8805409
1
Jan van Rijn
9954
Supervised Classification
7707
sklearn.pipeline.Pipeline(imputation=openmlstudy14.preprocessing.ConditionalImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,scaling=sklearn.preprocessing.data.StandardScaler,variencethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,classifier=sklearn.svm.classes.SVC)(1)
6780490
axis
0
7660
categorical_features
[]
7660
copy
true
7660
fill_empty
0
7660
missing_values
"NaN"
7660
strategy
"mean"
7660
strategy_nominal
"most_frequent"
7660
verbose
0
7660
categorical_features
[]
7661
dtype
{"oml-python:serialized_object": "type", "value": "np.float64"}
7661
handle_unknown
"ignore"
7661
n_values
"auto"
7661
sparse
true
7661
threshold
0.0
7662
copy
true
7663
with_mean
false
7663
with_std
true
7663
C
60.849852722106306
7708
cache_size
200
7708
class_weight
null
7708
coef0
-0.6280163651261268
7708
decision_function_shape
null
7708
degree
2
7708
gamma
0.05419516065575978
7708
kernel
"rbf"
7708
max_iter
-1
7708
probability
true
7708
random_state
3213
7708
shrinking
true
7708
tol
0.011216976979368841
7708
verbose
false
7708
openml-pimp
openml-python
Sklearn_0.18.1.
study_71
1491
one-hundred-plants-margin
https://www.openml.org/data/download/1592283/phpCsX3fx
-1
18526809
description
https://api.openml.org/data/download/18526809/description.xml
-1
18526810
predictions
https://api.openml.org/data/download/18526810/predictions.arff
area_under_roc_curve
0.9959655145202017 [0.992977,0.999724,1,0.998303,0.997554,0.990412,0.999921,0.999921,0.998067,0.987374,0.998935,0.999408,0.999527,0.950047,0.999448,0.998698,1,0.988123,0.987413,0.976681,0.997554,0.999842,0.995857,1,0.99929,0.980982,0.990136,0.999211,0.999369,0.999882,0.999724,0.993845,0.999921,0.990609,0.99858,0.999014,0.994476,0.985006,0.99925,0.999448,0.997948,0.998027,1,0.99858,0.999566,0.999448,0.998146,0.999171,0.998343,0.99854,0.996607,0.998027,0.997514,0.993608,0.995975,0.99203,1,0.999921,0.996133,0.993056,0.999408,0.999448,0.995068,0.999763,0.999605,0.994673,0.987176,1,0.997159,0.996843,0.996567,0.998816,0.995186,0.99929,0.977549,0.999961,0.999724,0.98548,1,0.999211,0.99349,0.996883,0.997396,0.996567,0.999527,0.999882,1,0.998816,0.998974,0.999803,0.999487,0.998974,0.998067,0.998935,0.999211,0.998619,0.995265,0.998185,0.973682,0.998698]
average_cost
0
f_measure
0.8280520629202008 [0.83871,0.967742,0.933333,0.7,0.903226,0.628571,1,0.967742,0.740741,0.933333,0.9375,0.866667,0.933333,0.8125,0.666667,0.9375,1,0.5625,0.444444,0.342857,0.8125,0.933333,0.833333,0.967742,0.9375,0.4,0.484848,0.8,0.903226,0.967742,0.967742,0.967742,0.969697,0.588235,0.875,0.875,0.516129,0.451613,0.903226,0.9375,0.787879,0.909091,1,0.83871,0.909091,0.967742,0.848485,0.909091,0.787879,0.866667,0.733333,0.787879,0.827586,0.758621,0.823529,0.533333,0.967742,0.9375,0.705882,0.8,0.827586,0.933333,0.75,0.9375,0.909091,0.628571,0.482759,1,0.909091,0.8,0.75,0.875,0.705882,0.9375,0.764706,0.967742,0.903226,0.666667,0.967742,0.9375,0.857143,0.83871,0.866667,0.642857,0.83871,0.903226,1,0.83871,0.903226,0.967742,0.83871,0.903226,0.896552,0.903226,0.967742,0.903226,0.727273,0.882353,0.625,0.9375]
kappa
0.8238636363636365
kb_relative_information_score
954.1779227924285
mean_absolute_error
0.01616910191304953
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
0.8367688750373972 [0.866667,1,1,0.583333,0.933333,0.578947,1,1,0.909091,1,0.9375,0.928571,1,0.8125,0.517241,0.9375,1,0.5625,0.4,0.315789,0.8125,1,0.75,1,0.9375,0.428571,0.470588,0.736842,0.933333,1,1,1,0.941176,0.555556,0.875,0.875,0.533333,0.466667,0.933333,0.9375,0.764706,0.882353,1,0.866667,0.882353,1,0.823529,0.882353,0.764706,0.928571,0.785714,0.764706,0.923077,0.846154,0.777778,0.571429,1,0.9375,0.666667,0.736842,0.923077,1,0.75,0.9375,0.882353,0.578947,0.538462,1,0.882353,0.736842,0.75,0.875,0.666667,0.9375,0.722222,1,0.933333,0.647059,1,0.9375,0.789474,0.866667,0.928571,0.75,0.866667,0.933333,1,0.866667,0.933333,1,0.866667,0.933333,1,0.933333,1,0.933333,0.705882,0.833333,0.625,0.9375]
predictive_accuracy
0.825625
prior_entropy
6.6438561897747395
recall
0.825625 [0.8125,0.9375,0.875,0.875,0.875,0.6875,1,0.9375,0.625,0.875,0.9375,0.8125,0.875,0.8125,0.9375,0.9375,1,0.5625,0.5,0.375,0.8125,0.875,0.9375,0.9375,0.9375,0.375,0.5,0.875,0.875,0.9375,0.9375,0.9375,1,0.625,0.875,0.875,0.5,0.4375,0.875,0.9375,0.8125,0.9375,1,0.8125,0.9375,0.9375,0.875,0.9375,0.8125,0.8125,0.6875,0.8125,0.75,0.6875,0.875,0.5,0.9375,0.9375,0.75,0.875,0.75,0.875,0.75,0.9375,0.9375,0.6875,0.4375,1,0.9375,0.875,0.75,0.875,0.75,0.9375,0.8125,0.9375,0.875,0.6875,0.9375,0.9375,0.9375,0.8125,0.8125,0.5625,0.8125,0.875,1,0.8125,0.875,0.9375,0.8125,0.875,0.8125,0.875,0.9375,0.875,0.75,0.9375,0.625,0.9375]
relative_absolute_error
0.8166213087398738
root_mean_prior_squared_error
0.09949874371066209
root_mean_squared_error
0.08275325568367717
root_relative_squared_error
0.831701512979098
total_cost
0
area_under_roc_curve
0.9964433564206671 [0.974843,1,1,1,0.996835,0.993711,1,1,1,1,1,1,1,1,1,0.987421,1,0.984177,0.984177,1,1,1,1,1,0.993711,0.987342,0.996835,1,1,1,1,1,1,0.993671,0.996835,0.993711,1,1,1,1,1,1,1,1,1,1,1,1,1,0.993671,1,1,1,1,0.993711,0.993711,1,1,1,1,1,0.993711,0.996835,1,1,1,0.971519,1,1,0.993711,1,1,1,1,0.993711,1,1,0.936709,1,1,1,1,1,1,1,1,1,1,0.996835,1,0.996835,1,1,0.996835,1,0.990506,1,0.993671,0.946203,1]
area_under_roc_curve
0.9945854231351007 [1,1,1,1,1,1,1,1,1,1,1,0.996835,1,0.778481,1,1,1,0.974684,0.993671,0.974843,1,1,1,1,1,0.993671,0.971519,1,1,1,1,1,1,1,1,0.993711,0.993711,0.993711,1,1,1,1,1,1,1,1,1,1,0.996835,1,1,1,1,1,1,0.974843,1,1,1,0.993671,1,1,1,1,1,1,0.990506,1,1,1,0.996835,1,1,1,1,1,1,1,1,0.990506,0.955696,0.996835,0.987421,0.993711,1,1,1,1,1,1,1,1,1,0.996835,1,1,0.987421,1,1,0.981132]
area_under_roc_curve
0.9969158008916488 [1,1,1,1,1,0.981013,1,1,0.996835,1,1,1,1,1,1,1,1,0.977848,1,0.936709,1,1,0.990506,1,1,0.96519,1,1,1,1,1,1,1,0.993671,0.993711,1,1,0.993711,1,1,0.993671,1,1,1,1,1,0.984177,1,0.993671,1,1,1,1,1,1,1,1,1,0.987421,0.971519,1,1,1,1,1,1,1,1,1,0.996835,1,0.996835,0.993711,1,1,1,1,0.993671,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.996835,1,1]
area_under_roc_curve
0.9975924986067988 [1,1,1,1,1,1,1,1,0.993671,1,1,1,1,1,1,1,1,0.990506,0.968553,0.984177,1,1,1,1,1,1,0.996835,1,1,1,1,1,1,0.990506,1,0.993711,1,0.962264,1,1,1,0.993711,1,1,1,1,1,1,1,1,1,1,1,0.981013,1,0.990506,1,1,1,1,1,1,1,1,1,0.996835,0.990506,1,1,0.990506,0.990506,1,0.993711,1,1,1,1,0.996835,1,1,1,1,1,0.996835,1,1,1,1,1,1,1,1,1,1,1,1,0.993671,0.993671,0.949686,1]
area_under_roc_curve
0.9965657590956132 [1,1,1,1,1,0.996835,1,0.996835,1,1,0.993671,1,1,0.90566,1,1,1,0.990506,0.987421,0.984177,1,1,1,1,1,1,1,1,1,1,1,0.993711,1,0.981013,1,1,1,0.987342,1,1,1,1,1,1,0.993711,1,1,1,1,1,0.981132,0.981132,1,1,0.977848,0.984177,1,0.996835,1,1,1,1,0.993711,1,1,1,1,1,0.996835,0.993671,1,1,1,0.993711,0.955696,1,1,1,1,1,1,1,0.996835,0.993671,1,1,1,1,1,1,1,1,1,1,0.993671,1,0.996835,1,0.987421,1]
area_under_roc_curve
0.9975089065361036 [0.968354,1,1,1,1,0.990506,1,1,1,1,1,1,0.987421,1,1,1,1,0.996835,1,0.984177,1,1,0.996835,1,1,0.996835,0.984177,1,1,1,1,1,1,0.984177,1,1,1,0.990506,1,1,0.993671,1,1,1,1,1,1,1,1,0.996835,1,1,0.987342,1,1,0.996835,1,1,1,0.993711,0.996835,1,0.993711,1,1,0.977848,1,1,0.996835,1,1,1,1,1,0.996835,1,1,1,1,1,1,0.993671,0.993671,0.993671,1,1,1,1,1,1,1,0.996835,1,1,1,1,1,1,1,1]
area_under_roc_curve
0.9963279197516121 [1,1,1,1,1,1,1,1,0.993711,1,1,1,1,1,1,1,1,1,0.993671,0.990506,0.981013,1,1,1,1,0.899371,0.968553,1,1,1,0.996835,1,1,1,1,1,0.968354,0.984177,1,0.993711,0.996835,0.996835,1,1,1,0.996835,1,0.993671,1,1,1,1,1,1,1,1,1,1,0.993671,1,1,1,0.993711,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.990506,1,1,1,1,1,1,0.987421,0.993711,1,1,1,0.996835,1,1,1,1,1,0.911392,1]
area_under_roc_curve
0.9975131358968234 [0.977848,1,1,1,1,0.996835,1,1,0.993711,1,1,1,1,1,1,1,1,0.993711,0.977848,0.984177,0.990506,1,1,1,1,1,1,1,0.993711,0.996835,1,1,1,1,1,1,0.987342,0.993671,1,1,1,1,1,1,1,1,1,1,1,1,0.987421,0.996835,1,1,1,0.990506,1,1,0.993671,0.981132,1,1,1,1,1,0.974843,0.968553,1,1,0.993671,1,1,1,1,0.996835,1,1,0.974843,1,1,1,1,0.996835,1,1,1,1,1,1,1,1,0.993671,1,1,1,1,1,1,1,1]
area_under_roc_curve
0.9977892882732267 [1,1,1,1,1,1,1,1,0.993671,1,1,1,1,1,1,1,1,0.987421,1,0.962264,1,1,1,1,1,0.981132,0.993711,1,1,1,1,1,1,0.993711,0.996835,1,1,0.962025,1,1,1,1,1,0.993671,1,1,1,1,0.993711,1,0.996835,1,1,0.981013,1,0.987421,1,1,0.996835,1,1,1,1,1,1,1,0.981013,1,0.996835,1,1,0.987421,0.981013,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1]
area_under_roc_curve
0.9978290940211766 [1,1,1,1,1,0.993711,1,1,1,0.993711,1,1,1,0.977848,1,1,1,0.993711,0.987342,0.987421,1,1,1,1,1,1,1,1,1,1,1,1,1,0.974843,0.996835,1,0.996835,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.993671,1,0.993711,1,1,0.984177,1,1,1,0.984177,1,0.987421,0.993711,0.990506,1,0.987342,1,0.987421,1,0.993671,1,1,1,1,1,1,1,1,0.981132,1,0.993711,1,1,1,1,1,1,1,0.996835,1,0.996835,1,1,1,1,1,1]
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
0.8041770302814956
kappa
0.8294377763739735
kappa
0.8546947800679143
kappa
0.835761380236093
kappa
0.8104564839677776
kappa
0.8104714522624971
kappa
0.8167673656359831
kappa
0.8230927183699257
kappa
0.8357289527720739
kappa
0.8168324648665719
kb_relative_information_score
94.47900583021577
kb_relative_information_score
95.0613757559406
kb_relative_information_score
95.70330250209004
kb_relative_information_score
96.08845506420317
kb_relative_information_score
95.15783892622076
kb_relative_information_score
93.85711705043533
kb_relative_information_score
97.321329166946
kb_relative_information_score
96.62861049216691
kb_relative_information_score
95.90636192577155
kb_relative_information_score
93.97452607843863
mean_absolute_error
0.01623070936577581
mean_absolute_error
0.016148748896868435
mean_absolute_error
0.016086926399699622
mean_absolute_error
0.016160971071113604
mean_absolute_error
0.016110633101369183
mean_absolute_error
0.016338429775721176
mean_absolute_error
0.015883783306600494
mean_absolute_error
0.01616392753135485
mean_absolute_error
0.01617252150439363
mean_absolute_error
0.01639436817759826
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
0.80625
predictive_accuracy
0.83125
predictive_accuracy
0.85625
predictive_accuracy
0.8375
predictive_accuracy
0.8125
predictive_accuracy
0.8125
predictive_accuracy
0.81875
predictive_accuracy
0.825
predictive_accuracy
0.8375
predictive_accuracy
0.81875
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
0.80625 [1,0.5,1,1,0.5,1,1,1,0.5,1,0.5,1,1,1,1,0,1,0.5,0,0,0,1,1,1,1,0.5,0.5,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,0,1,1,0,1,1,1,0.5,1,1,1,0,1,1,0,0.5,1,1,1,1,1,0,0,1,1,1,1,1,1,1,0.5,1,1,0.5,1,1,1,1,1,1,0.5,0,1,0.5,1]
recall
0.83125 [1,1,1,1,1,1,1,1,1,1,1,0.5,1,0.5,0.5,1,1,0.5,0.5,1,1,1,1,1,1,0.5,0,1,1,1,1,1,1,1,0.5,0,0,0,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,0.5,1,0,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,0.5,0.5,0.5,1,0,0.5,1,1,1,0.5,1,0.5,1,0.5,1,1,1,0,1,0.5,0]
recall
0.85625 [1,1,0.5,1,1,0.5,1,1,0.5,1,1,0.5,1,1,1,1,1,0.5,1,0.5,1,0,0.5,1,1,0.5,1,1,1,1,1,1,1,0.5,1,1,1,0,1,1,0.5,1,1,1,1,1,0.5,1,0.5,1,1,1,1,1,1,1,1,1,1,0,0,1,0.5,0,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,0.5,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1]
recall
0.8375 [0.5,1,0.5,1,0.5,0.5,1,1,0.5,1,1,0.5,1,1,1,1,1,0.5,0,0.5,1,1,1,1,1,0,1,1,1,1,1,1,1,0.5,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,0.5,1,1,1,1,1,1,1,1,1,0.5,0.5,1,1,1,0,1,0,1,1,1,1,0.5,1,1,1,1,0.5,0.5,1,1,1,1,1,1,0.5,1,1,1,1,1,0,1,1,1]
recall
0.8125 [1,1,1,1,1,0.5,1,0.5,1,1,1,1,0,0,1,1,1,0,1,0.5,1,1,1,1,1,1,0,1,1,1,1,0,1,0.5,1,1,0.5,0.5,1,1,1,1,1,0,0,1,1,1,1,1,0,0,0.5,1,0.5,0,1,1,1,1,1,1,1,1,0.5,1,0,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,0.5,0.5,1,1,1,1,1,1,1,0.5,1,0,0.5,1,1,1,0,1]
recall
0.8125 [0.5,1,1,0.5,1,0.5,1,1,1,0.5,1,1,0,1,1,1,1,1,1,0.5,0.5,0.5,1,1,1,0.5,0.5,0,1,1,1,1,1,0.5,1,0.5,0,0.5,1,1,1,1,1,1,1,1,1,1,0.5,0.5,1,1,0.5,1,1,1,1,1,0.5,1,0.5,0.5,1,1,1,0,1,1,1,1,0.5,1,1,1,0.5,1,1,0.5,1,1,1,0.5,1,1,0,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1]
recall
0.81875 [1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,0,0,0.5,1,1,0.5,1,1,1,1,1,0,0.5,1,0,1,0.5,1,1,1,0.5,0.5,1,1,1,0,1,1,0,1,0.5,1,1,0,1,1,0.5,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,0,1,1,0.5,1,1,0,1]
recall
0.825 [0.5,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0.5,1,1,1,0.5,0,1,1,0,0.5,1,1,1,1,1,1,0,0.5,1,1,0.5,1,1,1,1,1,1,0.5,1,0,0,0.5,0.5,1,1,0.5,0.5,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,0.5,0.5,0.5,0.5,1,0,1,1,1,1,1,1,1,1,1,1,1,1]
recall
0.8375 [1,1,1,0.5,1,1,1,1,0.5,1,1,1,1,1,1,1,1,0,1,0,1,1,1,0.5,1,0,1,1,1,1,1,1,1,1,1,1,1,0,0.5,1,0,1,1,0.5,1,1,1,1,0,1,0.5,1,0.5,0.5,0.5,0,1,0,1,1,0.5,1,1,1,1,1,0.5,1,1,1,1,0,0.5,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0.5,0.5,1,1,1,1,1,1,0.5,1]
recall
0.81875 [1,1,1,1,1,1,1,1,0.5,0,1,1,1,0.5,1,1,1,1,0,1,1,1,1,1,1,0,0,1,0.5,1,1,1,1,1,0.5,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,0.5,0.5,1,0.5,1,1,1,1,1,1,0.5,1,0,1,1,1,0,1,0.5,1,1,0,0,0.5,0.5,0.5,1,1,1,1,1,0,1,0,1,1,1,0.5,1,1,1,1,1,0.5,1,1,1,1,1,1]
relative_absolute_error
0.819732796251302
relative_absolute_error
0.8155933786297176
relative_absolute_error
0.8124710302878583
relative_absolute_error
0.8162106601572513
relative_absolute_error
0.8136683384529877
relative_absolute_error
0.8251732209960178
relative_absolute_error
0.8022112781111348
relative_absolute_error
0.8163599763310517
relative_absolute_error
0.8167940153734142
relative_absolute_error
0.8279983928079915
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
0.08310490539091595
root_mean_squared_error
0.08266345627708173
root_mean_squared_error
0.08238787904055041
root_mean_squared_error
0.08274101464761259
root_mean_squared_error
0.082439125068401
root_mean_squared_error
0.08366711731522974
root_mean_squared_error
0.08144748170535443
root_mean_squared_error
0.0826400145899226
root_mean_squared_error
0.08271421950732563
root_mean_squared_error
0.08370424471256491
root_relative_squared_error
0.8352357255140963
root_relative_squared_error
0.8307989949849357
root_relative_squared_error
0.8280293395475496
root_relative_squared_error
0.8315784859376697
root_relative_squared_error
0.8285443815062662
root_relative_squared_error
0.8408861679553463
root_relative_squared_error
0.81857799071514
root_relative_squared_error
0.8305633971644517
root_relative_squared_error
0.831309184645134
root_relative_squared_error
0.8412593123383865
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
2917.3655120000603
usercpu_time_millis
2719.486181000093
usercpu_time_millis
2775.2773929998966
usercpu_time_millis
2732.8544560002683
usercpu_time_millis
2723.7836209999386
usercpu_time_millis
2871.991871999853
usercpu_time_millis
2743.1068159999086
usercpu_time_millis
2744.7597110001425
usercpu_time_millis
2733.072975000141
usercpu_time_millis
2788.3124799998313
usercpu_time_millis_testing
148.25410100002046
usercpu_time_millis_testing
148.0700940001043
usercpu_time_millis_testing
148.21897799993167
usercpu_time_millis_testing
148.12539100012145
usercpu_time_millis_testing
147.59436099984669
usercpu_time_millis_testing
146.93276999992122
usercpu_time_millis_testing
147.36382299997786
usercpu_time_millis_testing
147.9809770000884
usercpu_time_millis_testing
147.59312800015323
usercpu_time_millis_testing
156.78921499988974
usercpu_time_millis_training
2769.11141100004
usercpu_time_millis_training
2571.4160869999887
usercpu_time_millis_training
2627.058414999965
usercpu_time_millis_training
2584.729065000147
usercpu_time_millis_training
2576.189260000092
usercpu_time_millis_training
2725.059101999932
usercpu_time_millis_training
2595.7429929999307
usercpu_time_millis_training
2596.778734000054
usercpu_time_millis_training
2585.479846999988
usercpu_time_millis_training
2631.5232649999416