10412235
1
Jan van Rijn
9954
Supervised Classification
16360
sklearn.svm.classes.SVC(32)
8249999
C
1472.8662881498958
16360
cache_size
200
16360
class_weight
null
16360
coef0
-0.3150805847806095
16360
decision_function_shape
"ovr"
16360
degree
3
16360
gamma
0.06620574278449574
16360
kernel
"sigmoid"
16360
max_iter
-1
16360
probability
false
16360
random_state
44380
16360
shrinking
false
16360
tol
0.004847036473626274
16360
verbose
false
16360
openml-python
Sklearn_0.21.2.
1491
one-hundred-plants-margin
https://www.openml.org/data/download/1592283/phpCsX3fx
-1
21746263
description
https://api.openml.org/data/download/21746263/description.xml
-1
21746264
predictions
https://api.openml.org/data/download/21746264/predictions.arff
area_under_roc_curve
0.9081439393939397 [0.842487,0.96875,1,1,0.96875,0.874369,0.96875,0.999684,0.936237,0.96875,0.905619,0.999053,0.96875,0.780934,1,0.968434,1,0.684659,0.653093,0.649937,0.873737,0.96875,0.873737,1,0.937184,0.622159,0.714331,0.936553,0.9375,0.96875,0.999369,1,0.967803,0.81029,0.905619,0.967172,0.807765,0.684975,0.999369,0.999684,0.904672,0.968119,1,0.967803,0.96875,0.968119,0.96875,0.905934,0.934975,0.905934,0.874053,0.874684,0.937184,0.811869,0.904987,0.590909,1,0.999684,0.811553,0.904356,0.999053,0.999684,0.90404,0.968119,0.999684,0.810922,0.684659,0.999684,0.874369,0.903725,0.843119,0.905619,0.840909,0.937184,0.842803,0.96875,0.96875,0.717487,1,0.96875,0.90625,0.937184,0.905934,0.873422,0.905619,0.936869,0.999684,0.905934,0.937184,1,0.812184,0.967803,0.968119,0.905934,0.968119,0.936237,0.967487,0.935922,0.685922,0.905934]
average_cost
0
f_measure
0.8185077814494732 [0.709677,0.967742,1,1,0.967742,0.8,0.967742,0.969697,0.823529,0.967742,0.83871,0.914286,0.967742,0.692308,1,0.9375,1,0.387097,0.322581,0.243902,0.75,0.967742,0.75,1,0.903226,0.275862,0.378378,0.848485,0.933333,0.967742,0.941176,1,0.882353,0.606061,0.83871,0.833333,0.487805,0.4,0.941176,0.969697,0.764706,0.909091,1,0.882353,0.967742,0.909091,0.967742,0.866667,0.736842,0.866667,0.774194,0.827586,0.903226,0.714286,0.787879,0.214286,1,0.969697,0.689655,0.742857,0.914286,0.969697,0.722222,0.909091,0.969697,0.645161,0.387097,0.969697,0.8,0.702703,0.758621,0.83871,0.611111,0.903226,0.733333,0.967742,0.967742,0.518519,1,0.967742,0.896552,0.903226,0.866667,0.727273,0.83871,0.875,0.969697,0.866667,0.903226,1,0.740741,0.882353,0.909091,0.866667,0.909091,0.823529,0.857143,0.8,0.444444,0.866667]
kappa
0.8162878787878788
kb_relative_information_score
0.817728075508727
mean_absolute_error
0.0036374999999999776
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
0.8267095286464474 [0.733333,1,1,1,1,0.857143,1,0.941176,0.777778,1,0.866667,0.842105,1,0.9,1,0.9375,1,0.4,0.333333,0.2,0.75,1,0.75,1,0.933333,0.307692,0.333333,0.823529,1,1,0.888889,1,0.833333,0.588235,0.866667,0.75,0.4,0.428571,0.888889,0.941176,0.722222,0.882353,1,0.833333,1,0.882353,1,0.928571,0.636364,0.928571,0.8,0.923077,0.933333,0.833333,0.764706,0.25,1,0.941176,0.769231,0.684211,0.842105,0.941176,0.65,0.882353,0.941176,0.666667,0.4,0.941176,0.857143,0.619048,0.846154,0.866667,0.55,0.933333,0.785714,1,1,0.636364,1,1,1,0.933333,0.928571,0.705882,0.866667,0.875,0.941176,0.928571,0.933333,1,0.909091,0.833333,0.882353,0.928571,0.882353,0.777778,0.789474,0.736842,0.545455,0.928571]
predictive_accuracy
0.818125
prior_entropy
6.643856189774611
recall
0.818125 [0.6875,0.9375,1,1,0.9375,0.75,0.9375,1,0.875,0.9375,0.8125,1,0.9375,0.5625,1,0.9375,1,0.375,0.3125,0.3125,0.75,0.9375,0.75,1,0.875,0.25,0.4375,0.875,0.875,0.9375,1,1,0.9375,0.625,0.8125,0.9375,0.625,0.375,1,1,0.8125,0.9375,1,0.9375,0.9375,0.9375,0.9375,0.8125,0.875,0.8125,0.75,0.75,0.875,0.625,0.8125,0.1875,1,1,0.625,0.8125,1,1,0.8125,0.9375,1,0.625,0.375,1,0.75,0.8125,0.6875,0.8125,0.6875,0.875,0.6875,0.9375,0.9375,0.4375,1,0.9375,0.8125,0.875,0.8125,0.75,0.8125,0.875,1,0.8125,0.875,1,0.625,0.9375,0.9375,0.8125,0.9375,0.875,0.9375,0.875,0.375,0.8125]
relative_absolute_error
0.18371212121211972
root_mean_prior_squared_error
0.09949874371066209
root_mean_squared_error
0.06031169040907391
root_relative_squared_error
0.6061552956332555
total_cost
0
area_under_roc_curve
0.9054016399968156 [0.993711,0.75,1,1,1,1,1,1,1,1,0.75,1,1,0.5,1,1,1,0.5,0.496835,0.987421,0.996855,1,1,1,1,0.746835,0.75,0.996835,1,0.5,1,1,0.746835,0.496835,0.75,0.996855,0.996855,0.996855,1,1,1,1,1,1,1,1,1,0.996855,1,0.75,1,1,1,0.75,0.996855,0.496855,1,1,1,1,1,0.996855,1,1,1,0.996835,0.5,1,1,0.496855,0.75,1,0.996835,1,0.996855,1,0.75,0.75,1,1,1,1,1,1,1,0.75,1,1,0.75,1,0.746835,1,1,0.75,1,0.743671,0.996855,0.993671,0.746835,1]
area_under_roc_curve
0.921085104689117 [1,1,1,1,1,1,0.75,1,1,1,0.75,1,1,0.75,1,1,1,0.746835,0.75,0.496855,1,1,0.996855,1,1,0.496835,0.496835,1,1,1,1,1,1,1,1,0.996855,0.996855,0.496855,0.996855,1,1,1,1,0.996835,1,1,1,1,0.996835,1,1,1,1,1,1,0.493711,1,1,1,0.75,1,1,0.996835,1,1,0.75,0.996835,1,0.5,1,0.746835,1,0.75,0.75,1,1,1,0.990506,1,0.75,0.75,1,0.996855,1,0.746835,1,1,1,0.75,1,0.75,1,1,1,0.996835,1,1,0.996835,0.746835,0.496855]
area_under_roc_curve
0.9179205477270915 [1,1,1,1,1,0.996835,1,1,1,1,1,1,1,0.75,1,1,1,0.743671,1,0.493671,0.5,1,0.75,1,1,0.743671,0.746835,1,1,1,1,1,1,0.5,0.996855,0.996855,0.990566,0.5,1,1,0.5,1,1,1,1,1,1,1,0.75,1,1,1,1,1,1,0.75,1,1,1,0.746835,1,1,0.75,0.5,1,1,0.493671,1,0.996855,0.75,0.746835,0.996835,0.996855,0.996835,1,1,1,0.496835,1,1,1,1,1,1,1,0.996855,1,1,1,1,1,0.996855,1,1,0.996835,1,1,0.75,0.496855,1]
area_under_roc_curve
0.8896186609346388 [0.5,1,1,1,0.75,0.75,1,1,0.746835,1,1,1,1,0.75,1,1,1,0.746835,0.493711,0.496835,0.5,1,0.993671,1,0.5,0.75,0.740506,1,1,1,1,1,1,0.75,0.996855,0.996855,0.993711,0.493711,1,1,0.996835,0.993711,1,1,1,1,1,1,0.996835,1,1,1,0.996855,0.5,1,0.496835,1,1,0.996855,1,0.996855,1,0.996835,1,1,0.5,0.746835,1,1,0.993671,0.5,0.75,0.490566,0.75,1,1,1,0.75,1,1,1,1,0.75,0.75,1,1,1,1,1,1,0.75,1,0.996855,1,1,0.996855,0.75,0.996835,0.496855,0.75]
area_under_roc_curve
0.8957487461189393 [0.75,1,1,1,1,1,1,1,1,1,1,1,0.5,0.496855,1,0.996835,1,0.496835,0.996855,0.740506,0.996835,1,0.5,1,1,0.746835,0.743671,1,1,1,0.996855,1,1,0.746835,1,1,0.746835,0.746835,1,1,0.993671,1,1,0.5,1,1,1,1,1,1,0.493711,0.496855,0.75,0.496855,0.743671,0.496835,1,0.996835,0.5,1,1,1,1,1,1,1,0.496855,1,0.75,0.743671,1,1,1,1,0.75,1,1,0.75,1,1,1,1,0.75,0.993671,0.996855,1,1,1,1,1,1,0.75,1,0.5,0.75,1,0.993671,1,0.5,1]
area_under_roc_curve
0.8957686489929143 [0.75,1,1,1,1,0.75,1,1,0.996855,0.75,0.75,0.996835,1,1,1,1,1,0.743671,0.496855,0.743671,1,0.75,0.996835,1,0.996835,0.490506,0.743671,0.5,1,1,1,1,0.996835,0.996835,1,0.75,0.75,0.496835,1,1,0.996835,1,1,0.996855,1,1,1,0.75,0.746835,0.75,1,1,1,1,0.996835,0.496835,1,1,0.75,0.996855,1,1,0.493711,1,1,0.75,0.996855,1,1,1,1,0.746835,1,1,0.75,1,1,0.75,1,1,0.5,0.75,1,0.996835,0.5,1,1,0.996855,0.996835,1,0.5,0.996835,1,1,1,1,1,0.996855,0.496855,0.75]
area_under_roc_curve
0.8989929145768649 [0.996835,1,1,1,1,0.5,1,1,0.993711,1,0.996855,0.996855,1,1,1,0.75,1,1,0.490506,0.5,0.746835,1,1,1,1,0.5,0.487421,0.746835,1,1,0.996835,1,1,0.993711,1,1,0.493671,0.746835,0.996835,1,0.996835,0.75,1,1,0.5,0.75,0.75,0.75,0.996855,1,0.5,1,1,1,0.75,0.5,1,1,0.5,0.996855,0.993671,1,0.996855,0.996835,1,0.5,0.5,1,1,1,1,1,0.996835,1,0.996835,1,1,0.5,1,1,1,1,1,0.996835,1,1,1,0.5,1,1,1,1,0.746835,1,1,1,1,1,0.5,1]
area_under_roc_curve
0.9116511424249658 [0.75,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.743671,0.496835,0.746835,1,0.75,1,0.75,0.496855,0.996855,0.996835,0.5,1,1,1,0.996855,1,0.75,1,0.993671,0.75,1,0.996855,1,1,1,1,1,0.996835,1,0.75,0.993711,0.5,0.496855,0.75,0.75,0.996855,1,0.743671,1,1,0.996835,0.993711,1,1,1,1,1,0.490566,0.5,1,1,0.996835,1,1,0.996835,1,0.996835,1,1,0.5,1,1,0.75,1,0.75,0.75,0.75,0.75,1,0.5,1,1,0.5,1,1,1,1,0.996835,1,1,0.75,1]
area_under_roc_curve
0.9337234296632433 [0.996855,1,1,1,1,0.996855,1,1,0.75,1,1,0.996855,1,1,1,1,1,0.496855,0.75,0.990566,1,1,1,1,1,0.5,1,1,1,1,1,1,1,0.996855,1,1,0.743671,0.496835,1,1,0.5,1,1,1,1,0.996835,1,1,0.996855,1,1,0.75,1,0.75,0.75,0.5,1,1,0.996835,1,1,1,0.996835,0.996835,1,1,0.993671,1,0.746835,1,1,0.5,0.746835,1,0.75,1,1,0.5,1,1,1,1,1,0.5,1,1,1,1,1,1,0.75,1,1,0.996835,1,0.75,1,1,0.75,1]
area_under_roc_curve
0.9117506567948412 [1,1,1,1,1,1,1,0.996855,1,1,0.996855,1,1,0.75,1,1,1,0.496855,0.5,0.990566,1,1,1,1,1,0.5,0.5,1,0.75,1,1,1,1,0.996855,0.75,0.996835,0.746835,1,1,1,1,1,1,0.996835,1,1,1,1,0.996855,0.996855,0.75,0.75,1,0.75,1,0.996855,1,1,0.75,0.746835,1,1,0.746835,1,0.996855,0.996855,0.496835,0.996855,0.75,0.993711,1,1,0.496835,1,0.5,0.75,1,1,1,1,1,0.496855,1,0.496855,1,0.996835,0.996835,0.75,1,1,1,0.996835,1,0.75,1,1,0.996855,0.75,1,1]
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
0.8105313018078472
kappa
0.8420533070088845
kappa
0.8357419252941641
kappa
0.7789444597955236
kappa
0.7914691943127962
kappa
0.7914938988271532
kappa
0.7978282329713722
kappa
0.8230927183699257
kappa
0.8673090593160098
kappa
0.8231555678364189
kb_relative_information_score
0.8120907994935211
kb_relative_information_score
0.8434089995779346
kb_relative_information_score
0.8371453595610518
kb_relative_information_score
0.7807725994091079
kb_relative_information_score
0.7932998794428733
kb_relative_information_score
0.7932998794428733
kb_relative_information_score
0.7995635194597558
kb_relative_information_score
0.8246180795272865
kb_relative_information_score
0.8684635596454652
kb_relative_information_score
0.8246180795272865
mean_absolute_error
0.003750000000000001
mean_absolute_error
0.0031250000000000006
mean_absolute_error
0.0032500000000000007
mean_absolute_error
0.004375000000000002
mean_absolute_error
0.004125000000000002
mean_absolute_error
0.004125000000000002
mean_absolute_error
0.004000000000000002
mean_absolute_error
0.003500000000000001
mean_absolute_error
0.0026250000000000006
mean_absolute_error
0.003500000000000001
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
0.8125
predictive_accuracy
0.84375
predictive_accuracy
0.8375
predictive_accuracy
0.78125
predictive_accuracy
0.79375
predictive_accuracy
0.79375
predictive_accuracy
0.8
predictive_accuracy
0.825
predictive_accuracy
0.86875
predictive_accuracy
0.825
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
0.8125 [1,0.5,1,1,1,1,1,1,1,1,0.5,1,1,0,1,1,1,0,0,1,1,1,1,1,1,0.5,0.5,1,1,0,1,1,0.5,0,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0.5,1,0,1,1,1,1,1,1,1,1,1,1,0,1,1,0,0.5,1,1,1,1,1,0.5,0.5,1,1,1,1,1,1,1,0.5,1,1,0.5,1,0.5,1,1,0.5,1,0.5,1,1,0.5,1]
recall
0.84375 [1,1,1,1,1,1,0.5,1,1,1,0.5,1,1,0.5,1,1,1,0.5,0.5,0,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,0.5,1,1,1,1,1,0.5,1,1,0,1,0.5,1,0.5,0.5,1,1,1,1,1,0.5,0.5,1,1,1,0.5,1,1,1,0.5,1,0.5,1,1,1,1,1,1,1,0.5,0]
recall
0.8375 [1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0.5,1,0,0,1,0.5,1,1,0.5,0.5,1,1,1,1,1,1,0,1,1,1,0,1,1,0,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,0.5,1,1,1,0.5,1,1,0.5,0,1,1,0,1,1,0.5,0.5,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,0,1]
recall
0.78125 [0,1,1,1,0.5,0.5,1,1,0.5,1,1,1,1,0.5,1,1,1,0.5,0,0,0,1,1,1,0,0.5,0.5,1,1,1,1,1,1,0.5,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,1,1,1,1,1,1,1,1,1,0,0.5,1,1,1,0,0.5,0,0.5,1,1,1,0.5,1,1,1,1,0.5,0.5,1,1,1,1,1,1,0.5,1,1,1,1,1,0.5,1,0,0.5]
recall
0.79375 [0.5,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,0,1,0.5,1,1,0,1,1,0.5,0.5,1,1,1,1,1,1,0.5,1,1,0.5,0.5,1,1,1,1,1,0,1,1,1,1,1,1,0,0,0.5,0,0.5,0,1,1,0,1,1,1,1,1,1,1,0,1,0.5,0.5,1,1,1,1,0.5,1,1,0.5,1,1,1,1,0.5,1,1,1,1,1,1,1,1,0.5,1,0,0.5,1,1,1,0,1]
recall
0.79375 [0.5,1,1,1,1,0.5,1,1,1,0.5,0.5,1,1,1,1,1,1,0.5,0,0.5,1,0.5,1,1,1,0,0.5,0,1,1,1,1,1,1,1,0.5,0.5,0,1,1,1,1,1,1,1,1,1,0.5,0.5,0.5,1,1,1,1,1,0,1,1,0.5,1,1,1,0,1,1,0.5,1,1,1,1,1,0.5,1,1,0.5,1,1,0.5,1,1,0,0.5,1,1,0,1,1,1,1,1,0,1,1,1,1,1,1,1,0,0.5]
recall
0.8 [1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,0.5,1,1,0,0,0.5,1,1,1,1,0,0,0.5,1,1,1,1,1,1,1,1,0,0.5,1,1,1,0.5,1,1,0,0.5,0.5,0.5,1,1,0,1,1,1,0.5,0,1,1,0,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,0,1,1,1,1,0.5,1,1,1,1,1,0,1]
recall
0.825 [0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,0,0.5,1,0.5,1,0.5,0,1,1,0,1,1,1,1,1,0.5,1,1,0.5,1,1,1,1,1,1,1,1,1,0.5,1,0,0,0.5,0.5,1,1,0.5,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,0,1,1,0.5,1,0.5,0.5,0.5,0.5,1,0,1,1,0,1,1,1,1,1,1,1,0.5,1]
recall
0.86875 [1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,0,0.5,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,0.5,0,1,1,0,1,1,1,1,1,1,1,1,1,1,0.5,1,0.5,0.5,0,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,0,0.5,1,0.5,1,1,0,1,1,1,1,1,0,1,1,1,1,1,1,0.5,1,1,1,1,0.5,1,1,0.5,1]
recall
0.825 [1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0,0,1,1,1,1,1,1,0,0,1,0.5,1,1,1,1,1,0.5,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,0.5,1,0.5,1,1,1,1,0.5,0.5,1,1,0.5,1,1,1,0,1,0.5,1,1,1,0,1,0,0.5,1,1,1,1,1,0,1,0,1,1,1,0.5,1,1,1,1,1,0.5,1,1,1,0.5,1,1]
relative_absolute_error
0.18939393939393911
relative_absolute_error
0.1578282828282826
relative_absolute_error
0.1641414141414139
relative_absolute_error
0.2209595959595957
relative_absolute_error
0.20833333333333307
relative_absolute_error
0.20833333333333307
relative_absolute_error
0.2020202020202018
relative_absolute_error
0.17676767676767655
relative_absolute_error
0.13257575757575737
relative_absolute_error
0.17676767676767655
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
0.061237243569579464
root_mean_squared_error
0.05590169943749475
root_mean_squared_error
0.0570087712549569
root_mean_squared_error
0.06614378277661478
root_mean_squared_error
0.06422616289332567
root_mean_squared_error
0.06422616289332567
root_mean_squared_error
0.0632455532033676
root_mean_squared_error
0.05916079783099617
root_mean_squared_error
0.051234753829797995
root_mean_squared_error
0.05916079783099617
root_relative_squared_error
0.6154574548966634
root_relative_squared_error
0.5618332187193681
root_relative_squared_error
0.5729597091269403
root_relative_squared_error
0.6647700293478879
root_relative_squared_error
0.6454972243679026
root_relative_squared_error
0.6454972243679026
root_relative_squared_error
0.6356417261637279
root_relative_squared_error
0.5945883900105629
root_relative_squared_error
0.5149286505444369
root_relative_squared_error
0.5945883900105629
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
316.9303970000783
usercpu_time_millis
319.55009599982986
usercpu_time_millis
320.73728499995013
usercpu_time_millis
329.9005110000053
usercpu_time_millis
321.4047080000455
usercpu_time_millis
320.33525800011375
usercpu_time_millis
320.32619800020257
usercpu_time_millis
327.1978980001222
usercpu_time_millis
327.81223599999976
usercpu_time_millis
324.2858939997859
usercpu_time_millis_testing
62.75619500001994
usercpu_time_millis_testing
63.564482999936445
usercpu_time_millis_testing
63.083825999910914
usercpu_time_millis_testing
64.35807499997281
usercpu_time_millis_testing
63.12459400010084
usercpu_time_millis_testing
62.91120200012301
usercpu_time_millis_testing
63.53934000003392
usercpu_time_millis_testing
64.43978600009359
usercpu_time_millis_testing
63.24668299998848
usercpu_time_millis_testing
63.06385599987152
usercpu_time_millis_training
254.17420200005836
usercpu_time_millis_training
255.98561299989342
usercpu_time_millis_training
257.6534590000392
usercpu_time_millis_training
265.54243600003247
usercpu_time_millis_training
258.28011399994466
usercpu_time_millis_training
257.42405599999074
usercpu_time_millis_training
256.78685800016865
usercpu_time_millis_training
262.75811200002863
usercpu_time_millis_training
264.5655530000113
usercpu_time_millis_training
261.2220379999144
wall_clock_time_millis
316.91932678222656
wall_clock_time_millis
319.5490837097168
wall_clock_time_millis
320.7263946533203
wall_clock_time_millis
329.95128631591797
wall_clock_time_millis
321.40445709228516
wall_clock_time_millis
320.3318119049072
wall_clock_time_millis
320.3110694885254
wall_clock_time_millis
327.2106647491455
wall_clock_time_millis
327.8036117553711
wall_clock_time_millis
324.293851852417
wall_clock_time_millis_testing
62.7591609954834
wall_clock_time_millis_testing
63.567161560058594
wall_clock_time_millis_testing
63.086748123168945
wall_clock_time_millis_testing
64.37349319458008
wall_clock_time_millis_testing
63.12704086303711
wall_clock_time_millis_testing
62.912940979003906
wall_clock_time_millis_testing
63.54022026062012
wall_clock_time_millis_testing
64.44430351257324
wall_clock_time_millis_testing
63.251495361328125
wall_clock_time_millis_testing
63.08746337890625
wall_clock_time_millis_training
254.16016578674316
wall_clock_time_millis_training
255.9819221496582
wall_clock_time_millis_training
257.63964653015137
wall_clock_time_millis_training
265.5777931213379
wall_clock_time_millis_training
258.27741622924805
wall_clock_time_millis_training
257.4188709259033
wall_clock_time_millis_training
256.7708492279053
wall_clock_time_millis_training
262.76636123657227
wall_clock_time_millis_training
264.55211639404297
wall_clock_time_millis_training
261.20638847351074