10408806
1
Jan van Rijn
9954
Supervised Classification
16360
sklearn.svm.classes.SVC(32)
8246572
C
59.87279268674813
16360
cache_size
200
16360
class_weight
null
16360
coef0
0.0
16360
decision_function_shape
"ovr"
16360
degree
3
16360
gamma
0.0988888211054266
16360
kernel
"rbf"
16360
max_iter
-1
16360
probability
false
16360
random_state
37692
16360
shrinking
false
16360
tol
0.00017914430736309405
16360
verbose
false
16360
openml-python
Sklearn_0.21.2.
1491
one-hundred-plants-margin
https://www.openml.org/data/download/1592283/phpCsX3fx
-1
21739400
description
https://api.openml.org/data/download/21739400/description.xml
-1
21739401
predictions
https://api.openml.org/data/download/21739401/predictions.arff
area_under_roc_curve
0.7730429292929302 [0.652778,0.650884,0.999684,1,0.842487,0.683396,0.905619,0.935606,0.68529,0.90625,0.717487,0.748106,0.622475,0.562184,1,0.717487,0.9375,0.522727,0.583965,0.557765,0.593119,0.90625,0.684659,1,0.779987,0.498106,0.589646,0.841856,0.873106,0.90625,0.936869,0.96875,0.748422,0.745896,0.650884,0.872475,0.619003,0.556187,0.90404,0.968434,0.809028,0.903725,0.967803,0.839962,0.84375,0.810606,0.873106,0.653093,0.778409,0.84154,0.74779,0.778725,0.809975,0.717487,0.746528,0.558081,0.999684,0.968434,0.684975,0.684659,0.935606,0.842803,0.903093,0.811237,0.935606,0.559343,0.555556,1,0.653725,0.683081,0.686869,0.780934,0.714646,0.810922,0.558712,0.812184,0.811237,0.621528,0.999684,0.937184,0.624369,0.874684,0.778725,0.777778,0.653725,0.874684,1,0.559975,0.905303,0.619318,0.592172,0.967172,0.686237,0.620265,0.933712,0.748422,0.616793,0.560922,0.498422,0.904672]
average_cost
0
f_measure
0.5509569922305428 [0.3125,0.263158,0.969697,1,0.709677,0.342857,0.83871,0.777778,0.413793,0.896552,0.518519,0.533333,0.285714,0.210526,1,0.518519,0.933333,0.045455,0.12,0.121212,0.285714,0.896552,0.387097,1,0.62069,0,0.1875,0.666667,0.705882,0.896552,0.875,0.967742,0.551724,0.432432,0.263158,0.666667,0.205128,0.105263,0.722222,0.9375,0.540541,0.702703,0.882353,0.564103,0.814815,0.625,0.705882,0.322581,0.529412,0.647059,0.516129,0.545455,0.588235,0.518519,0.457143,0.125,0.969697,0.9375,0.4,0.387097,0.777778,0.733333,0.666667,0.666667,0.777778,0.142857,0.1,1,0.344828,0.333333,0.5,0.692308,0.388889,0.645161,0.133333,0.740741,0.666667,0.258065,0.969697,0.903226,0.363636,0.827586,0.545455,0.5,0.344828,0.827586,1,0.153846,0.8125,0.210526,0.25,0.833333,0.461538,0.228571,0.666667,0.551724,0.173913,0.173913,0,0.764706]
kappa
0.5460858585858586
kb_relative_information_score
0.549644282786144
mean_absolute_error
0.008987499999999864
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
0.573151207206144 [0.3125,0.227273,0.941176,1,0.733333,0.315789,0.866667,0.7,0.461538,1,0.636364,0.571429,0.333333,0.666667,1,0.636364,1,0.035714,0.088235,0.117647,0.6,1,0.4,1,0.692308,0,0.1875,0.647059,0.666667,1,0.875,1,0.615385,0.380952,0.227273,0.6,0.173913,0.090909,0.65,0.9375,0.47619,0.619048,0.833333,0.478261,1,0.625,0.666667,0.333333,0.5,0.611111,0.533333,0.529412,0.555556,0.636364,0.421053,0.125,0.941176,0.9375,0.428571,0.4,0.7,0.785714,0.565217,0.714286,0.7,0.166667,0.083333,1,0.384615,0.3,0.75,0.9,0.35,0.666667,0.142857,0.909091,0.714286,0.266667,0.941176,0.933333,0.666667,0.923077,0.529412,0.45,0.384615,0.923077,1,0.2,0.8125,0.181818,0.375,0.75,0.6,0.210526,0.538462,0.615385,0.133333,0.285714,0,0.722222]
predictive_accuracy
0.550625
prior_entropy
6.643856189774611
recall
0.550625 [0.3125,0.3125,1,1,0.6875,0.375,0.8125,0.875,0.375,0.8125,0.4375,0.5,0.25,0.125,1,0.4375,0.875,0.0625,0.1875,0.125,0.1875,0.8125,0.375,1,0.5625,0,0.1875,0.6875,0.75,0.8125,0.875,0.9375,0.5,0.5,0.3125,0.75,0.25,0.125,0.8125,0.9375,0.625,0.8125,0.9375,0.6875,0.6875,0.625,0.75,0.3125,0.5625,0.6875,0.5,0.5625,0.625,0.4375,0.5,0.125,1,0.9375,0.375,0.375,0.875,0.6875,0.8125,0.625,0.875,0.125,0.125,1,0.3125,0.375,0.375,0.5625,0.4375,0.625,0.125,0.625,0.625,0.25,1,0.875,0.25,0.75,0.5625,0.5625,0.3125,0.75,1,0.125,0.8125,0.25,0.1875,0.9375,0.375,0.25,0.875,0.5,0.25,0.125,0,0.8125]
relative_absolute_error
0.4539141414141337
root_mean_prior_squared_error
0.09949874371066209
root_mean_squared_error
0.09480242612929199
root_relative_squared_error
0.9528002323825637
total_cost
0
area_under_roc_curve
0.7766101425045775 [0.493711,0.5,1,1,1,0.987421,0.496835,0.996855,0.5,1,0.75,0.75,0.5,0.5,1,0.996855,1,0.5,0.5,0.984277,0.5,1,0.990566,1,0.496855,0.5,0.75,0.996835,0.75,0.5,1,1,0.5,0.5,0.5,0.993711,0.996855,0.987421,0.993711,1,0.993711,0.993711,0.996835,0.996835,1,1,1,0.990566,0.75,0.746835,1,0.5,0.990566,0.5,0.993711,0.984277,1,1,0.5,1,0.996855,0.993711,1,0.75,1,0.5,0.5,1,0.993711,0.487421,0.75,1,0.996835,0.75,0.487421,0.75,0.5,0.5,1,1,0.5,1,1,0.996855,0.5,0.75,1,0.5,0.75,0.993711,0.5,1,0.5,0.5,1,0.5,0.984277,0.5,0.5,0.996855]
area_under_roc_curve
0.7764509195127771 [0.993711,0.5,1,1,1,0.993711,0.75,0.993711,0.5,1,0.75,0.5,0.5,0.5,1,0.996855,1,0.5,0.5,0.981132,1,0.5,0.493711,1,1,0.5,0.5,1,1,1,0.996835,1,0.746835,0.5,0.5,0.990566,0.993711,0.993711,0.996855,1,0.990566,0.993711,1,0.996835,0.75,0.75,0.996855,0.990566,0.746835,1,1,0.746835,0.993711,1,0.996855,0.490566,1,1,0.996855,0.5,0.996855,1,0.996835,0.496835,0.993711,0.5,0.5,1,0.496855,0.993711,0.746835,1,1,0.496835,0.493711,0.496835,0.5,0.743671,1,0.75,0.5,0.75,0.990566,1,0.496835,1,1,0.5,0.75,0.990566,0.5,1,0.5,0.5,0.996835,0.5,0.990566,0.5,0.5,0.996855]
area_under_roc_curve
0.7671960831144016 [0.5,0.5,1,1,0.75,1,1,0.75,0.996835,1,0.75,0.5,0.993711,0.5,1,0.5,0.75,0.5,0.490566,0.5,0.5,0.5,0.5,1,0.996855,0.5,0.496835,0.993711,0.75,1,1,1,1,0.5,0.981132,0.996855,0.974843,0.481132,0.996855,0.75,0.5,0.996855,1,0.987421,1,0.996855,0.75,0.993711,0.5,1,0.5,0.996855,1,0.5,0.987421,0.5,1,1,0.993711,0.5,0.996855,0.496855,0.75,0.493711,0.996835,0.5,0.5,1,0.993711,0.75,0.5,0.996835,0.984277,1,0.990566,0.75,0.75,0.5,1,1,0.496855,1,0.5,0.5,0.996855,1,1,0.5,0.996835,0.981132,0.75,0.996855,1,0.5,1,1,0.5,0.5,0.496855,1]
area_under_roc_curve
0.7608669691903508 [0.496835,0.5,1,1,0.75,0.496835,1,0.75,0.746835,0.75,0.75,0.5,0.996855,0.75,1,0.5,1,0.5,0.987421,0.5,0.5,1,0.746835,1,0.496855,0.5,0.5,0.993711,0.75,1,1,1,0.5,0.75,0.984277,0.993711,0.984277,0.474843,0.996855,1,1,0.990566,1,0.993711,1,0.993711,0.75,0.993711,0.75,1,0.5,0.996855,0.993711,0.5,0.996855,0.5,1,1,0.990566,0.5,0.996855,0.5,0.996835,0.5,0.746835,0.5,0.5,1,0.493711,0.746835,0.5,0.75,0.490566,0.75,0.990566,1,0.75,0.5,1,1,1,0.75,0.5,0.5,0.990566,1,1,0.5,1,0.977987,0.5,1,1,0.5,1,0.993711,0.5,0.5,0.490566,0.75]
area_under_roc_curve
0.7765106281347022 [0.75,0.993711,1,1,1,0.5,0.996855,0.996835,0.496855,0.75,0.5,1,0.993711,0.496855,1,0.75,1,0.5,0.962264,0.5,0.5,1,0.75,1,0.75,0.496835,0.5,0.996855,0.996855,0.75,0.996855,0.5,0.746835,0.996835,0.993711,1,0.5,0.5,0.75,1,1,0.5,1,1,1,0.996855,1,0.5,0.75,0.5,0.5,0.490566,0.5,0.496855,0.743671,0.5,0.996855,0.996835,0.5,0.993711,1,1,0.993711,1,0.75,0.5,0.474843,1,0.5,0.5,0.5,0.75,0.993711,1,0.5,1,0.996835,0.5,1,1,0.496855,1,0.75,0.743671,0.993711,1,1,0.996855,1,0.5,0.493711,0.746835,0.990566,0.993711,1,0.993711,0.5,0.990566,0.5,1]
area_under_roc_curve
0.7827800334368282 [0.5,0.990566,0.996835,1,0.990566,0.5,1,1,1,0.75,0.5,0.75,0.990566,0.5,1,0.75,0.75,0.5,0.962264,0.5,0.5,0.75,0.75,1,0.75,0.5,0.5,0.5,1,1,1,1,0.496835,0.743671,0.987421,0.75,0.5,0.5,1,1,1,0.75,1,0.996855,1,0.996855,0.996835,0.5,0.75,0.75,1,0.996855,0.746835,0.996855,0.746835,0.5,1,1,0.5,0.996855,1,1,0.993711,0.996855,1,0.5,0.968553,1,0.5,0.75,0.75,0.5,0.993711,0.993711,0.5,1,1,0.5,1,1,0.5,0.75,0.75,0.990506,0.996855,1,1,0.996855,0.996835,0.5,0.493711,0.996835,0.996855,0.993711,0.5,0.996855,0.5,0.996855,0.496855,0.5]
area_under_roc_curve
0.7859644932728284 [1,0.984277,1,1,0.996855,0.5,1,1,0.993711,1,0.996855,0.990566,0.5,1,1,0.75,1,0.984277,0.5,0.5,0.496835,1,0.496835,1,0.75,0.493711,0.481132,0.5,0.993711,1,0.75,1,1,0.987421,0.75,0.75,0.496835,0.5,0.993671,1,0.746835,1,1,0.5,0.5,0.5,0.5,0.5,0.993711,0.996855,0.493711,1,1,0.996855,0.75,0.5,1,1,0.5,0.993711,0.993671,1,0.993711,1,1,0.490566,0.493711,1,0.75,0.5,1,0.75,0.5,1,0.5,1,1,0.493711,1,1,0.75,1,0.996835,0.996835,0.5,0.75,1,0.490566,0.5,0.5,1,1,0.5,0.984277,0.993711,0.75,0.5,0.5,0.5,1]
area_under_roc_curve
0.7734057797946022 [0.5,0.977987,1,1,1,0.5,1,1,0.993711,1,0.5,0.996855,0.5,0.5,1,0.5,1,0.471698,0.5,0.5,0.746835,1,0.496835,1,0.5,0.493711,0.996855,0.5,0.490566,1,0.75,1,1,0.996855,0.5,1,0.493671,0.5,1,0.996855,0.493671,1,0.993671,0.5,1,0.5,1,0.5,0.990566,0.5,0.484277,0.75,0.75,0.996855,0.75,0.5,1,1,1,0.987421,1,0.75,0.996855,1,1,0.487421,0.993711,1,0.5,0.5,1,0.75,0.5,1,0.5,1,1,0.987421,1,1,0.5,1,0.75,1,0.5,0.75,1,0.490566,1,0.5,0.496855,0.996835,1,0.981132,0.993711,1,0.5,0.5,0.5,1]
area_under_roc_curve
0.7671562773664514 [0.481132,0.75,1,1,0.5,0.990566,1,0.996855,0.5,1,0.993711,0.993711,0.5,0.5,1,0.996855,1,0.484277,0.5,0.490566,0.75,1,1,1,1,0.496855,0.990566,1,1,1,1,1,0.996855,0.996855,0.5,1,0.5,0.5,0.75,1,0.5,1,0.75,0.746835,0.75,0.746835,0.996855,0.5,0.996855,0.990566,1,0.746835,0.5,0.75,0.5,0.490566,1,0.5,0.496835,0.5,0.75,0.75,1,0.75,1,0.993711,0.5,1,0.746835,0.990566,0.996855,0.5,0.5,0.746835,0.5,0.75,0.996855,0.996855,0.996855,0.75,0.75,1,0.993711,0.490566,0.75,1,1,0.5,0.996855,0.5,0.5,1,0.5,0.5,0.981132,0.75,0.974843,0.496835,0.5,0.996855]
area_under_roc_curve
0.7702611257065517 [1,0.5,1,1,0.75,0.990566,1,0.996855,0.5,1,0.996855,1,0.5,0.5,1,0.996855,1,0.474843,0.5,0.496855,0.5,1,0.996855,1,0.996835,0.5,0.493711,1,1,0.5,1,1,0.996855,0.987421,0.5,0.5,0.5,0.5,0.75,1,0.990566,1,1,0.993671,0.5,1,0.990566,0.75,0.993711,0.993711,0.75,0.75,1,0.75,0.5,0.990566,1,1,0.746835,0.5,0.75,0.75,0.496835,1,0.993711,0.996855,0.5,1,0.75,0.987421,0.5,1,0.5,0.746835,0.5,0.75,0.993711,0.993711,1,0.996835,0.75,0.496855,0.993711,0.496855,0.5,0.746835,1,0.5,1,0.5,0.75,0.996835,0.5,0.5,0.996855,0.5,0.968553,0.5,0.5,0.993711]
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
0.5523681929230042
kappa
0.5522623364338641
kappa
0.5335093179937749
kappa
0.5209014617233364
kappa
0.5522270398108001
kappa
0.5648746649850228
kappa
0.5711132134973195
kappa
0.5459561721582847
kappa
0.5334541729056663
kappa
0.5397225725094577
kb_relative_information_score
0.5552815588013323
kb_relative_information_score
0.5552815588013325
kb_relative_information_score
0.5364906387506845
kb_relative_information_score
0.5239633587169191
kb_relative_information_score
0.5552815588013327
kb_relative_information_score
0.5678088388350979
kb_relative_information_score
0.5740724788519804
kb_relative_information_score
0.5490179187844498
kb_relative_information_score
0.5364906387506845
kb_relative_information_score
0.5427542787675673
mean_absolute_error
0.008875000000000004
mean_absolute_error
0.008875000000000004
mean_absolute_error
0.009250000000000005
mean_absolute_error
0.009500000000000005
mean_absolute_error
0.008875000000000004
mean_absolute_error
0.008625000000000004
mean_absolute_error
0.008500000000000004
mean_absolute_error
0.009000000000000005
mean_absolute_error
0.009250000000000005
mean_absolute_error
0.009125000000000005
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
0.55625
predictive_accuracy
0.55625
predictive_accuracy
0.5375
predictive_accuracy
0.525
predictive_accuracy
0.55625
predictive_accuracy
0.56875
predictive_accuracy
0.575
predictive_accuracy
0.55
predictive_accuracy
0.5375
predictive_accuracy
0.54375
prior_entropy
6.643856189774732
prior_entropy
6.643856189774732
prior_entropy
6.643856189774732
prior_entropy
6.643856189774732
prior_entropy
6.643856189774732
prior_entropy
6.643856189774732
prior_entropy
6.643856189774732
prior_entropy
6.643856189774732
prior_entropy
6.643856189774732
prior_entropy
6.643856189774732
recall
0.55625 [0,0,1,1,1,1,0,1,0,1,0.5,0.5,0,0,1,1,1,0,0,1,0,1,1,1,0,0,0.5,1,0.5,0,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,0.5,1,0,1,0,1,1,1,1,0,1,1,1,1,0.5,1,0,0,1,1,0,0.5,1,1,0.5,0,0.5,0,0,1,1,0,1,1,1,0,0.5,1,0,0.5,1,0,1,0,0,1,0,1,0,0,1]
recall
0.55625 [1,0,1,1,1,1,0.5,1,0,1,0.5,0,0,0,1,1,1,0,0,1,1,0,0,1,1,0,0,1,1,1,1,1,0.5,0,0,1,1,1,1,1,1,1,1,1,0.5,0.5,1,1,0.5,1,1,0.5,1,1,1,0,1,1,1,0,1,1,1,0,1,0,0,1,0,1,0.5,1,1,0,0,0,0,0.5,1,0.5,0,0.5,1,1,0,1,1,0,0.5,1,0,1,0,0,1,0,1,0,0,1]
recall
0.5375 [0,0,1,1,0.5,1,1,0.5,1,1,0.5,0,1,0,1,0,0.5,0,0,0,0,0,0,1,1,0,0,1,0.5,1,1,1,1,0,1,1,1,0,1,0.5,0,1,1,1,1,1,0.5,1,0,1,0,1,1,0,1,0,1,1,1,0,1,0,0.5,0,1,0,0,1,1,0.5,0,1,1,1,1,0.5,0.5,0,1,1,0,1,0,0,1,1,1,0,1,1,0.5,1,1,0,1,1,0,0,0,1]
recall
0.525 [0,0,1,1,0.5,0,1,0.5,0.5,0.5,0.5,0,1,0.5,1,0,1,0,1,0,0,1,0.5,1,0,0,0,1,0.5,1,1,1,0,0.5,1,1,1,0,1,1,1,1,1,1,1,1,0.5,1,0.5,1,0,1,1,0,1,0,1,1,1,0,1,0,1,0,0.5,0,0,1,0,0.5,0,0.5,0,0.5,1,1,0.5,0,1,1,1,0.5,0,0,1,1,1,0,1,1,0,1,1,0,1,1,0,0,0,0.5]
recall
0.55625 [0.5,1,1,1,1,0,1,1,0,0.5,0,1,1,0,1,0.5,1,0,1,0,0,1,0.5,1,0.5,0,0,1,1,0.5,1,0,0.5,1,1,1,0,0,0.5,1,1,0,1,1,1,1,1,0,0.5,0,0,0,0,0,0.5,0,1,1,0,1,1,1,1,1,0.5,0,0,1,0,0,0,0.5,1,1,0,1,1,0,1,1,0,1,0.5,0.5,1,1,1,1,1,0,0,0.5,1,1,1,1,0,1,0,1]
recall
0.56875 [0,1,1,1,1,0,1,1,1,0.5,0,0.5,1,0,1,0.5,0.5,0,1,0,0,0.5,0.5,1,0.5,0,0,0,1,1,1,1,0,0.5,1,0.5,0,0,1,1,1,0.5,1,1,1,1,1,0,0.5,0.5,1,1,0.5,1,0.5,0,1,1,0,1,1,1,1,1,1,0,1,1,0,0.5,0.5,0,1,1,0,1,1,0,1,1,0,0.5,0.5,1,1,1,1,1,1,0,0,1,1,1,0,1,0,1,0,0]
recall
0.575 [1,1,1,1,1,0,1,1,1,1,1,1,0,1,1,0.5,1,1,0,0,0,1,0,1,0.5,0,0,0,1,1,0.5,1,1,1,0.5,0.5,0,0,1,1,0.5,1,1,0,0,0,0,0,1,1,0,1,1,1,0.5,0,1,1,0,1,1,1,1,1,1,0,0,1,0.5,0,1,0.5,0,1,0,1,1,0,1,1,0.5,1,1,1,0,0.5,1,0,0,0,1,1,0,1,1,0.5,0,0,0,1]
recall
0.55 [0,1,1,1,1,0,1,1,1,1,0,1,0,0,1,0,1,0,0,0,0.5,1,0,1,0,0,1,0,0,1,0.5,1,1,1,0,1,0,0,1,1,0,1,1,0,1,0,1,0,1,0,0,0.5,0.5,1,0.5,0,1,1,1,1,1,0.5,1,1,1,0,1,1,0,0,1,0.5,0,1,0,1,1,1,1,1,0,1,0.5,1,0,0.5,1,0,1,0,0,1,1,1,1,1,0,0,0,1]
recall
0.5375 [0,0.5,1,1,0,1,1,1,0,1,1,1,0,0,1,1,1,0,0,0,0.5,1,1,1,1,0,1,1,1,1,1,1,1,1,0,1,0,0,0.5,1,0,1,0.5,0.5,0.5,0.5,1,0,1,1,1,0.5,0,0.5,0,0,1,0,0,0,0.5,0.5,1,0.5,1,1,0,1,0.5,1,1,0,0,0.5,0,0.5,1,1,1,0.5,0.5,1,1,0,0.5,1,1,0,1,0,0,1,0,0,1,0.5,1,0,0,1]
recall
0.54375 [1,0,1,1,0.5,1,1,1,0,1,1,1,0,0,1,1,1,0,0,0,0,1,1,1,1,0,0,1,1,0,1,1,1,1,0,0,0,0,0.5,1,1,1,1,1,0,1,1,0.5,1,1,0.5,0.5,1,0.5,0,1,1,1,0.5,0,0.5,0.5,0,1,1,1,0,1,0.5,1,0,1,0,0.5,0,0.5,1,1,1,1,0.5,0,1,0,0,0.5,1,0,1,0,0.5,1,0,0,1,0,1,0,0,1]
relative_absolute_error
0.4482323232323227
relative_absolute_error
0.4482323232323227
relative_absolute_error
0.4671717171717167
relative_absolute_error
0.4797979797979793
relative_absolute_error
0.4482323232323227
relative_absolute_error
0.43560606060606005
relative_absolute_error
0.4292929292929288
relative_absolute_error
0.45454545454545403
relative_absolute_error
0.4671717171717167
relative_absolute_error
0.4608585858585853
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
0.09420721840708389
root_mean_squared_error
0.09420721840708389
root_mean_squared_error
0.09617692030835674
root_mean_squared_error
0.09746794344808966
root_mean_squared_error
0.09420721840708389
root_mean_squared_error
0.09287087810503357
root_mean_squared_error
0.0921954445729289
root_mean_squared_error
0.0948683298050514
root_mean_squared_error
0.09617692030835674
root_mean_squared_error
0.09552486587271403
root_relative_squared_error
0.9468181696950296
root_relative_squared_error
0.9468181696950296
root_relative_squared_error
0.9666144186507013
root_relative_squared_error
0.9795896894087641
root_relative_squared_error
0.9468181696950296
root_relative_squared_error
0.9333874443188747
root_relative_squared_error
0.926599081904282
root_relative_squared_error
0.9534625892455919
root_relative_squared_error
0.9666144186507013
root_relative_squared_error
0.9600610249964171
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
491.47593899942876
usercpu_time_millis
490.21646099936333
usercpu_time_millis
492.7688279985887
usercpu_time_millis
493.89460399834206
usercpu_time_millis
497.1289599998272
usercpu_time_millis
492.52348600020923
usercpu_time_millis
496.60842699995555
usercpu_time_millis
496.3657839998632
usercpu_time_millis
493.89252699984354
usercpu_time_millis
493.11058800230967
usercpu_time_millis_testing
64.89556499946048
usercpu_time_millis_testing
64.6326179994503
usercpu_time_millis_testing
64.99938900014968
usercpu_time_millis_testing
65.11875999967742
usercpu_time_millis_testing
64.72889699944062
usercpu_time_millis_testing
64.70364500091819
usercpu_time_millis_testing
64.92912499925296
usercpu_time_millis_testing
64.86829399909766
usercpu_time_millis_testing
64.986321998731
usercpu_time_millis_testing
64.7912600015843
usercpu_time_millis_training
426.5803739999683
usercpu_time_millis_training
425.58384299991303
usercpu_time_millis_training
427.769438998439
usercpu_time_millis_training
428.77584399866464
usercpu_time_millis_training
432.4000630003866
usercpu_time_millis_training
427.81984099929105
usercpu_time_millis_training
431.6793020007026
usercpu_time_millis_training
431.49749000076554
usercpu_time_millis_training
428.90620500111254
usercpu_time_millis_training
428.31932800072536
wall_clock_time_millis
491.4865493774414
wall_clock_time_millis
490.22531509399414
wall_clock_time_millis
492.77734756469727
wall_clock_time_millis
493.90339851379395
wall_clock_time_millis
497.13826179504395
wall_clock_time_millis
492.53106117248535
wall_clock_time_millis
496.61874771118164
wall_clock_time_millis
496.384859085083
wall_clock_time_millis
493.90268325805664
wall_clock_time_millis
493.1190013885498
wall_clock_time_millis_testing
64.90540504455566
wall_clock_time_millis_testing
64.64076042175293
wall_clock_time_millis_testing
65.00720977783203
wall_clock_time_millis_testing
65.12641906738281
wall_clock_time_millis_testing
64.73755836486816
wall_clock_time_millis_testing
64.71037864685059
wall_clock_time_millis_testing
64.93854522705078
wall_clock_time_millis_testing
64.87536430358887
wall_clock_time_millis_testing
64.99576568603516
wall_clock_time_millis_testing
64.79930877685547
wall_clock_time_millis_training
426.58114433288574
wall_clock_time_millis_training
425.5845546722412
wall_clock_time_millis_training
427.77013778686523
wall_clock_time_millis_training
428.77697944641113
wall_clock_time_millis_training
432.4007034301758
wall_clock_time_millis_training
427.82068252563477
wall_clock_time_millis_training
431.68020248413086
wall_clock_time_millis_training
431.50949478149414
wall_clock_time_millis_training
428.9069175720215
wall_clock_time_millis_training
428.31969261169434