8802955
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)
6778036
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
3019.783311634322
7708
cache_size
200
7708
class_weight
null
7708
coef0
-0.1652226628397302
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decision_function_shape
null
7708
degree
2
7708
gamma
0.052618247267007
7708
kernel
"poly"
7708
max_iter
-1
7708
probability
true
7708
random_state
13487
7708
shrinking
false
7708
tol
0.05794386554168139
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
18521915
description
https://api.openml.org/data/download/18521915/description.xml
-1
18521916
predictions
https://api.openml.org/data/download/18521916/predictions.arff
area_under_roc_curve
0.9964599116161612 [0.988479,1,1,0.999961,0.998343,0.994989,0.999803,0.999645,0.99779,0.999961,0.998816,0.999566,0.999645,0.973761,0.999408,0.999566,1,0.990964,0.983862,0.974708,0.998264,0.999527,0.996607,0.999329,0.998698,0.976957,0.992227,0.99929,0.99854,1,0.999724,1,1,0.990136,0.99925,0.998895,0.993213,0.983941,0.999684,0.999842,0.999014,0.998658,1,0.998777,0.996883,0.999921,0.99925,0.999329,0.997435,0.996725,0.9942,0.999014,0.998027,0.991872,0.996883,0.993963,1,0.999448,0.992858,0.996725,0.998698,0.999448,0.997633,0.99925,0.999369,0.994239,0.986111,0.999921,0.998264,0.993608,0.996883,0.999408,0.996291,0.998343,0.989386,0.999487,0.999448,0.990885,0.999961,1,0.995818,0.997593,0.998106,0.995502,0.999369,0.999921,0.999961,0.999211,0.999329,1,0.99925,0.999605,0.998816,0.997711,0.996646,0.997711,0.998343,0.99854,0.967764,0.99779]
average_cost
0
f_measure
0.8308628869769268 [0.705882,0.967742,0.967742,0.967742,0.933333,0.827586,1,0.903226,0.875,0.933333,0.882353,0.875,0.9375,0.714286,0.967742,0.933333,1,0.645161,0.424242,0.266667,0.8,0.967742,0.764706,1,0.909091,0.388889,0.516129,0.848485,0.933333,0.967742,0.967742,0.967742,0.967742,0.516129,0.848485,0.875,0.5625,0.516129,0.941176,0.896552,0.777778,0.909091,1,0.848485,0.9375,0.941176,0.857143,0.909091,0.764706,0.83871,0.787879,0.785714,0.8125,0.705882,0.774194,0.545455,1,0.9375,0.702703,0.742857,0.896552,0.848485,0.774194,0.9375,0.909091,0.615385,0.529412,0.969697,0.83871,0.705882,0.823529,0.933333,0.709677,0.967742,0.756757,0.9375,0.903226,0.685714,1,1,0.774194,0.875,0.866667,0.533333,0.875,0.967742,0.967742,0.903226,0.933333,0.967742,0.8125,0.866667,0.875,0.875,0.9375,0.8,0.8,0.848485,0.5,0.903226]
kappa
0.827020202020202
kb_relative_information_score
991.0624149126379
mean_absolute_error
0.015935068880324615
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
0.8382305024192392 [0.666667,1,1,1,1,0.923077,1,0.933333,0.875,1,0.833333,0.875,0.9375,0.833333,1,1,1,0.666667,0.411765,0.285714,0.857143,1,0.722222,1,0.882353,0.35,0.533333,0.823529,1,1,1,1,1,0.533333,0.823529,0.875,0.5625,0.533333,0.888889,1,0.7,0.882353,1,0.823529,0.9375,0.888889,1,0.882353,0.722222,0.866667,0.764706,0.916667,0.8125,0.666667,0.8,0.529412,1,0.9375,0.619048,0.684211,1,0.823529,0.8,0.9375,0.882353,0.521739,0.5,0.941176,0.866667,0.666667,0.777778,1,0.733333,1,0.666667,0.9375,0.933333,0.631579,1,1,0.8,0.875,0.928571,0.571429,0.875,1,1,0.933333,1,1,0.8125,0.928571,0.875,0.875,0.9375,0.736842,0.736842,0.823529,0.5,0.933333]
predictive_accuracy
0.82875
prior_entropy
6.6438561897747395
recall
0.82875 [0.75,0.9375,0.9375,0.9375,0.875,0.75,1,0.875,0.875,0.875,0.9375,0.875,0.9375,0.625,0.9375,0.875,1,0.625,0.4375,0.25,0.75,0.9375,0.8125,1,0.9375,0.4375,0.5,0.875,0.875,0.9375,0.9375,0.9375,0.9375,0.5,0.875,0.875,0.5625,0.5,1,0.8125,0.875,0.9375,1,0.875,0.9375,1,0.75,0.9375,0.8125,0.8125,0.8125,0.6875,0.8125,0.75,0.75,0.5625,1,0.9375,0.8125,0.8125,0.8125,0.875,0.75,0.9375,0.9375,0.75,0.5625,1,0.8125,0.75,0.875,0.875,0.6875,0.9375,0.875,0.9375,0.875,0.75,1,1,0.75,0.875,0.8125,0.5,0.875,0.9375,0.9375,0.875,0.875,0.9375,0.8125,0.8125,0.875,0.875,0.9375,0.875,0.875,0.875,0.5,0.875]
relative_absolute_error
0.8048014586022518
root_mean_prior_squared_error
0.09949874371066209
root_mean_squared_error
0.08202253718892395
root_relative_squared_error
0.8243575157837353
total_cost
0
area_under_roc_curve
0.9963657352121646 [1,1,1,1,1,1,1,1,1,1,1,0.996835,1,0.987342,1,0.981132,1,0.990506,0.984177,0.987421,1,1,1,1,1,0.996835,0.993671,1,1,1,1,1,1,0.990506,1,0.993711,1,0.993711,1,1,0.993711,0.993711,1,1,1,1,1,1,1,0.981013,1,1,0.993711,1,1,1,1,1,1,1,1,1,1,1,1,1,0.971519,1,1,0.962264,0.996835,1,1,1,1,1,1,0.955696,1,1,1,1,0.993711,1,1,1,1,1,1,1,1,1,1,1,1,0.987342,0.981132,0.996835,0.943038,1]
area_under_roc_curve
0.9964040482445664 [1,1,1,1,1,1,1,1,1,1,1,1,1,0.892405,1,1,1,0.984177,0.996835,0.987421,1,0.993711,0.993711,1,1,0.977848,0.971519,1,1,1,1,1,1,0.996835,1,1,0.993711,0.993711,1,1,1,1,1,1,1,1,1,1,0.996835,1,1,1,1,1,1,0.993711,1,1,1,0.993671,1,1,1,1,1,0.996835,1,1,0.987421,1,0.996835,1,1,1,1,1,1,0.993671,1,1,0.981013,0.996835,1,0.987421,0.996835,1,1,1,1,1,1,1,1,0.990506,1,1,1,0.996835,1,0.974843]
area_under_roc_curve
0.9970745263115992 [1,1,1,1,1,1,1,1,0.996835,1,1,1,1,1,1,1,1,1,1,0.936709,1,1,0.993671,1,1,0.939873,1,1,1,1,1,1,1,0.984177,1,1,1,1,1,1,0.993671,0.981132,1,1,1,1,1,1,0.996835,1,1,1,1,1,1,1,1,1,0.981132,0.981013,1,1,1,0.993711,1,0.993671,1,1,1,0.987342,1,0.996835,1,1,1,1,1,0.996835,1,1,1,1,1,0.996835,1,1,1,1,1,1,1,1,1,1,0.993671,1,1,1,1,1]
area_under_roc_curve
0.9972364859485708 [1,1,1,1,1,0.993671,1,1,0.996835,1,1,1,1,1,1,1,1,0.987342,0.943396,0.974684,1,1,0.996835,1,0.993711,1,1,1,1,1,1,1,1,0.987342,1,1,1,0.962264,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.984177,1,0.984177,1,1,0.993711,1,1,1,1,1,1,0.996835,0.996835,1,1,0.977848,0.984177,1,0.981132,1,0.993711,1,1,0.996835,1,1,1,1,0.993671,0.996835,1,1,1,1,1,1,1,1,0.993711,1,1,1,1,1,1,1]
area_under_roc_curve
0.9962498009712603 [1,1,1,1,1,0.996835,1,1,1,1,0.990506,1,1,0.918239,1,1,1,0.990506,0.987421,0.990506,1,1,1,1,1,0.993671,0.993671,1,1,1,1,1,1,0.977848,1,1,0.993671,0.987342,1,1,1,1,1,1,1,1,1,1,1,1,1,0.987421,1,1,0.990506,0.993671,1,0.996835,1,1,1,1,0.993711,1,1,1,1,1,0.996835,1,1,1,1,1,0.949367,1,0.993671,1,1,1,1,1,1,0.990506,0.993711,1,1,1,1,1,1,1,1,1,0.971519,0.993711,1,1,0.930818,1]
area_under_roc_curve
0.9964013115993946 [0.924051,1,1,1,1,0.984177,1,1,1,1,1,1,1,1,1,1,1,1,1,0.955696,1,1,1,1,0.993671,0.987342,0.987342,1,1,1,1,1,1,0.993671,1,0.993671,0.996835,0.981013,1,1,0.996835,1,1,0.993711,1,1,1,1,0.990506,0.996835,1,1,1,1,1,0.993671,1,1,0.993671,1,0.996835,1,0.993711,1,1,0.981013,1,1,0.996835,1,1,1,1,1,0.993671,1,1,1,1,1,0.993711,0.993671,1,0.993671,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.993711,1]
area_under_roc_curve
0.9954984674787036 [1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.993711,0.996835,0.977848,0.996835,1,0.990506,1,1,0.886792,0.974843,0.993671,1,1,0.996835,1,1,1,1,1,0.974684,0.993671,1,1,1,1,1,1,0.968553,1,1,1,1,1,1,1,1,1,1,1,1,1,0.987342,1,1,1,1,0.996835,1,0.981132,1,1,1,1,1,1,0.996835,1,1,1,1,0.993711,1,1,0.974684,1,1,1,1,1,1,1,1,1,1,1,0.993671,1,1,1,1,1,0.870253,1]
area_under_roc_curve
0.9971215468513653 [1,1,1,1,1,1,1,1,1,1,1,1,0.996835,1,1,1,1,0.993711,0.990506,1,0.996835,1,1,1,0.993671,0.993711,1,1,0.974843,1,1,1,1,1,1,1,0.981013,0.987342,1,1,1,1,1,1,1,1,1,0.993671,1,0.987421,0.949686,1,0.996835,1,1,0.987342,1,1,0.987342,1,1,1,1,1,1,0.974843,0.924528,1,1,0.996835,1,1,1,1,1,1,1,0.968553,1,1,0.993671,1,0.993671,1,1,1,1,1,1,1,1,1,1,1,1,0.993671,1,1,1,0.996835]
area_under_roc_curve
0.997156874452671 [1,1,1,1,1,1,1,1,0.993671,1,1,1,1,1,1,1,1,0.987421,0.990506,0.974843,0.996835,1,0.981132,0.993671,1,0.987421,0.993711,1,1,1,1,1,1,0.993711,1,1,1,0.952532,1,1,1,1,1,0.996835,1,1,1,1,0.993711,1,0.990506,1,1,0.968354,0.990506,0.993711,1,1,0.996835,1,0.996835,1,1,1,1,1,0.987342,1,1,1,1,0.993711,0.984177,1,1,1,1,0.993711,1,1,1,0.993711,1,0.987421,1,1,1,1,1,1,1,1,1,1,1,0.996835,1,1,1,1]
area_under_roc_curve
0.9977487361675028 [0.993711,1,1,1,1,1,1,1,1,1,1,1,1,0.993671,1,1,1,1,0.974684,0.987421,0.996835,1,1,1,1,1,1,0.996835,1,1,1,1,1,0.993711,1,0.993671,0.996835,1,1,1,1,1,1,1,0.996835,1,1,1,0.993711,1,1,1,1,0.996835,1,1,1,1,0.981013,1,1,1,0.993671,1,0.993711,0.993711,0.981013,1,1,1,1,1,0.990506,0.990506,1,0.990506,1,1,1,1,1,0.968553,1,0.993711,1,1,1,0.996835,1,1,0.996835,1,1,0.996835,1,1,0.993711,1,1,1]
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
0.8041924914136829
kappa
0.8104415133085854
kappa
0.8799747315224258
kappa
0.8294445102451735
kappa
0.8294040990403981
kappa
0.8167963043392427
kappa
0.8041615667074664
kappa
0.8230647709320694
kappa
0.8546890424481737
kappa
0.8168469250809189
kb_relative_information_score
99.50202625488626
kb_relative_information_score
97.64557858315702
kb_relative_information_score
98.95037302853531
kb_relative_information_score
98.13553921848037
kb_relative_information_score
98.7029710567152
kb_relative_information_score
98.35833134678577
kb_relative_information_score
102.08301426396366
kb_relative_information_score
98.76309865605027
kb_relative_information_score
99.70598000645357
kb_relative_information_score
99.21550249761218
mean_absolute_error
0.015811771294932064
mean_absolute_error
0.016133921059792847
mean_absolute_error
0.01604050487404044
mean_absolute_error
0.016108232685283677
mean_absolute_error
0.016074738434251237
mean_absolute_error
0.015976428230886113
mean_absolute_error
0.015522369697436565
mean_absolute_error
0.016001665541914935
mean_absolute_error
0.015828814180214847
mean_absolute_error
0.015852242804493242
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
0.8125
predictive_accuracy
0.88125
predictive_accuracy
0.83125
predictive_accuracy
0.83125
predictive_accuracy
0.81875
predictive_accuracy
0.80625
predictive_accuracy
0.825
predictive_accuracy
0.85625
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 [1,0.5,1,1,0.5,1,1,1,1,1,0.5,1,1,0,1,0,1,0.5,0,1,0,1,1,1,1,0.5,0.5,1,1,1,1,1,0.5,0,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,0.5,1,0.5,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0,1,1,0,1,1,1,1,1,1,0.5,0,1,1,1,1,1,1,1,1,0.5,1,0.5,1,1,1,1,1,1,0.5,0,1,0,1]
recall
0.8125 [1,1,1,0,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0.5,0.5,0,1,1,1,1,1,0.5,0,1,1,1,1,1,1,1,0.5,0,0,0,1,1,1,1,1,0.5,1,1,1,1,0.5,1,1,0.5,1,0.5,1,0,1,1,1,0.5,0,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0.5,1,1,1,0,1,1,0,0.5,1,1,1,0.5,1,0.5,1,0.5,1,1,1,1,1,0.5,0]
recall
0.88125 [1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,0.5,1,0,1,1,0.5,1,1,0.5,1,1,1,1,1,1,1,0.5,1,1,1,1,1,0.5,0,0,1,1,1,1,0.5,1,0.5,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1]
recall
0.83125 [0,1,1,1,0.5,0.5,1,1,0.5,0.5,1,0.5,1,0.5,1,1,1,0.5,0,0.5,1,1,1,1,1,0.5,1,1,1,1,1,1,1,0.5,1,1,1,0,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,0.5,1,0.5,1,1,1,1,1,1,1,1,0.5,0.5,0.5,1,1,0.5,0,1,0,1,1,1,1,1,1,1,1,1,0.5,0.5,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1]
recall
0.83125 [1,1,1,1,1,0.5,1,1,1,1,1,1,1,0,1,1,1,0.5,1,0.5,0.5,1,1,1,1,1,0.5,1,1,1,1,1,1,0,1,1,0.5,0,1,1,1,1,1,0,1,1,1,1,1,1,0,0,0.5,1,0.5,0,1,1,1,1,1,1,0,1,1,1,1,1,0.5,0.5,1,1,1,1,0.5,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,0.5,1,0,0.5,1,1,1,0,1]
recall
0.81875 [0.5,1,0.5,1,1,0.5,1,0.5,1,0.5,1,1,0,1,1,1,1,1,1,0,0.5,0.5,1,1,1,0.5,0.5,0,1,1,1,1,1,0.5,1,0.5,0.5,1,1,1,1,1,1,1,1,1,1,1,0.5,0.5,1,1,0.5,1,1,1,1,1,0.5,1,0.5,0.5,1,1,1,0.5,1,1,0.5,1,1,1,1,1,0.5,1,1,0.5,1,1,1,0.5,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1]
recall
0.80625 [1,1,1,1,1,0.5,1,0.5,1,1,1,1,1,1,1,0.5,1,1,0,0,1,1,0.5,1,1,0,0,0.5,1,1,0.5,0,1,1,1,1,0,0.5,1,1,1,1,1,1,0,1,0,1,1,1,1,1,1,1,0.5,0.5,1,1,0,1,1,0.5,1,0.5,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,0,1,1,1,1,0.5,1,1,1,1,1,0,1]
recall
0.825 [0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,0,0.5,1,1,1,0.5,0,1,1,0,0.5,1,1,1,1,1,1,0.5,0.5,1,1,1,1,1,1,1,1,1,0.5,1,0,0,0.5,0.5,1,1,0.5,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,0,1,1,0.5,1,0.5,0.5,0.5,0.5,1,1,1,1,0,0.5,1,1,1,1,1,1,1,0.5]
recall
0.85625 [1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,0,0.5,0,1,1,0,1,1,0,0,1,1,1,1,1,1,1,1,1,1,0,1,0,1,1,1,1,1,1,1,1,1,1,0.5,1,1,0.5,0.5,0,1,0,1,1,1,1,1,1,1,1,0.5,1,1,1,1,0,0.5,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0.5,0.5,1,1,1,0.5,1,1,0.5,1]
recall
0.81875 [1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,0,1,1,1,1,1,1,0,0,1,0.5,1,1,1,1,0,0.5,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,0.5,0.5,1,1,1,1,1,0.5,1,0,1,1,1,0,1,0.5,1,1,0,0,0.5,1,0.5,1,1,1,1,1,0,1,0,1,1,1,0.5,1,1,1,1,1,0.5,1,1,1,0,1,1]
relative_absolute_error
0.7985743078248504
relative_absolute_error
0.8148444979693343
relative_absolute_error
0.8101265087899199
relative_absolute_error
0.8135471053173561
relative_absolute_error
0.8118554764773339
relative_absolute_error
0.8068903146912164
relative_absolute_error
0.7839580655270979
relative_absolute_error
0.8081649263593388
relative_absolute_error
0.799435059606809
relative_absolute_error
0.8006183234592532
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
0.0815739624779738
root_mean_squared_error
0.08278870001997765
root_mean_squared_error
0.08224210754067088
root_mean_squared_error
0.08273175235331741
root_mean_squared_error
0.0824743392641087
root_mean_squared_error
0.08237585615305026
root_mean_squared_error
0.08019371289967235
root_mean_squared_error
0.08214783044696346
root_mean_squared_error
0.08166994741677569
root_mean_squared_error
0.08199574685744497
root_relative_squared_error
0.8198491703089966
root_relative_squared_error
0.8320577419622858
root_relative_squared_error
0.8265642808498898
root_relative_squared_error
0.8314853963774425
root_relative_squared_error
0.8288982974894681
root_relative_squared_error
0.827908504981687
root_relative_squared_error
0.8059771401021115
root_relative_squared_error
0.8256167604070028
root_relative_squared_error
0.8208138552409093
root_relative_squared_error
0.8240882628215386
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
1352.8822900000002
usercpu_time_millis
1184.9075080000002
usercpu_time_millis
1220.9892
usercpu_time_millis
1187.0360069999997
usercpu_time_millis
1184.2086080000006
usercpu_time_millis
1187.002196
usercpu_time_millis
1179.4310950000017
usercpu_time_millis
1170.707032000001
usercpu_time_millis
1187.738492000001
usercpu_time_millis
1166.5155980000018
usercpu_time_millis_testing
139.0018660000001
usercpu_time_millis_testing
137.9063700000005
usercpu_time_millis_testing
148.20443699999953
usercpu_time_millis_testing
142.80118199999947
usercpu_time_millis_testing
139.5386710000004
usercpu_time_millis_testing
136.78012199999932
usercpu_time_millis_testing
139.89520700000037
usercpu_time_millis_testing
139.41233400000107
usercpu_time_millis_testing
141.356033000001
usercpu_time_millis_testing
138.39433600000106
usercpu_time_millis_training
1213.8804240000002
usercpu_time_millis_training
1047.0011379999996
usercpu_time_millis_training
1072.7847630000006
usercpu_time_millis_training
1044.2348250000002
usercpu_time_millis_training
1044.6699370000001
usercpu_time_millis_training
1050.2220740000005
usercpu_time_millis_training
1039.5358880000015
usercpu_time_millis_training
1031.294698
usercpu_time_millis_training
1046.3824590000002
usercpu_time_millis_training
1028.1212620000008