0.987421,0.974684,0.993671,1,1,1,1,1,0.974843,0.987421,1,0.861635,1,1,1,1,1,1,1,1,0.981013,1,1,1,1,1,0.996835,1,0.996835,1,1,0.993711,1,0.981132,0.993671,0.981013,1,0.996835,0.958861,1,1,0.974684,0.974843,1,0.996835,1,1,1,0.955975,0.981132,1,0.96519,0.981013,1,1,1,1,0.984177,1,1,1,1,1,0.977848,0.993711,1,0.996835,1,0.968354,1,0.987421,1,1,1,1,1,0.924528,1,0.990506,0.987342,0.987421,0.968354,1]
area_under_roc_curve
0.9937238774779079 [0.993711,1,1,1,1,0.993711,0.990506,0.981132,1,1,0.993711,1,1,1,0.996835,1,1,1,1,1,1,1,0.955975,1,1,0.899371,0.981132,1,1,1,1,1,1,1,1,1,0.996835,0.981013,0.996835,0.987421,1,0.993671,0.996835,1,1,1,1,0.993671,0.987421,1,1,0.987342,1,0.96519,0.996835,0.962264,1,1,0.993671,0.984177,1,1,1,0.993671,1,1,0.974684,1,0.955696,0.987421,1,0.981132,0.968354,0.996835,0.990506,0.971519,1,1,1,0.996835,0.990506,0.974843,1,0.993711,1,1,1,0.993671,0.993711,1,1,0.996835,1,1,1,0.993671,0.993711,1,0.971519,1]
area_under_roc_curve
0.9941622382772071 [0.943396,1,0.974843,1,1,0.993711,1,0.968553,0.996835,1,1,1,1,0.993671,1,1,1,0.974843,0.990506,1,1,1,1,1,1,0.880503,0.993711,0.996835,0.996835,1,1,1,1,1,0.996835,0.993671,0.971519,0.987342,0.993671,1,1,1,1,1,0.996835,1,1,0.990506,0.993711,1,1,1,1,0.981013,1,0.974843,1,0.993711,0.993671,0.996835,1,1,0.971519,0.984177,1,1,0.993671,1,0.987342,0.981132,0.981132,1,0.977848,1,0.996835,0.990506,1,0.993711,1,0.990506,1,0.981132,1,0.968553,0.996835,1,1,0.987342,1,0.996835,1,0.996835,0.996835,1,1,1,0.981132,1,1,1]
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
0.6463669732012473
kappa
0.7094583925469762
kappa
0.6464088397790055
kappa
0.6715875898002684
kappa
0.6715097915350601
kappa
0.7156959526159921
kappa
0.7283745903904615
kappa
0.6652455392389073
kappa
0.6651794527579263
kappa
0.6652983896431954
kb_relative_information_score
104.1021811334494
kb_relative_information_score
106.00216267027871
kb_relative_information_score
105.13024007486965
kb_relative_information_score
105.32414908699977
kb_relative_information_score
104.98404786790738
kb_relative_information_score
105.48246628593668
kb_relative_information_score
107.44574613283179
kb_relative_information_score
104.48219649156921
kb_relative_information_score
105.31473799804533
kb_relative_information_score
104.72274334378055
mean_absolute_error
0.015028557689550807
mean_absolute_error
0.014819471249993868
mean_absolute_error
0.014996708524509239
mean_absolute_error
0.015028868265044081
mean_absolute_error
0.014829449879874057
mean_absolute_error
0.01493685194418159
mean_absolute_error
0.014714761147751587
mean_absolute_error
0.014948001295983832
mean_absolute_error
0.015030249002203993
mean_absolute_error
0.015076015945774771
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
0.65
predictive_accuracy
0.7125
predictive_accuracy
0.65
predictive_accuracy
0.675
predictive_accuracy
0.675
predictive_accuracy
0.71875
predictive_accuracy
0.73125
predictive_accuracy
0.66875
predictive_accuracy
0.66875
predictive_accuracy
0.66875
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
0.65 [1,1,1,1,1,1,1,1,0.5,1,0.5,0.5,1,0,1,1,1,0,0.5,0,1,0,0,1,0,0,0,1,0.5,0,0.5,1,0.5,0,1,0,1,1,1,0.5,1,1,1,1,0.5,1,1,1,1,0.5,1,0,1,0,1,0,1,1,0,0.5,1,1,0,1,1,1,0,0,0,1,0,1,0,1,1,0.5,1,0.5,1,1,0,1,1,1,0.5,0.5,1,1,0.5,1,1,1,1,0.5,1,0,1,0.5,0,1]
recall
0.7125 [0,1,1,1,1,1,0.5,1,1,1,1,1,1,0.5,1,1,1,0,0,1,1,1,1,1,1,0.5,0,0.5,1,1,1,1,1,0.5,1,0,0,1,1,1,1,1,1,0.5,1,1,1,0,0.5,1,1,0,1,0.5,1,0,1,1,0,0.5,1,1,1,1,1,0.5,0,1,0,0,0,1,1,1,0,0,0.5,0.5,1,0,0,0.5,1,1,0.5,1,1,1,1,1,1,1,1,0,1,1,1,0.5,0,1]
recall
0.65 [0,1,1,1,1,0.5,1,1,0.5,1,1,1,1,0.5,1,1,1,0,0,0,1,0,0,1,1,0,0.5,1,1,1,1,1,1,0,1,1,1,0,1,1,0.5,1,1,1,0.5,1,0.5,1,0.5,1,0.5,1,1,0,1,0.5,1,1,0,0,1,1,0.5,1,0.5,1,0,0,0,0.5,0,1,0,1,0,0.5,1,0.5,1,0.5,0,1,0.5,0.5,1,1,1,0.5,1,1,1,1,0,0,1,1,0.5,0.5,0,0.5]
recall
0.675 [0,1,1,1,1,0,1,0.5,0.5,1,0.5,1,1,0.5,1,0.5,1,0.5,0,0,1,1,0.5,1,1,0,0.5,0,1,1,1,0.5,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,0.5,1,0.5,1,0.5,0,0.5,1,1,0.5,1,1,1,0,1,0,0,0,1,1,1,0,0.5,1,0.5,1,0.5,1,0.5,1,1,1,0,1,1,1,1,1,1,0,0,1,1,0,0,0,0]
recall
0.675 [0,1,1,1,1,1,1,0.5,1,1,1,0.5,0,0,1,0.5,1,1,1,0,1,1,0.5,1,0.5,0.5,0,1,1,0.5,1,0,1,0.5,1,1,0.5,0,1,1,1,1,1,1,1,1,1,0.5,0.5,1,1,0,0.5,0,0.5,0,1,1,0,1,1,1,0,1,0.5,1,0,0,0,0.5,0.5,1,1,1,0,0,1,0,1,1,1,1,1,1,1,0,1,1,1,1,1,0.5,1,0,0.5,1,0.5,0,0,0.5]
recall
0.71875 [0,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,0,0,1,1,1,1,1,0.5,1,0,0.5,0.5,1,0,1,1,0.5,0,1,1,1,1,0,1,0.5,1,1,1,1,0.5,0.5,1,1,0,1,1,1,0,1,1,1,1,1,0,0.5,0,0.5,1,1,0.5,0,1,0.5,1,1,0,0.5,1,0.5,0,1,1,1,0,1,1,1,0,0,1,1,1,0,0,1]
recall
0.73125 [0.5,1,1,1,1,0,0.5,1,1,1,1,1,1,1,1,0.5,1,1,0.5,0,0.5,1,0.5,1,0.5,0,0,0.5,1,1,0.5,0,1,1,1,1,0.5,1,1,1,1,1,1,1,0,0.5,0.5,1,1,1,0,1,1,0,0.5,0.5,1,0.5,0,0,1,1,1,1,0.5,1,0,0.5,0.5,0.5,1,1,1,1,1,0,1,1,1,1,0,1,1,1,1,1,1,0,1,1,1,1,0,1,1,0.5,1,0,0,1]
recall
0.66875 [1,1,1,1,1,0.5,1,1,1,1,1,1,1,0,1,0.5,1,1,0.5,0,1,0.5,0.5,1,1,0,0,0.5,0,1,1,1,1,1,1,1,1,0,0.5,1,1,1,1,0.5,0,1,1,1,1,1,0,0.5,0.5,1,0.5,0,1,1,0,0,1,1,1,1,1,0,1,0.5,0,0,0,1,0.5,1,0.5,0,1,1,1,1,0,0,0,1,0,0.5,1,0,1,1,1,1,1,0,1,0.5,0,0,0,0.5]
recall
0.66875 [0,1,1,1,1,1,0.5,0,1,1,1,1,1,0.5,1,0,1,1,1,0,1,1,0,1,1,0,0,1,1,1,1,1,1,1,1,1,0,0.5,0.5,0,1,0.5,0.5,0.5,0,1,1,0.5,0,1,1,0.5,1,0.5,0.5,0,1,0,0,0.5,1,1,0.5,0.5,1,1,0.5,1,0.5,0,1,0,0,0.5,0.5,0,1,0,1,0.5,0.5,1,1,1,1,1,1,0.5,1,1,1,1,1,0,0,0.5,0,0,0.5,1]
recall
0.66875 [0,0.5,1,1,1,1,1,0,1,1,1,1,1,0,1,1,1,0,0,0,1,1,1,1,1,0,0,0.5,1,1,1,1,1,1,1,0.5,0.5,0.5,0.5,1,1,1,1,0.5,0.5,0.5,1,1,0,1,1,1,1,0,0.5,0,1,0,0,0.5,1,1,0,0.5,1,1,0.5,0,0,0,0,0,0,1,0,0,1,1,1,0.5,0.5,0,1,0,1,0.5,1,1,1,0.5,1,1,1,0.5,1,1,1,0.5,0.5,1]
relative_absolute_error
0.7590180651288274
relative_absolute_error
0.7484581439390829
relative_absolute_error
0.7574095214398594
relative_absolute_error
0.7590337507598008
relative_absolute_error
0.7489621151451531
relative_absolute_error
0.7543864618273518
relative_absolute_error
0.7431697549369476
relative_absolute_error
0.7549495604032227
relative_absolute_error
0.7591034849597963
relative_absolute_error
0.7614149467563003
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
0.08078776177853501
root_mean_squared_error
0.07933646780722761
root_mean_squared_error
0.08013051873954337
root_mean_squared_error
0.08036197239964545
root_mean_squared_error
0.07989268994166857
root_mean_squared_error
0.07991579467112382
root_mean_squared_error
0.07884131518616143
root_mean_squared_error
0.07990565308361144
root_mean_squared_error
0.08027632903036172
root_mean_squared_error
0.08102010740209298
root_relative_squared_error
0.8119475559758047
root_relative_squared_error
0.7973615027535881
root_relative_squared_error
0.8053420148957797
root_relative_squared_error
0.807668211704607
root_relative_squared_error
0.8029517455415615
root_relative_squared_error
0.8031839568097001
root_relative_squared_error
0.7923850316686257
root_relative_squared_error
0.8030820300201331
root_relative_squared_error
0.8068074634570437
root_relative_squared_error
0.814282717354662
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
1483.6645159994077
usercpu_time_millis
1343.070634000469
usercpu_time_millis
1363.960861999658
usercpu_time_millis
1356.310677001602
usercpu_time_millis
1372.9063870014215
usercpu_time_millis
1362.752883000212
usercpu_time_millis
1332.4880029977066
usercpu_time_millis
1337.301278999803
usercpu_time_millis
1338.6256949961535
usercpu_time_millis
1363.8907919958
usercpu_time_millis_testing
31.286006000300404
usercpu_time_millis_testing
32.08893600094598
usercpu_time_millis_testing
32.83774800001993
usercpu_time_millis_testing
32.28295100052492
usercpu_time_millis_testing
32.2510890000558
usercpu_time_millis_testing
31.614835999789648
usercpu_time_millis_testing
32.451332997879945
usercpu_time_millis_testing
33.29811699950369
usercpu_time_millis_testing
32.01766299753217
usercpu_time_millis_testing
32.25145999749657
usercpu_time_millis_training
1452.3785099991073
usercpu_time_millis_training
1310.981697999523
usercpu_time_millis_training
1331.123113999638
usercpu_time_millis_training
1324.027726001077
usercpu_time_millis_training
1340.6552980013657
usercpu_time_millis_training
1331.1380470004224
usercpu_time_millis_training
1300.0366699998267
usercpu_time_millis_training
1304.0031620002992
usercpu_time_millis_training
1306.6080319986213
usercpu_time_millis_training
1331.6393319983035