5996933
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)
4031666
bootstrap
false
6902
class_weight
null
6902
criterion
"entropy"
6902
max_depth
null
6902
max_features
0.6716768941155856
6902
max_leaf_nodes
null
6902
min_impurity_split
1e-07
6902
min_samples_leaf
13
6902
min_samples_split
13
6902
min_weight_fraction_leaf
0.0
6902
n_estimators
100
6902
n_jobs
1
6902
oob_score
false
6902
random_state
61817
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
12916999
description
https://api.openml.org/data/download/12916999/description.xml
-1
12917000
predictions
https://api.openml.org/data/download/12917000/predictions.arff
area_under_roc_curve
0.9886710858585859 [0.977667,0.998461,0.999763,0.999724,0.996252,0.988202,0.997909,0.995857,0.995778,0.998343,0.996883,0.997396,0.994397,0.976997,0.996922,0.992858,0.999645,0.973879,0.975773,0.960701,0.997356,0.998303,0.988952,1,0.989781,0.956795,0.973288,0.989504,0.996488,0.998737,0.99925,0.999882,0.993253,0.980508,0.993924,0.997909,0.976681,0.979443,0.997593,0.999566,0.970486,0.995186,0.999211,0.995462,0.995344,0.982678,0.997869,0.990925,0.978496,0.982047,0.98114,0.984257,0.993647,0.962831,0.990175,0.958688,1,0.998974,0.992424,0.980508,0.999171,0.995423,0.993174,0.995857,0.995502,0.990688,0.97021,0.999763,0.946654,0.96295,0.981179,0.997356,0.989149,0.995344,0.964449,0.988913,0.998501,0.963068,0.998501,0.998106,0.98911,0.990175,0.989228,0.992898,0.990609,0.971788,0.999605,0.988636,0.995896,0.998816,0.998619,0.998737,0.992148,0.983467,0.9942,0.995818,0.993016,0.989228,0.956045,0.984138]
average_cost
0
f_measure
0.6043093066100977 [0.482759,0.769231,0.941176,0.866667,0.764706,0.533333,0.8,0.857143,0.645161,0.774194,0.625,0.764706,0.634146,0.4,0.722222,0.592593,0.810811,0.375,0.5,0,0.65,0.8125,0.484848,1,0.540541,0.105263,0.342857,0.588235,0.857143,0.8,0.615385,0.914286,0.685714,0.428571,0.702703,0.7,0.378378,0.388889,0.64,0.810811,0.516129,0.702703,0.857143,0.666667,0.666667,0.5,0.684211,0.64,0.642857,0.8,0.533333,0.551724,0.647059,0.333333,0.466667,0.148148,0.914286,0.756757,0.444444,0.518519,0.833333,0.585366,0.5625,0.722222,0.684211,0.514286,0.275862,0.820513,0.347826,0.25,0.32,0.717949,0.526316,0.764706,0.454545,0.785714,0.789474,0.1,0.882353,0.866667,0.615385,0.5,0.611111,0.37037,0.628571,0.756757,0.866667,0.540541,0.592593,0.75,0.744186,0.780488,0.615385,0.105263,0.56,0.65,0.606061,0.466667,0,0.571429]
kappa
0.6224747474747474
kb_relative_information_score
1066.1594975132646
mean_absolute_error
0.014398638976724998
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
0.6149599922529522 [0.538462,0.652174,0.888889,0.928571,0.722222,0.571429,0.736842,0.789474,0.666667,0.8,0.625,0.722222,0.52,0.555556,0.65,0.727273,0.714286,0.375,0.5,0,0.541667,0.8125,0.470588,1,0.47619,0.333333,0.315789,0.555556,0.789474,0.736842,0.8,0.842105,0.631579,0.5,0.619048,0.583333,0.333333,0.35,0.888889,0.714286,0.533333,0.619048,0.789474,0.647059,0.647059,0.583333,0.590909,0.888889,0.75,0.857143,0.571429,0.615385,0.611111,0.5,0.5,0.181818,0.842105,0.666667,0.4,0.636364,0.75,0.48,0.5625,0.65,0.590909,0.473684,0.307692,0.695652,0.571429,0.375,0.444444,0.608696,0.454545,0.722222,0.833333,0.916667,0.681818,0.25,0.833333,0.928571,0.8,0.583333,0.55,0.454545,0.578947,0.666667,0.928571,0.47619,0.727273,0.75,0.592593,0.64,0.8,0.333333,0.777778,0.541667,0.588235,0.5,0,0.666667]
predictive_accuracy
0.62625
prior_entropy
6.6438561897747395
recall
0.62625 [0.4375,0.9375,1,0.8125,0.8125,0.5,0.875,0.9375,0.625,0.75,0.625,0.8125,0.8125,0.3125,0.8125,0.5,0.9375,0.375,0.5,0,0.8125,0.8125,0.5,1,0.625,0.0625,0.375,0.625,0.9375,0.875,0.5,1,0.75,0.375,0.8125,0.875,0.4375,0.4375,0.5,0.9375,0.5,0.8125,0.9375,0.6875,0.6875,0.4375,0.8125,0.5,0.5625,0.75,0.5,0.5,0.6875,0.25,0.4375,0.125,1,0.875,0.5,0.4375,0.9375,0.75,0.5625,0.8125,0.8125,0.5625,0.25,1,0.25,0.1875,0.25,0.875,0.625,0.8125,0.3125,0.6875,0.9375,0.0625,0.9375,0.8125,0.5,0.4375,0.6875,0.3125,0.6875,0.875,0.8125,0.625,0.5,0.75,1,1,0.5,0.0625,0.4375,0.8125,0.625,0.4375,0,0.5]
relative_absolute_error
0.7272039887234834
root_mean_prior_squared_error
0.09949874371066209
root_mean_squared_error
0.07876530099801671
root_relative_squared_error
0.7916210603328088
total_cost
0
area_under_roc_curve
0.9886924309370271 [1,1,1,1,0.996835,1,1,1,0.996835,1,1,0.987342,0.987342,0.958861,1,1,1,0.96519,0.955696,0.981132,1,0.993711,0.993711,1,0.993711,0.990506,0.981013,0.996835,0.996835,0.993711,1,1,0.990506,0.981013,1,0.987421,1,0.993711,1,1,1,1,1,1,1,0.996835,1,1,1,0.968354,0.892405,1,1,0.987342,1,0.993711,1,1,0.987421,0.974684,1,1,0.996835,0.993671,1,1,0.996835,1,1,0.955975,0.968354,1,0.987342,0.996835,1,1,1,0.981013,0.996835,1,1,0.990506,0.993711,1,0.990506,0.851266,1,0.993671,0.993671,0.987421,1,1,1,0.984177,1,0.990506,1,0.996835,0.85443,1]
area_under_roc_curve
0.9898871009473769 [0.987421,1,1,1,1,1,0.993671,1,0.996835,1,0.993671,1,0.993671,0.949367,1,1,1,0.943038,0.996835,0.987421,1,1,0.993711,1,1,0.946203,0.987342,0.955696,0.996835,1,1,1,1,0.990506,0.996835,1,0.924528,1,0.993711,1,0.993711,1,1,1,1,0.987342,1,1,0.990506,1,1,0.939873,1,0.987342,0.993711,0.937107,1,1,1,0.933544,1,1,1,0.993671,1,1,0.993671,1,0.893082,1,0.990506,1,0.990506,1,1,1,1,0.943038,1,1,0.987342,0.993671,0.962264,0.987421,1,1,0.993671,0.996835,0.977848,1,0.996835,1,1,0.968354,0.993671,0.996835,1,0.974684,0.993671,1]
area_under_roc_curve
0.9884608112411433 [0.984177,0.996835,1,1,0.990506,0.977848,0.993711,1,0.981013,0.996835,0.996835,1,1,0.993671,0.977848,0.990506,1,0.987342,0.937107,0.898734,1,0.981132,0.946203,1,0.949686,0.984177,1,1,1,1,1,1,1,0.96519,0.987421,1,0.993711,0.949686,1,1,0.984177,1,1,1,0.993671,1,0.996835,1,0.873418,0.996835,0.990506,1,1,0.974684,1,0.993671,1,0.996835,0.987421,0.984177,1,0.987421,0.993671,1,0.996835,0.968354,0.987342,1,0.981132,0.936709,1,0.993671,0.981132,0.993671,1,1,1,0.962025,0.996835,1,1,1,1,0.996835,1,1,1,0.996835,1,1,0.996835,1,0.993711,0.981013,0.993671,1,0.990506,0.987342,0.987421,0.996835]
area_under_roc_curve
0.9886600887668177 [0.993671,0.996835,1,1,0.993671,0.974684,1,1,0.993671,0.996835,1,0.996835,1,1,1,1,1,0.981013,0.855346,0.987342,1,1,0.996835,1,0.962264,0.968354,0.927215,1,1,1,1,1,1,0.993671,1,0.987421,1,1,1,1,0.990506,1,1,1,1,1,1,1,0.987342,1,0.993671,1,0.987421,0.927215,1,0.996835,1,1,1,0.993671,1,1,1,1,0.990506,0.993671,0.952532,1,1,0.905063,0.987342,0.993671,0.993711,1,0.993711,0.946203,1,0.924051,1,0.996835,0.955975,0.977848,1,0.987342,1,1,1,1,1,1,1,1,0.968553,0.993671,1,0.981132,0.977848,0.993671,0.987421,0.946203]
area_under_roc_curve
0.9856181832656633 [0.987342,1,1,1,0.993711,0.987342,0.993711,1,1,1,0.993671,0.993671,1,0.874214,1,0.990506,1,0.996835,0.993711,0.990506,0.981013,0.993671,1,1,0.996835,0.952532,0.993671,1,1,1,1,1,0.984177,0.946203,1,1,0.987342,0.943038,0.990506,1,1,0.996835,0.987421,1,1,0.993711,1,0.987342,1,0.993671,0.993711,0.962264,0.990506,0.981132,0.968354,0.914557,1,0.990506,0.993671,0.981132,1,1,1,1,0.996835,1,0.880503,1,0.781646,0.96519,1,1,1,0.987421,0.901899,1,0.993671,0.943038,1,1,1,1,0.993671,0.996835,0.981132,1,1,1,1,1,1,0.993671,0.993711,0.987421,0.984177,1,0.993671,1,0.987421,0.974684]
area_under_roc_curve
0.9863635458960273 [0.908228,1,1,1,1,0.987342,1,1,1,0.996835,1,1,1,0.993711,1,1,1,1,1,0.93038,1,0.996835,0.974684,1,0.990506,0.987342,0.974684,0.993711,1,1,1,1,0.974684,0.990506,0.962264,1,0.933544,0.984177,1,1,1,0.968354,1,1,1,1,1,0.993671,0.977848,0.920886,1,0.974843,1,1,0.984177,0.939873,1,1,1,1,1,0.993671,0.968553,1,1,1,0.974843,1,0.974684,1,0.920886,0.990506,1,1,0.870253,1,0.996835,0.968354,1,0.993711,1,0.987342,1,0.990506,0.993711,1,1,0.974843,0.987342,1,1,0.996835,0.955975,0.993711,1,1,0.996835,0.962264,0.987421,0.955696]
area_under_roc_curve
0.9909616073561018 [0.987342,1,1,1,1,1,1,1,0.993711,1,1,1,0.971519,0.981132,0.993711,0.990506,0.987421,0.949686,0.984177,0.981013,0.987342,0.993671,1,1,0.984177,0.855346,0.993711,0.977848,1,1,1,1,1,0.993711,1,1,0.993671,0.996835,1,0.987421,0.981013,0.996835,1,0.996835,1,0.993671,0.987342,0.981013,1,1,0.987421,0.993671,0.996835,0.974843,0.996835,0.974684,1,1,0.993671,0.981132,1,0.996835,1,0.974684,1,0.987421,0.949686,1,0.987342,0.968354,0.993711,1,0.996835,1,0.993671,1,1,0.974843,1,1,0.984177,1,0.974684,0.996835,1,1,1,0.962264,1,1,1,1,0.987342,0.974843,0.981132,0.990506,1,0.987421,0.939873,1]
area_under_roc_curve
0.990443386274978 [1,1,1,1,1,0.987342,0.996835,1,0.993711,1,0.993711,1,1,1,1,0.984177,1,0.949686,0.990506,0.936709,0.990506,1,1,1,0.996835,0.962264,0.924528,0.984177,1,0.996835,1,1,1,1,1,1,0.984177,0.977848,1,1,1,1,1,0.993671,1,0.993671,1,1,0.993711,1,0.981132,0.981013,0.977848,1,0.996835,0.958861,1,1,0.990506,1,1,0.993671,0.993711,0.996835,1,0.974843,0.962264,1,0.96519,0.987342,0.993711,1,1,0.955975,0.984177,1,1,0.974843,1,1,0.987342,1,0.962025,0.996835,0.971519,0.955696,1,0.974843,1,1,1,0.996835,0.996835,0.974843,0.993711,1,0.984177,0.993711,0.958861,0.984177]
area_under_roc_curve
0.9917109505612608 [0.968553,1,1,1,1,1,0.993671,1,1,1,0.987421,1,1,1,1,0.993711,1,1,1,1,1,1,0.993711,1,1,1,0.962264,1,0.987342,1,1,1,1,0.987421,0.996835,1,0.993671,0.943038,1,1,0.786164,1,1,0.984177,0.987342,0.971519,1,0.996835,0.974843,1,1,0.996835,1,0.882911,0.987342,0.955975,1,1,0.996835,0.990506,0.996835,0.996835,1,1,1,1,0.987342,1,0.981013,0.987421,1,0.993711,0.977848,1,0.996835,0.981013,1,1,1,0.996835,1,0.993711,0.993711,0.993711,0.993671,1,1,0.981013,1,1,1,1,1,0.987342,0.987421,0.990506,0.987421,0.993671,0.993671,1]
area_under_roc_curve
0.9929421921025394 [0.968553,0.996835,0.993711,1,1,0.993711,1,0.937107,0.996835,1,1,1,0.993671,0.987342,0.996835,1,1,0.993711,0.990506,0.993711,1,1,1,1,1,0.842767,1,0.996835,0.990506,1,1,1,1,0.974843,0.996835,0.996835,0.987342,1,1,1,0.987421,1,1,0.996835,1,0.93038,1,0.990506,1,0.993711,1,0.990506,1,0.984177,0.993671,0.924528,1,1,0.987342,1,1,0.993671,0.974684,1,0.987421,1,0.993671,1,0.993671,0.955975,0.968553,1,0.977848,1,0.993671,0.996835,1,0.993711,0.981132,1,1,0.962264,1,0.974843,1,1,1,1,1,1,1,1,1,0.996835,1,1,1,1,1,0.993711]
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
0.6337372222441489
kappa
0.6589832649194821
kappa
0.595895816890292
kappa
0.6525721504994275
kappa
0.5957681983262276
kappa
0.5894844872503355
kappa
0.5956404991312588
kappa
0.6021314387211367
kappa
0.646269245953415
kappa
0.65254471512615
kb_relative_information_score
107.3209532029916
kb_relative_information_score
106.25807155976071
kb_relative_information_score
105.1316859563904
kb_relative_information_score
105.16713543951181
kb_relative_information_score
105.67174589312356
kb_relative_information_score
104.72445235039646
kb_relative_information_score
107.05227052705727
kb_relative_information_score
106.88330562245626
kb_relative_information_score
109.36667025499172
kb_relative_information_score
108.58320670658524
mean_absolute_error
0.014313132870455849
mean_absolute_error
0.014468236898037732
mean_absolute_error
0.014469201838028464
mean_absolute_error
0.014535485286705651
mean_absolute_error
0.014381092686288394
mean_absolute_error
0.01444383592316357
mean_absolute_error
0.014470672351896006
mean_absolute_error
0.014353416234693286
mean_absolute_error
0.014212484884969318
mean_absolute_error
0.014338830793011615
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
0.6375
predictive_accuracy
0.6625
predictive_accuracy
0.6
predictive_accuracy
0.65625
predictive_accuracy
0.6
predictive_accuracy
0.59375
predictive_accuracy
0.6
predictive_accuracy
0.60625
predictive_accuracy
0.65
predictive_accuracy
0.65625
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
0.6375 [1,1,1,1,0.5,1,1,1,1,1,0.5,0.5,1,0,1,1,1,0,0,0,1,0,0,1,1,0,0,1,0.5,0,0.5,1,0.5,0,1,0,0,1,1,1,1,1,1,1,1,0.5,1,1,0.5,0.5,0.5,1,1,0,1,0,1,1,1,0.5,1,1,0,0.5,1,0.5,0.5,1,0,0,0,1,0.5,1,1,1,1,0,1,1,0.5,0.5,1,0,1,0.5,1,0.5,0,0,1,1,1,0.5,0.5,0.5,1,0.5,0,1]
recall
0.6625 [1,1,1,1,1,1,0.5,1,0.5,1,0.5,1,1,0.5,1,1,1,0,0.5,0,1,1,0,1,1,0.5,0.5,0,1,1,0.5,1,1,0.5,0.5,1,0,1,0,1,1,1,1,1,0.5,0,1,0,0,1,0.5,0.5,1,0,1,0,1,1,1,0.5,1,1,1,1,1,0.5,0.5,1,0,0,0.5,1,0.5,1,1,1,1,0,1,1,0,0,0,0,1,1,0.5,1,0.5,1,1,1,0.5,0,0.5,1,1,0,0,1]
recall
0.6 [0,1,1,1,0.5,0,1,1,0,1,0.5,1,1,0.5,0.5,0,1,0.5,0,0,1,0,0.5,1,0,0,0.5,1,1,1,0,1,1,0,0,1,1,0,1,1,0,1,1,1,0.5,1,0.5,1,0.5,0.5,0.5,1,1,0.5,1,0,1,1,1,0,1,1,0.5,1,0.5,0.5,0.5,1,0,0,0.5,1,0,0.5,0,0.5,1,0,0.5,1,1,0.5,1,0.5,1,1,1,0.5,1,1,1,1,1,0,0.5,1,0.5,0.5,0,0.5]
recall
0.65625 [0.5,1,1,1,0.5,0,1,1,0.5,0.5,1,0.5,1,0.5,1,1,1,0.5,0,0,0,1,0.5,1,0,0,0.5,1,1,0.5,1,1,1,0.5,1,0,1,0,1,1,0.5,1,1,1,1,1,0.5,1,1,1,0,1,0,0,1,1,1,1,0,0.5,1,1,1,1,0.5,1,0,1,0,0.5,0,0.5,1,1,0,0.5,1,0,1,1,0,0.5,1,0.5,1,1,1,1,1,1,1,1,0,0,1,0,0.5,0.5,0,0]
recall
0.6 [0.5,1,1,1,1,0.5,0,1,1,1,0.5,0.5,1,0,1,0.5,1,1,1,0,0.5,0.5,1,1,1,0,0.5,1,1,1,0,1,0,0,1,1,1,0,0,1,1,0.5,1,1,1,0,1,0,0.5,0.5,0,0,0.5,0,0,0,1,0.5,1,0,1,1,1,1,0.5,0,0,1,0,0.5,0,1,1,0,0,1,0.5,0,1,1,0,1,0.5,0,0,1,1,1,1,1,1,1,1,0,0.5,1,0.5,1,0,0.5]
recall
0.59375 [0,1,1,0.5,1,0.5,1,1,1,0.5,0,1,1,1,1,0.5,1,0.5,1,0,1,1,0.5,1,0.5,0,0.5,1,1,1,0,1,0.5,0.5,0,1,0.5,0.5,0.5,1,1,0.5,1,1,1,1,1,0,0.5,0.5,1,0,1,1,0,0,1,1,0,1,0.5,0.5,0,1,1,0.5,0,1,0.5,0.5,0.5,1,1,1,0,0,1,0,1,0,1,0,1,0.5,0,1,0,0,0,1,1,1,0,0,0,1,0.5,0,0,0.5]
recall
0.6 [0.5,1,1,0.5,1,1,1,1,1,1,1,1,0.5,0,0,0.5,0,0,0.5,0,1,1,0.5,1,0.5,0,0,0,1,1,0.5,1,1,0,1,1,0,1,0.5,0,0,0.5,1,0.5,0,0.5,0.5,0.5,1,1,0,0.5,0.5,0,0.5,0,1,0.5,0.5,0,1,0.5,1,0.5,1,1,0,1,0.5,0,1,1,1,1,1,1,1,0,1,1,0.5,1,0.5,0.5,1,1,0.5,0,0,0,1,1,0.5,0,0,0.5,1,0,0,0.5]
recall
0.60625 [1,1,1,0.5,1,0,1,1,1,0.5,1,1,0.5,0,1,0.5,1,0,0.5,0,0.5,1,0.5,1,0.5,0,0,0.5,1,1,0,1,1,1,1,1,0,0,1,1,0.5,1,1,0,1,0.5,1,1,1,1,0,0.5,0.5,1,0.5,0,1,1,0.5,1,1,0.5,1,1,1,0,1,1,0,0,0,1,1,0,0,1,1,0,1,1,0,0,0,0.5,0,0.5,1,0,1,1,1,1,0,0,0,1,0.5,1,0,0.5]
recall
0.65 [0,1,1,1,1,1,1,1,0,1,1,1,1,0,1,0,1,1,1,0,1,1,0,1,1,0,0,1,1,1,1,1,1,1,1,1,1,0,0.5,1,0,1,1,0.5,0,0,1,0.5,0,1,1,0,1,0,0,0,1,1,0.5,0,1,1,0.5,0.5,1,1,0,1,0.5,0,0,0,0.5,1,0.5,0.5,1,1,1,0.5,1,1,1,0,0.5,1,1,0.5,0,1,1,1,0,0,0,1,0,0.5,0,1]
recall
0.65625 [0,0.5,1,1,1,1,1,0,1,0,1,1,0.5,0.5,0.5,0,1,0,0.5,0,1,1,1,1,0.5,0,1,0.5,1,1,1,1,1,1,1,1,0,1,0,1,0,1,0.5,0.5,1,0.5,1,0.5,1,1,1,0.5,0.5,0.5,0.5,0,1,1,0,1,1,0.5,0,1,1,1,0,1,0.5,0,0,1,0,1,0,0.5,1,0,1,0.5,1,0,1,0,1,1,1,1,0,0.5,1,1,1,0,1,1,1,0.5,0,0]
relative_absolute_error
0.7228854985078699
relative_absolute_error
0.7307190352544296
relative_absolute_error
0.7307677695973959
relative_absolute_error
0.7341154185204863
relative_absolute_error
0.7263178124388067
relative_absolute_error
0.7294866627860377
relative_absolute_error
0.7308420379745445
relative_absolute_error
0.7249200118531951
relative_absolute_error
0.717802266917641
relative_absolute_error
0.7241833733844237
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
0.07800984792766356
root_mean_squared_error
0.0786786306782386
root_mean_squared_error
0.07939437932793893
root_mean_squared_error
0.0791778001909607
root_mean_squared_error
0.0790105131766116
root_mean_squared_error
0.07944131728515516
root_mean_squared_error
0.07936265522304148
root_mean_squared_error
0.07857455890621666
root_mean_squared_error
0.07747453062613038
root_mean_squared_error
0.07850472769524344
root_relative_squared_error
0.784028471299223
root_relative_squared_error
0.7907499908444329
root_relative_squared_error
0.7979435354361284
root_relative_squared_error
0.7957668332095352
root_relative_squared_error
0.7940855354553087
root_relative_squared_error
0.7984152796558617
root_relative_squared_error
0.7976246961853566
root_relative_squared_error
0.7897040301806021
root_relative_squared_error
0.7786483299871896
root_relative_squared_error
0.7890022001034679
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
7102.1598810002615
usercpu_time_millis
6928.397249999762
usercpu_time_millis
6880.319194999174
usercpu_time_millis
6817.889874000684
usercpu_time_millis
6843.169843998112
usercpu_time_millis
6826.403444998505
usercpu_time_millis
6839.086585998302
usercpu_time_millis
6888.643756999954
usercpu_time_millis
6869.785174998469
usercpu_time_millis
6999.598336999043
usercpu_time_millis_testing
34.258572000908316
usercpu_time_millis_testing
33.18105000107607
usercpu_time_millis_testing
33.16534599980514
usercpu_time_millis_testing
33.359888000632054
usercpu_time_millis_testing
32.92691099886724
usercpu_time_millis_testing
33.20104799968249
usercpu_time_millis_testing
32.95185099887021
usercpu_time_millis_testing
33.128814000519924
usercpu_time_millis_testing
33.06646999953955
usercpu_time_millis_testing
33.095533999585314
usercpu_time_millis_training
7067.901308999353
usercpu_time_millis_training
6895.216199998686
usercpu_time_millis_training
6847.153848999369
usercpu_time_millis_training
6784.529986000052
usercpu_time_millis_training
6810.242932999245
usercpu_time_millis_training
6793.202396998822
usercpu_time_millis_training
6806.134734999432
usercpu_time_millis_training
6855.514942999434
usercpu_time_millis_training
6836.71870499893
usercpu_time_millis_training
6966.502802999457