10413445
1
Jan van Rijn
9954
Supervised Classification
16360
sklearn.svm.classes.SVC(32)
8251189
C
13257.403304167956
16360
cache_size
200
16360
class_weight
null
16360
coef0
-0.609628306536486
16360
decision_function_shape
"ovr"
16360
degree
3
16360
gamma
0.859964143916746
16360
kernel
"sigmoid"
16360
max_iter
-1
16360
probability
false
16360
random_state
34665
16360
shrinking
false
16360
tol
1.6626046731423483e-05
16360
verbose
false
16360
openml-python
Sklearn_0.21.2.
1491
one-hundred-plants-margin
https://www.openml.org/data/download/1592283/phpCsX3fx
-1
21748699
description
https://api.openml.org/data/download/21748699/description.xml
-1
21748700
predictions
https://api.openml.org/data/download/21748700/predictions.arff
area_under_roc_curve
0.915088383838384 [0.904672,0.96875,1,1,1,0.936237,0.999684,0.999684,0.905619,0.96875,0.967803,0.999684,0.968434,0.8125,1,0.968434,0.999684,0.809659,0.652778,0.650884,0.874369,0.96875,0.904672,1,0.936869,0.714646,0.715593,0.935922,0.968434,1,0.999684,1,0.999369,0.746843,0.999369,0.936237,0.748422,0.748422,0.999369,1,0.935606,0.999684,0.999684,0.968434,1,0.96875,0.937184,0.874369,0.90404,0.90625,0.968119,0.905934,0.937184,0.842803,0.873737,0.74779,1,0.999684,0.902462,0.873737,0.936869,1,0.841856,0.937184,0.999684,0.841856,0.748106,0.999684,0.842803,0.904987,0.874369,0.905619,0.746528,0.96875,0.905619,0.96875,0.968434,0.716856,1,0.96875,0.875,0.90625,0.936869,0.749369,0.905934,1,0.999684,0.936553,0.937184,0.96875,0.874684,0.967803,0.937184,0.937184,0.96875,0.936237,0.905619,0.905303,0.653409,0.874684]
average_cost
0
f_measure
0.833236927198149 [0.764706,0.967742,1,1,1,0.823529,0.969697,0.969697,0.83871,0.967742,0.882353,0.969697,0.9375,0.769231,1,0.9375,0.969697,0.571429,0.3125,0.263158,0.8,0.967742,0.764706,1,0.875,0.388889,0.424242,0.8,0.9375,1,0.969697,1,0.941176,0.470588,0.941176,0.823529,0.551724,0.551724,0.941176,1,0.777778,0.969697,0.969697,0.9375,1,0.967742,0.903226,0.8,0.722222,0.896552,0.909091,0.866667,0.903226,0.733333,0.75,0.516129,1,0.969697,0.634146,0.75,0.875,1,0.666667,0.903226,0.969697,0.666667,0.533333,0.969697,0.733333,0.787879,0.8,0.83871,0.457143,0.967742,0.83871,0.967742,0.9375,0.482759,1,0.967742,0.857143,0.896552,0.875,0.615385,0.866667,1,0.969697,0.848485,0.903226,0.967742,0.827586,0.882353,0.903226,0.903226,0.967742,0.823529,0.83871,0.8125,0.333333,0.827586]
kappa
0.8301767676767677
kb_relative_information_score
0.8315080835458679
mean_absolute_error
0.003362499999999983
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
0.8409790661780596 [0.722222,1,1,1,1,0.777778,0.941176,0.941176,0.866667,1,0.833333,0.941176,0.9375,1,1,0.9375,0.941176,0.526316,0.3125,0.227273,0.857143,1,0.722222,1,0.875,0.35,0.411765,0.736842,0.9375,1,0.941176,1,0.888889,0.444444,0.888889,0.777778,0.615385,0.615385,0.888889,1,0.7,0.941176,0.941176,0.9375,1,1,0.933333,0.857143,0.65,1,0.882353,0.928571,0.933333,0.785714,0.75,0.533333,1,0.941176,0.52,0.75,0.875,1,0.647059,0.933333,0.941176,0.647059,0.571429,0.941176,0.785714,0.764706,0.857143,0.866667,0.421053,1,0.866667,1,0.9375,0.538462,1,1,1,1,0.875,0.8,0.928571,1,0.941176,0.823529,0.933333,1,0.923077,0.833333,0.933333,0.933333,1,0.777778,0.866667,0.8125,0.357143,0.923077]
predictive_accuracy
0.831875
prior_entropy
6.643856189774611
recall
0.831875 [0.8125,0.9375,1,1,1,0.875,1,1,0.8125,0.9375,0.9375,1,0.9375,0.625,1,0.9375,1,0.625,0.3125,0.3125,0.75,0.9375,0.8125,1,0.875,0.4375,0.4375,0.875,0.9375,1,1,1,1,0.5,1,0.875,0.5,0.5,1,1,0.875,1,1,0.9375,1,0.9375,0.875,0.75,0.8125,0.8125,0.9375,0.8125,0.875,0.6875,0.75,0.5,1,1,0.8125,0.75,0.875,1,0.6875,0.875,1,0.6875,0.5,1,0.6875,0.8125,0.75,0.8125,0.5,0.9375,0.8125,0.9375,0.9375,0.4375,1,0.9375,0.75,0.8125,0.875,0.5,0.8125,1,1,0.875,0.875,0.9375,0.75,0.9375,0.875,0.875,0.9375,0.875,0.8125,0.8125,0.3125,0.75]
relative_absolute_error
0.16982323232323118
root_mean_prior_squared_error
0.09949874371066209
root_mean_squared_error
0.057987067523715866
root_relative_squared_error
0.5827919565732375
total_cost
0
area_under_roc_curve
0.9243093702730674 [0.993711,0.75,1,1,1,1,1,1,1,1,0.75,1,1,0.75,1,1,1,0.746835,0.743671,0.996855,0.496855,1,0.996855,1,0.996855,0.75,0.75,0.996835,1,1,1,1,1,0.496835,1,0.996855,1,0.996855,1,1,0.996855,1,1,1,1,1,1,0.996855,1,0.75,1,1,1,0.75,0.996855,0.496855,1,1,1,1,1,1,1,1,1,1,0.75,1,1,0.496855,0.75,1,0.746835,1,1,1,0.75,0.496835,1,1,1,1,1,1,1,1,1,1,0.75,1,1,1,1,1,1,0.746835,1,0.993671,0.496835,1]
area_under_roc_curve
0.9179205477270915 [1,1,1,1,1,1,0.996835,1,1,1,1,1,1,0.75,1,1,1,0.75,0.75,0.490566,1,1,0.996855,1,1,0.746835,0.496835,1,1,1,1,1,1,0.996835,1,0.496855,0.996855,1,1,1,1,1,1,1,1,1,1,1,0.996835,1,1,1,1,0.75,1,0.496855,1,1,0.996855,1,0.5,1,0.996835,1,1,0.746835,0.746835,1,0.5,1,0.993671,1,0.496835,1,1,1,1,0.993671,1,0.75,0.75,1,0.993711,0.5,0.746835,1,1,0.996835,0.75,1,0.75,1,0.75,0.75,1,1,1,1,0.746835,0.5]
area_under_roc_curve
0.9243093702730671 [1,1,1,1,1,0.996835,1,1,1,1,1,1,1,0.75,1,1,1,0.746835,0.5,0.493671,0.5,1,0.75,1,1,0.743671,1,0.996855,1,1,1,1,1,0.746835,0.996855,1,0.993711,0.496855,1,1,0.746835,1,1,1,1,1,1,1,0.75,1,1,1,1,1,1,0.75,1,1,0.993711,0.496835,1,1,1,0.5,1,1,0.996835,1,0.996855,0.75,0.75,1,0.993711,1,0.996855,1,1,0.496835,1,1,1,1,1,0.5,1,1,1,1,1,1,1,0.996855,1,1,1,1,1,0.75,0.496855,1]
area_under_roc_curve
0.9022171801608149 [0.996835,1,1,1,1,0.75,1,1,0.746835,1,1,1,1,0.75,1,1,0.996835,0.996835,0.496855,0.5,1,1,0.996835,1,0.5,0.5,0.746835,1,1,1,1,1,1,0.496835,0.996855,0.996855,1,0.5,1,1,1,0.996855,0.996855,1,1,1,1,1,0.996835,0.75,1,1,1,0.75,1,0.993671,1,1,0.996855,1,0.996855,1,0.996835,1,1,0.496835,0.743671,1,0.996855,0.75,0.5,0.75,0.993711,0.75,1,1,1,0.75,1,1,1,1,0.75,0.75,1,1,1,1,1,1,0.75,1,0.996855,1,1,0.996855,0.75,0.996835,0.487421,0.5]
area_under_roc_curve
0.8957885518668895 [0.75,1,1,1,1,0.996835,1,1,0.5,1,1,1,0.5,0.5,1,0.996835,1,0.746835,0.990566,0.740506,0.75,1,0.75,1,1,0.987342,0.746835,1,0.996855,1,0.996855,1,1,0.496835,1,1,0.5,0.75,1,1,0.993671,1,1,0.5,1,1,1,0.75,1,1,0.496855,0.996855,0.75,0.993711,0.496835,0.5,1,0.996835,0.990506,1,1,1,0.5,0.5,1,1,0.5,1,0.5,0.996835,1,1,1,1,0.75,1,0.996835,0.75,1,1,1,0.75,1,0.75,1,1,1,1,1,1,1,1,1,1,0.75,0.996855,0.996835,1,0.496855,1]
area_under_roc_curve
0.9115118223071409 [0.75,1,1,1,1,1,1,1,1,0.75,1,0.996835,1,1,1,1,1,0.993671,0.5,0.75,1,0.75,0.996835,1,0.996835,0.993671,0.740506,0.5,1,1,1,1,0.996835,0.746835,1,0.746835,0.75,0.746835,1,1,0.75,1,1,0.996855,1,1,0.996835,0.75,0.746835,0.75,1,1,1,1,0.996835,0.75,1,1,0.75,0.996855,1,1,0.493711,1,1,0.75,1,1,1,1,1,0.746835,1,1,0.75,1,1,0.996835,1,1,0.5,0.75,1,0.996835,0.5,1,1,0.996855,0.996835,0.75,0.5,0.996835,1,1,1,1,1,1,0.496855,0.75]
area_under_roc_curve
0.9021176657909402 [0.996835,1,1,1,1,0.75,1,1,0.996855,1,0.996855,1,1,1,1,0.75,1,0.996855,0.493671,0.490506,0.996835,1,0.996835,1,1,0.5,0.493711,0.746835,1,1,1,1,1,0.996855,1,1,0.5,0.75,0.993671,1,0.993671,1,1,1,1,0.75,0.5,0.746835,0.996855,1,1,1,1,1,0.75,0.746835,1,1,0.5,0.496855,0.996835,1,0.996855,0.996835,1,0.496855,0.5,1,1,1,1,1,0.746835,1,0.996835,1,1,0.496855,1,1,0.75,1,1,0.996835,1,1,1,0.5,1,1,1,1,0.75,1,1,0.75,1,1,0.5,1]
area_under_roc_curve
0.9336836239152934 [0.75,1,1,1,1,0.996835,1,1,1,1,1,1,0.996835,1,1,1,1,1,0.740506,0.5,0.75,1,1,1,0.75,0.496855,0.996855,0.996835,1,1,1,1,0.996855,1,1,1,0.496835,0.746835,1,1,1,1,1,1,1,1,1,0.75,0.996855,1,0.996855,0.75,0.75,0.996855,0.996835,0.993671,1,1,0.996835,1,1,1,1,1,1,0.996855,0.5,1,1,1,1,1,0.996835,1,1,1,1,0.5,1,1,0.75,1,0.75,0.75,0.75,1,1,1,1,1,1,0.75,1,1,1,0.996835,0.75,1,1,1]
area_under_roc_curve
0.930598678449168 [0.996855,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.496855,0.75,0.990566,1,1,0.5,1,1,0.496855,0.496855,1,1,1,1,1,1,0.996855,1,1,1,0.496835,1,1,1,1,1,1,1,1,1,1,0.496855,1,1,0.75,0.996835,0.75,0.75,0.5,1,1,0.993671,1,1,1,0.75,1,1,0.996855,0.993671,1,0.746835,1,1,0.496855,0.493671,1,1,1,1,0.5,1,1,1,1,1,0.5,1,1,1,0.996835,1,1,0.75,1,1,0.996835,1,1,0.5,1,0.75,1]
area_under_roc_curve
0.9086060027067908 [1,1,1,1,1,0.996855,1,0.996855,0.75,1,0.993711,1,1,0.75,1,1,1,0.496855,0.5,0.993711,1,1,1,1,1,0.493711,0.5,0.996835,0.75,1,1,1,1,0.993711,1,1,0.746835,1,1,1,1,1,1,1,1,1,1,1,0.996855,1,1,0.75,1,0.75,1,1,1,1,0.993671,0.746835,0.75,1,0.496835,1,0.996855,0.996855,0.5,0.996855,0.75,0.993711,1,1,0.496835,1,0.75,0.75,1,1,1,1,1,0.5,1,0.5,1,1,0.996835,0.75,1,1,0.996835,0.996835,1,0.75,1,1,0.996855,0.5,0.75,0.996855]
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
f_measure
0.8452083333333332 [0.5,0.666667,1,1,1,1,1,1,1,1,0.666667,1,1,0.666667,1,1,1,0.5,0.4,0.666667,0,1,0.666667,1,0.666667,0.666667,0.666667,0.8,1,1,1,1,1,0,1,0.666667,1,0.666667,1,1,0.666667,1,1,1,1,1,1,0.666667,1,0.666667,1,1,1,0.666667,0.666667,0,1,1,1,1,1,1,1,1,1,1,0.666667,1,1,0,0.666667,1,0.5,1,1,1,0.666667,0,1,1,1,1,1,1,1,1,1,1,0.666667,1,1,1,1,1,1,0.5,1,0.666667,0,1]
kappa
0.8484011054086064
kappa
0.8357224657426056
kappa
0.848389134554643
kappa
0.8042002210642666
kappa
0.7914856646394439
kappa
0.8230577826928394
kappa
0.8041383667667036
kappa
0.8673195387774444
kappa
0.8609849532009005
kappa
0.8168469250809189
kb_relative_information_score
0.8496726395948171
kb_relative_information_score
0.8371453595610518
kb_relative_information_score
0.8496726395948171
kb_relative_information_score
0.8058271594766385
kb_relative_information_score
0.7932998794428733
kb_relative_information_score
0.8246180795272865
kb_relative_information_score
0.8058271594766385
kb_relative_information_score
0.8684635596454652
kb_relative_information_score
0.8621999196285823
kb_relative_information_score
0.8183544395104039
mean_absolute_error
0.003000000000000001
mean_absolute_error
0.0032500000000000007
mean_absolute_error
0.003000000000000001
mean_absolute_error
0.0038750000000000013
mean_absolute_error
0.004125000000000002
mean_absolute_error
0.003500000000000001
mean_absolute_error
0.0038750000000000013
mean_absolute_error
0.0026250000000000006
mean_absolute_error
0.0027500000000000007
mean_absolute_error
0.003625000000000001
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]
precision
0.8770833333333334 [0.333333,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,0.333333,0.5,0,1,0.5,1,0.5,1,1,0.666667,1,1,1,1,1,0,1,0.5,1,0.5,1,1,0.5,1,1,1,1,1,1,0.5,1,1,1,1,1,1,0.5,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,0.5,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,0.5,0,1]
predictive_accuracy
0.85
predictive_accuracy
0.8375
predictive_accuracy
0.85
predictive_accuracy
0.80625
predictive_accuracy
0.79375
predictive_accuracy
0.825
predictive_accuracy
0.80625
predictive_accuracy
0.86875
predictive_accuracy
0.8625
predictive_accuracy
0.81875
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
0.85 [1,0.5,1,1,1,1,1,1,1,1,0.5,1,1,0.5,1,1,1,0.5,0.5,1,0,1,1,1,1,0.5,0.5,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0.5,1,0,1,1,1,1,1,1,1,1,1,1,0.5,1,1,0,0.5,1,0.5,1,1,1,0.5,0,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,0.5,1,1,0,1]
recall
0.8375 [1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0.5,0.5,0,1,1,1,1,1,0.5,0,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,0,1,1,1,1,0,1,1,1,1,0.5,0.5,1,0,1,1,1,0,1,1,1,1,1,1,0.5,0.5,1,1,0,0.5,1,1,1,0.5,1,0.5,1,0.5,0.5,1,1,1,1,0.5,0]
recall
0.85 [1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0.5,0,0,0,1,0.5,1,1,0.5,1,1,1,1,1,1,1,0.5,1,1,1,0,1,1,0.5,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,0.5,1,1,1,0,1,1,1,0,1,1,1,1,1,0.5,0.5,1,1,1,1,1,1,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,0,1]
recall
0.80625 [1,1,1,1,1,0.5,1,1,0.5,1,1,1,1,0.5,1,1,1,1,0,0,1,1,1,1,0,0,0.5,1,1,1,1,1,1,0,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,0,0.5,1,1,0.5,0,0.5,1,0.5,1,1,1,0.5,1,1,1,1,0.5,0.5,1,1,1,1,1,1,0.5,1,1,1,1,1,0.5,1,0,0]
recall
0.79375 [0.5,1,1,1,1,1,1,1,0,1,1,1,0,0,1,1,1,0.5,1,0.5,0.5,1,0.5,1,1,1,0.5,1,1,1,1,1,1,0,1,1,0,0.5,1,1,1,1,1,0,1,1,1,0.5,1,1,0,1,0.5,1,0,0,1,1,1,1,1,1,0,0,1,1,0,1,0,1,1,1,1,1,0.5,1,1,0.5,1,1,1,0.5,1,0.5,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0,1]
recall
0.825 [0.5,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,0,0.5,1,0.5,1,1,1,1,0.5,0,1,1,1,1,1,0.5,1,0.5,0.5,0.5,1,1,0.5,1,1,1,1,1,1,0.5,0.5,0.5,1,1,1,1,1,0.5,1,1,0.5,1,1,1,0,1,1,0.5,1,1,1,1,1,0.5,1,1,0.5,1,1,1,1,1,0,0.5,1,1,0,1,1,1,1,0.5,0,1,1,1,1,1,1,1,0,0.5]
recall
0.80625 [1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,0.5,1,1,0,0,1,1,1,1,1,0,0,0.5,1,1,1,1,1,1,1,1,0,0.5,1,1,1,1,1,1,1,0.5,0,0.5,1,1,1,1,1,1,0.5,0.5,1,1,0,0,1,1,1,1,1,0,0,1,1,1,1,1,0.5,1,1,1,1,0,1,1,0.5,1,1,1,1,1,1,0,1,1,1,1,0.5,1,1,0.5,1,1,0,1]
recall
0.86875 [0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,0,0.5,1,1,1,0.5,0,1,1,1,1,1,1,1,1,1,1,0,0.5,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0.5,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,0,1,1,0.5,1,0.5,0.5,0.5,1,1,1,1,1,1,0.5,1,1,1,1,0.5,1,1,1]
recall
0.8625 [1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0.5,1,1,1,0,1,1,0,0,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,0,1,1,0.5,1,0.5,0.5,0,1,1,1,1,1,1,0.5,1,1,1,1,1,0.5,1,1,0,0,1,1,1,1,0,1,1,1,1,1,0,1,1,1,1,1,1,0.5,1,1,1,1,1,0,1,0.5,1]
recall
0.81875 [1,1,1,1,1,1,1,1,0.5,1,1,1,1,0.5,1,1,1,0,0,1,1,1,1,1,1,0,0,1,0.5,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,0.5,1,1,1,1,1,0.5,0.5,1,0,1,1,1,0,1,0.5,1,1,1,0,1,0.5,0.5,1,1,1,1,1,0,1,0,1,1,1,0.5,1,1,1,1,1,0.5,1,1,1,0,0.5,1]
relative_absolute_error
0.1515151515151513
relative_absolute_error
0.1641414141414139
relative_absolute_error
0.1515151515151513
relative_absolute_error
0.19570707070707044
relative_absolute_error
0.20833333333333307
relative_absolute_error
0.17676767676767655
relative_absolute_error
0.19570707070707044
relative_absolute_error
0.13257575757575737
relative_absolute_error
0.1388888888888887
relative_absolute_error
0.18308080808080782
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
0.05477225575051662
root_mean_squared_error
0.0570087712549569
root_mean_squared_error
0.05477225575051662
root_mean_squared_error
0.06224949798994367
root_mean_squared_error
0.06422616289332567
root_mean_squared_error
0.05916079783099617
root_mean_squared_error
0.06224949798994367
root_mean_squared_error
0.051234753829797995
root_mean_squared_error
0.052440442408507586
root_mean_squared_error
0.06020797289396149
root_relative_squared_error
0.5504818825631801
root_relative_squared_error
0.5729597091269403
root_relative_squared_error
0.5504818825631801
root_relative_squared_error
0.6256309946079566
root_relative_squared_error
0.6454972243679026
root_relative_squared_error
0.5945883900105629
root_relative_squared_error
0.6256309946079566
root_relative_squared_error
0.5149286505444369
root_relative_squared_error
0.5270462766947296
root_relative_squared_error
0.6051128953853288
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
365.39689700001077
usercpu_time_millis
367.15700999998546
usercpu_time_millis
368.1357789999993
usercpu_time_millis
369.7455580000053
usercpu_time_millis
365.71656899999994
usercpu_time_millis
367.6683550000064
usercpu_time_millis
367.44812099999535
usercpu_time_millis
369.88691799999174
usercpu_time_millis
371.67679099999873
usercpu_time_millis
368.21629900001085
usercpu_time_millis_testing
64.54308200000014
usercpu_time_millis_testing
64.63125399999115
usercpu_time_millis_testing
63.83455900000001
usercpu_time_millis_testing
64.4624279999988
usercpu_time_millis_testing
64.22609999999906
usercpu_time_millis_testing
64.34046300000773
usercpu_time_millis_testing
65.09633899999301
usercpu_time_millis_testing
64.3173299999944
usercpu_time_millis_testing
64.73820099999728
usercpu_time_millis_testing
63.72306100000458
usercpu_time_millis_training
300.8538150000106
usercpu_time_millis_training
302.5257559999943
usercpu_time_millis_training
304.30121999999926
usercpu_time_millis_training
305.2831300000065
usercpu_time_millis_training
301.49046900000087
usercpu_time_millis_training
303.32789199999866
usercpu_time_millis_training
302.35178200000234
usercpu_time_millis_training
305.56958799999734
usercpu_time_millis_training
306.93859000000145
usercpu_time_millis_training
304.4932380000063
wall_clock_time_millis
365.4181957244873
wall_clock_time_millis
367.17915534973145
wall_clock_time_millis
368.15619468688965
wall_clock_time_millis
369.77529525756836
wall_clock_time_millis
365.74578285217285
wall_clock_time_millis
367.6900863647461
wall_clock_time_millis
367.46668815612793
wall_clock_time_millis
369.9157238006592
wall_clock_time_millis
371.69909477233887
wall_clock_time_millis
368.2563304901123
wall_clock_time_millis_testing
64.55135345458984
wall_clock_time_millis_testing
64.63932991027832
wall_clock_time_millis_testing
63.841819763183594
wall_clock_time_millis_testing
64.47076797485352
wall_clock_time_millis_testing
64.23473358154297
wall_clock_time_millis_testing
64.34869766235352
wall_clock_time_millis_testing
65.10400772094727
wall_clock_time_millis_testing
64.32580947875977
wall_clock_time_millis_testing
64.74781036376953
wall_clock_time_millis_testing
63.73167037963867
wall_clock_time_millis_training
300.86684226989746
wall_clock_time_millis_training
302.5398254394531
wall_clock_time_millis_training
304.31437492370605
wall_clock_time_millis_training
305.30452728271484
wall_clock_time_millis_training
301.5110492706299
wall_clock_time_millis_training
303.3413887023926
wall_clock_time_millis_training
302.36268043518066
wall_clock_time_millis_training
305.5899143218994
wall_clock_time_millis_training
306.95128440856934
wall_clock_time_millis_training
304.52466011047363