6016103
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)
4050792
bootstrap
true
6902
class_weight
null
6902
criterion
"entropy"
6902
max_depth
null
6902
max_features
0.6036642443171817
6902
max_leaf_nodes
null
6902
min_impurity_split
1e-07
6902
min_samples_leaf
9
6902
min_samples_split
5
6902
min_weight_fraction_leaf
0.0
6902
n_estimators
100
6902
n_jobs
1
6902
oob_score
false
6902
random_state
19937
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
12955337
description
https://api.openml.org/data/download/12955337/description.xml
-1
12955338
predictions
https://api.openml.org/data/download/12955338/predictions.arff
area_under_roc_curve
0.9938273358585856 [0.981258,0.999763,1,1,0.997475,0.993292,0.999566,0.998974,0.995265,0.999684,0.997277,0.999684,0.99858,0.978812,0.999211,0.998067,0.999961,0.981889,0.986387,0.965041,0.998698,0.999487,0.99199,1,0.997988,0.969973,0.989583,0.99637,0.996646,0.999645,0.999684,1,0.998027,0.989031,0.997672,0.998698,0.992385,0.987689,0.999014,0.999645,0.996015,0.998185,0.999961,0.998146,0.998658,0.999092,0.999171,0.993134,0.990925,0.997199,0.995502,0.991832,0.996528,0.979482,0.988636,0.976918,1,0.999645,0.994752,0.984217,0.999921,0.996765,0.994239,0.997909,0.997751,0.994476,0.976168,0.999842,0.97968,0.980074,0.993687,0.998146,0.993253,0.998264,0.967448,0.998303,0.999329,0.979837,0.99929,0.99925,0.989268,0.995502,0.996765,0.993845,0.995857,0.990215,0.999882,0.994831,0.997238,0.999882,0.999803,0.999408,0.997672,0.989781,0.998343,0.999211,0.995818,0.993174,0.966461,0.995739]
average_cost
0
f_measure
0.7375112928754727 [0.56,0.864865,1,0.969697,0.866667,0.482759,0.909091,0.810811,0.645161,0.903226,0.6875,0.857143,0.769231,0.5,0.903226,0.83871,0.842105,0.461538,0.540541,0.296296,0.769231,0.967742,0.62069,1,0.810811,0.285714,0.344828,0.722222,0.8,0.833333,0.83871,0.969697,0.875,0.606061,0.777778,0.789474,0.545455,0.5,0.903226,0.941176,0.689655,0.909091,0.882353,0.882353,0.8125,0.8125,0.875,0.785714,0.733333,0.83871,0.645161,0.709677,0.777778,0.592593,0.642857,0.25,1,0.941176,0.647059,0.666667,0.857143,0.736842,0.62069,0.823529,0.810811,0.75,0.193548,0.914286,0.48,0.521739,0.571429,0.777778,0.55814,0.848485,0.814815,0.83871,0.842105,0.434783,0.888889,0.967742,0.571429,0.6875,0.8125,0.571429,0.8125,0.903226,0.969697,0.684211,0.764706,0.967742,0.888889,0.769231,0.866667,0.615385,0.833333,0.8,0.714286,0.580645,0.272727,0.709677]
kappa
0.7468434343434344
kb_relative_information_score
1070.5682465276418
mean_absolute_error
0.014830392095493347
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
0.7511530398715418 [0.777778,0.761905,1,0.941176,0.928571,0.538462,0.882353,0.714286,0.666667,0.933333,0.6875,0.789474,0.652174,0.75,0.933333,0.866667,0.727273,0.6,0.47619,0.363636,0.652174,1,0.692308,1,0.714286,0.6,0.384615,0.65,0.857143,0.75,0.866667,0.941176,0.875,0.588235,0.7,0.681818,0.529412,0.45,0.933333,0.888889,0.769231,0.882353,0.833333,0.833333,0.8125,0.8125,0.875,0.916667,0.785714,0.866667,0.666667,0.733333,0.7,0.727273,0.75,0.375,1,0.888889,0.611111,0.818182,0.789474,0.636364,0.692308,0.777778,0.714286,0.625,0.2,0.842105,0.666667,0.857143,0.666667,0.7,0.444444,0.823529,1,0.866667,0.727273,0.714286,0.8,1,0.666667,0.6875,0.8125,0.666667,0.8125,0.933333,0.941176,0.590909,0.722222,1,0.8,0.652174,0.928571,0.8,0.75,0.736842,0.833333,0.6,0.5,0.733333]
predictive_accuracy
0.749375
prior_entropy
6.6438561897747395
recall
0.749375 [0.4375,1,1,1,0.8125,0.4375,0.9375,0.9375,0.625,0.875,0.6875,0.9375,0.9375,0.375,0.875,0.8125,1,0.375,0.625,0.25,0.9375,0.9375,0.5625,1,0.9375,0.1875,0.3125,0.8125,0.75,0.9375,0.8125,1,0.875,0.625,0.875,0.9375,0.5625,0.5625,0.875,1,0.625,0.9375,0.9375,0.9375,0.8125,0.8125,0.875,0.6875,0.6875,0.8125,0.625,0.6875,0.875,0.5,0.5625,0.1875,1,1,0.6875,0.5625,0.9375,0.875,0.5625,0.875,0.9375,0.9375,0.1875,1,0.375,0.375,0.5,0.875,0.75,0.875,0.6875,0.8125,1,0.3125,1,0.9375,0.5,0.6875,0.8125,0.5,0.8125,0.875,1,0.8125,0.8125,0.9375,1,0.9375,0.8125,0.5,0.9375,0.875,0.625,0.5625,0.1875,0.6875]
relative_absolute_error
0.7490097017925919
root_mean_prior_squared_error
0.09949874371066209
root_mean_squared_error
0.07876387718409253
root_relative_squared_error
0.791606750464452
total_cost
0
area_under_roc_curve
0.9932397400684658 [1,1,1,1,0.996835,1,1,1,0.993671,1,0.990506,0.996835,1,0.971519,1,1,1,0.962025,0.96519,0.993711,1,1,0.993711,1,1,0.987342,0.993671,1,0.987342,0.993711,1,1,1,0.996835,1,0.993711,1,0.993711,1,1,1,1,1,1,1,1,1,1,1,0.990506,0.96519,1,0.993711,0.993671,1,1,1,1,0.993711,0.984177,1,1,1,1,1,1,0.996835,1,1,0.949686,0.993671,1,0.993671,1,1,1,1,0.968354,1,1,0.996835,0.996835,0.993711,1,1,0.946203,1,0.996835,0.993671,1,1,1,1,0.990506,1,0.993671,1,1,0.867089,1]
area_under_roc_curve
0.9938756368919668 [0.981132,1,1,1,1,1,1,1,1,1,1,1,0.990506,0.939873,1,1,1,0.946203,1,0.987421,1,1,1,1,1,0.946203,0.984177,0.990506,1,1,1,1,1,1,0.996835,0.993711,0.974843,1,1,1,1,1,1,0.996835,1,1,1,1,0.993671,1,1,0.949367,1,1,0.993711,0.949686,1,1,1,0.949367,1,1,1,0.993671,1,1,1,1,0.974843,0.993711,1,1,1,1,1,1,1,0.971519,1,1,0.996835,0.996835,0.987421,0.987421,1,1,1,0.996835,0.993671,1,1,1,1,0.984177,1,1,1,0.987342,0.993671,1]
area_under_roc_curve
0.9932822824615875 [0.996835,1,1,1,0.993671,0.984177,1,1,0.987342,1,1,1,1,0.996835,0.993671,1,1,0.996835,0.974843,0.901899,1,1,0.955696,1,1,0.984177,1,1,1,1,1,1,1,0.962025,0.993711,1,0.993711,0.955975,1,1,1,1,1,1,0.993671,1,1,1,0.955696,1,0.993671,1,1,0.996835,1,0.981013,1,1,0.993711,0.974684,1,0.981132,1,1,1,0.987342,0.993671,1,0.974843,0.987342,0.996835,0.996835,0.993711,1,1,1,1,0.977848,1,1,1,0.996835,1,0.996835,1,1,1,1,0.993671,1,1,1,0.993711,0.987342,0.996835,1,0.996835,0.993671,0.968553,1]
area_under_roc_curve
0.993126293686808 [1,1,1,1,0.996835,0.996835,1,1,0.993671,1,1,1,1,0.996835,1,1,1,0.981013,0.943396,0.990506,1,1,0.993671,1,0.987421,0.977848,0.971519,1,1,1,1,1,1,0.990506,1,0.993711,1,1,1,1,0.996835,1,1,1,1,1,1,1,0.993671,1,1,1,1,0.955696,1,0.990506,1,1,1,0.993671,1,1,0.996835,1,0.993671,0.996835,0.946203,1,1,0.936709,0.993671,0.996835,0.974843,1,1,0.993671,1,0.96519,1,1,0.924528,0.987342,1,0.987342,1,1,1,1,1,1,1,1,0.962264,1,1,0.987421,0.984177,0.996835,0.993711,0.971519]
area_under_roc_curve
0.9906789865456572 [0.996835,1,1,1,1,0.996835,1,1,1,1,1,0.996835,1,0.830189,1,1,1,0.996835,1,0.984177,0.984177,1,1,1,0.993671,0.968354,0.993671,1,1,1,1,1,0.993671,0.977848,1,1,0.993671,0.971519,0.996835,1,1,1,1,1,1,1,1,1,1,1,1,0.974843,0.996835,0.993711,0.936709,0.968354,1,0.996835,0.996835,0.987421,1,1,0.987421,1,0.996835,1,0.893082,1,0.93038,0.987342,1,1,1,1,0.835443,1,0.993671,0.984177,1,1,1,1,0.996835,0.993671,0.987421,1,1,1,1,1,1,0.996835,1,0.993711,0.990506,1,0.996835,1,0.987421,0.993671]
area_under_roc_curve
0.9935561957646684 [0.924051,1,1,1,1,0.984177,1,1,1,0.996835,1,1,1,1,1,1,1,0.993671,1,0.908228,1,0.996835,0.993671,1,0.993671,0.993671,0.981013,0.993711,1,1,1,1,0.984177,0.996835,0.974843,1,0.981013,1,1,1,1,0.993671,1,1,1,1,1,0.990506,0.993671,0.990506,1,1,1,1,0.990506,0.96519,1,1,0.993671,1,1,0.996835,0.987421,1,1,0.993671,0.993711,1,0.993671,1,0.984177,0.990506,1,1,0.971519,1,1,0.996835,1,1,1,0.990506,1,0.993671,1,1,1,0.987421,0.990506,1,1,1,1,1,1,1,1,0.968553,0.993711,0.987342]
area_under_roc_curve
0.9960540064485309 [0.993671,1,1,1,1,1,1,1,0.993711,1,1,1,1,1,1,0.996835,1,0.993711,0.993671,0.958861,1,1,1,1,0.996835,0.867925,0.987421,1,1,1,1,1,1,1,1,1,0.996835,1,1,1,0.996835,0.996835,1,1,1,0.996835,0.996835,0.974684,1,1,1,1,1,1,0.993671,0.990506,1,1,0.993671,0.993711,1,1,1,0.981013,1,1,0.968553,1,1,0.996835,0.993711,1,1,1,1,1,1,0.981132,1,1,0.984177,1,0.993671,0.996835,1,1,1,0.974843,1,1,1,1,1,1,1,1,1,1,0.977848,1]
area_under_roc_curve
0.9950250278640234 [1,1,1,1,1,1,0.996835,1,0.993711,1,0.993711,1,1,1,1,0.996835,1,0.962264,0.987342,0.977848,0.996835,1,1,1,1,0.981132,0.974843,0.981013,1,0.996835,1,1,1,1,1,1,1,0.987342,1,1,1,1,1,1,1,1,1,1,1,1,0.993711,0.996835,0.987342,1,1,0.968354,1,1,0.990506,1,1,0.993671,0.987421,0.996835,1,0.962264,0.968553,1,0.977848,0.984177,1,1,1,0.981132,0.993671,1,1,0.987421,1,1,0.984177,1,0.984177,1,0.981013,0.987342,1,1,0.993711,1,1,1,1,0.987421,1,1,0.984177,1,0.987342,1]
area_under_roc_curve
0.9963291636812354 [0.962264,1,1,1,1,1,1,1,1,1,0.993711,1,1,1,1,1,1,1,1,1,1,1,0.968553,1,1,1,0.993711,1,0.993671,1,1,1,1,0.993711,1,1,1,0.984177,1,1,0.962264,1,1,0.990506,0.996835,0.996835,1,1,0.993711,1,1,0.996835,1,0.93038,1,0.955975,1,1,0.993671,0.996835,1,1,1,1,1,1,1,1,0.993671,1,1,0.993711,0.990506,1,1,0.993671,0.993711,1,1,0.996835,1,1,1,0.993711,0.996835,1,1,0.993671,1,1,1,0.993671,1,0.996835,1,1,0.993711,1,0.971519,1]
area_under_roc_curve
0.9968068326566357 [0.899371,1,1,1,1,1,1,0.993711,0.996835,1,1,1,1,0.996835,1,1,1,0.993711,0.993671,0.993711,1,1,1,1,1,0.962264,1,1,0.993671,1,1,1,1,0.974843,1,1,0.993671,1,1,1,1,1,1,0.996835,1,1,1,0.990506,1,1,1,0.996835,1,0.984177,1,1,1,1,0.993671,1,1,0.996835,0.981013,1,0.993711,1,1,1,1,1,0.981132,1,0.981013,1,1,0.996835,1,1,0.981132,1,1,0.974843,1,0.974843,1,1,0.996835,0.996835,1,1,1,1,1,0.996835,1,1,1,1,1,1]
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
0.7283960364770439
kappa
0.7725747226280255
kappa
0.7221125759848425
kappa
0.7409776514254126
kappa
0.7662942639453635
kappa
0.7346705097326964
kappa
0.7788833609729132
kappa
0.709423980417703
kappa
0.7599115463591849
kappa
0.7536226161803609
kb_relative_information_score
106.65503657361809
kb_relative_information_score
106.740614078105
kb_relative_information_score
105.96429717169862
kb_relative_information_score
106.01963214288679
kb_relative_information_score
105.5407571779912
kb_relative_information_score
106.46809992164553
kb_relative_information_score
109.2212976455596
kb_relative_information_score
106.72060734729399
kb_relative_information_score
108.60483561543504
kb_relative_information_score
108.63306885340953
mean_absolute_error
0.014818839951977487
mean_absolute_error
0.014881212794261318
mean_absolute_error
0.014929382306983882
mean_absolute_error
0.014919498164106699
mean_absolute_error
0.014854141070805293
mean_absolute_error
0.014890047937772568
mean_absolute_error
0.014606503049083003
mean_absolute_error
0.014849387293801575
mean_absolute_error
0.014779377354886158
mean_absolute_error
0.014775531031255456
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
0.73125
predictive_accuracy
0.775
predictive_accuracy
0.725
predictive_accuracy
0.74375
predictive_accuracy
0.76875
predictive_accuracy
0.7375
predictive_accuracy
0.78125
predictive_accuracy
0.7125
predictive_accuracy
0.7625
predictive_accuracy
0.75625
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
0.73125 [1,1,1,1,0.5,1,1,1,0.5,1,0.5,1,1,0,1,1,1,0,0.5,0,1,1,0,1,1,0.5,0,1,0.5,0,1,1,1,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,0.5,0.5,0.5,1,0,1,0,1,1,0,1,1,1,0,1,1,1,0.5,1,0,0,0.5,1,0.5,1,1,1,1,0.5,1,1,0,1,1,1,1,0.5,1,0.5,0.5,1,1,1,1,0,1,0.5,1,1,0,1]
recall
0.775 [0,1,1,1,1,1,0.5,1,0.5,1,0.5,1,0.5,0.5,1,1,1,0,0.5,0,1,1,1,1,1,0,0,0.5,0.5,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,0.5,1,1,1,0.5,1,1,0.5,1,1,1,0,1,1,1,0.5,1,1,1,1,1,1,0,1,0,0,1,1,1,1,1,1,1,0.5,1,1,0.5,0.5,1,0,1,1,1,1,1,1,1,1,1,0,1,1,1,0,0,1]
recall
0.725 [0.5,1,1,1,0.5,0,1,1,0,1,1,1,1,0.5,0,0.5,1,1,0,0,1,0,0.5,1,1,0.5,0.5,1,1,1,1,1,1,0.5,1,1,1,0,1,1,0,1,1,1,0.5,1,0.5,1,0.5,1,1,1,1,0.5,1,0,1,1,1,0,1,1,0.5,1,1,1,0.5,1,0,0,0,1,1,1,1,1,1,0,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,0.5,1,1,0.5,0.5,0,0.5]
recall
0.74375 [1,1,1,1,0.5,0,1,1,0.5,0.5,1,1,1,0.5,1,1,1,0.5,0,0,1,1,0.5,1,1,0,0.5,1,1,1,1,1,1,0.5,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,0.5,1,1,1,1,0.5,1,1,1,1,1,0.5,1,1,1,1,0.5,1,0,1,0,0.5,0,0.5,0,1,1,0.5,1,0,1,1,0,0.5,1,0.5,1,1,1,1,1,1,1,1,0,1,1,0,0.5,0.5,0,0]
recall
0.76875 [0.5,1,1,1,1,0.5,1,1,1,1,1,0.5,1,0,1,1,1,0.5,1,0.5,0.5,1,1,1,1,0.5,0,1,1,1,1,1,0.5,0.5,1,1,1,0.5,0.5,1,1,1,1,1,1,1,1,0.5,0.5,0.5,0,0,0.5,0,0,0,1,1,1,1,1,1,1,1,1,1,0,1,0.5,0.5,1,1,1,0,0.5,1,1,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,0.5,1,0.5,1,1,0.5]
recall
0.7375 [0,1,1,1,1,0.5,1,1,1,0.5,0,1,1,1,1,1,1,0.5,1,0,1,1,0.5,1,1,0,0.5,1,1,1,1,1,0.5,1,0,0.5,0.5,0.5,1,1,1,1,1,1,1,1,1,0,1,0.5,1,1,1,1,0,0,1,1,0,1,1,0.5,0,1,1,1,1,1,0.5,0.5,0.5,1,1,1,0.5,0,1,0.5,1,1,1,0.5,1,0.5,0,1,1,1,1,1,1,1,0,1,1,1,1,0,0,0.5]
recall
0.78125 [0.5,1,1,1,1,0.5,1,1,1,1,1,1,1,0,1,1,1,0,1,0.5,1,1,0.5,1,0.5,0,0,0.5,1,1,0.5,1,1,1,1,1,0.5,1,1,1,0.5,0.5,1,1,1,0.5,0.5,0.5,1,1,0,1,1,1,0.5,0.5,1,1,0.5,1,0.5,0.5,1,0.5,1,1,0,1,1,0,1,1,1,1,1,1,1,0,1,1,0.5,1,0.5,1,1,1,1,0,0,1,1,1,0.5,1,1,1,1,1,0,1]
recall
0.7125 [0.5,1,1,1,1,0,1,1,1,1,1,1,1,0,1,0.5,1,0,0.5,0,1,1,0.5,1,1,0,0,0.5,0,1,0,1,1,1,1,1,0.5,0,1,1,0.5,1,1,1,1,1,1,1,1,1,0,0.5,0.5,1,1,0,1,1,1,1,1,1,1,0.5,1,0,0,1,0,1,0,1,1,0,1,1,1,0,1,1,0,0,0,1,0,0.5,1,1,1,1,1,1,1,0,1,1,0,1,0,1]
recall
0.7625 [0,1,1,1,1,1,1,1,0.5,1,0,1,1,0.5,1,0,1,1,1,1,1,1,0,1,1,0,1,1,1,1,1,1,1,1,0.5,1,1,0,1,1,0,1,1,1,0.5,0.5,1,1,0,1,0.5,0.5,1,0.5,0.5,0,1,1,0.5,0,1,1,0.5,1,1,1,0,1,0.5,1,1,1,0.5,1,0.5,1,1,1,1,0.5,0.5,1,1,0,1,1,1,0.5,0,1,1,0.5,1,0.5,1,1,0,0.5,0.5,1]
recall
0.75625 [0,1,1,1,1,1,1,0,1,1,1,1,1,0.5,1,1,1,0,0.5,1,1,1,1,1,1,0,1,1,0.5,1,1,1,1,0,1,1,0,1,0.5,1,1,1,0.5,0.5,1,0.5,1,0.5,1,1,0.5,1,1,0,0.5,0,1,1,1,0.5,1,1,0,1,1,1,0,1,0.5,0,0,0,0.5,1,0,0.5,1,1,1,1,1,0,1,0,1,1,1,1,1,0.5,1,1,1,0.5,1,1,1,0.5,0.5,1]
relative_absolute_error
0.7484262602008819
relative_absolute_error
0.7515764037505704
relative_absolute_error
0.7540092074234273
relative_absolute_error
0.7535100082882158
relative_absolute_error
0.7502091449901651
relative_absolute_error
0.7520226231198254
relative_absolute_error
0.7377021741961102
relative_absolute_error
0.7499690552425026
relative_absolute_error
0.746433199741724
relative_absolute_error
0.7462389409724964
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
0.07862110376131576
root_mean_squared_error
0.07879006469351588
root_mean_squared_error
0.07936235162006469
root_mean_squared_error
0.07923612985145291
root_mean_squared_error
0.07906730045753332
root_mean_squared_error
0.07925400490619303
root_mean_squared_error
0.07762522828015535
root_mean_squared_error
0.07896638529463607
root_mean_squared_error
0.07826658241716873
root_mean_squared_error
0.07843293198985779
root_relative_squared_error
0.7901718235754056
root_relative_squared_error
0.7918699448370313
root_relative_squared_error
0.7976216448606316
root_relative_squared_error
0.7963530683549942
root_relative_squared_error
0.7946562691028294
root_relative_squared_error
0.7965327194146306
root_relative_squared_error
0.7801628983968488
root_relative_squared_error
0.7936420335543815
root_relative_squared_error
0.7866087500035627
root_relative_squared_error
0.7882806261146099
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
5188.622411999859
usercpu_time_millis
5023.217693999868
usercpu_time_millis
5128.989156999523
usercpu_time_millis
5074.163813000268
usercpu_time_millis
5001.825188999646
usercpu_time_millis
5009.1098209995835
usercpu_time_millis
5036.883517000206
usercpu_time_millis
5005.422235999504
usercpu_time_millis
5034.966830000485
usercpu_time_millis
5109.766876999856
usercpu_time_millis_testing
32.650522999574605
usercpu_time_millis_testing
32.400494999819784
usercpu_time_millis_testing
32.308756999555044
usercpu_time_millis_testing
32.25111000028846
usercpu_time_millis_testing
32.16800599966518
usercpu_time_millis_testing
32.77918599997065
usercpu_time_millis_testing
32.2260519997144
usercpu_time_millis_testing
32.516153999495145
usercpu_time_millis_testing
32.35056999983499
usercpu_time_millis_testing
32.24152700022387
usercpu_time_millis_training
5155.971889000284
usercpu_time_millis_training
4990.817199000048
usercpu_time_millis_training
5096.680399999968
usercpu_time_millis_training
5041.91270299998
usercpu_time_millis_training
4969.657182999981
usercpu_time_millis_training
4976.330634999613
usercpu_time_millis_training
5004.657465000491
usercpu_time_millis_training
4972.906082000009
usercpu_time_millis_training
5002.61626000065
usercpu_time_millis_training
5077.525349999632