10407834
1
Jan van Rijn
9954
Supervised Classification
16360
sklearn.svm.classes.SVC(32)
8245600
C
12.019104437263115
16360
cache_size
200
16360
class_weight
null
16360
coef0
0.0
16360
decision_function_shape
"ovr"
16360
degree
3
16360
gamma
0.0012787192456513489
16360
kernel
"rbf"
16360
max_iter
-1
16360
probability
false
16360
random_state
61752
16360
shrinking
true
16360
tol
0.0013381364776816477
16360
verbose
false
16360
openml-python
Sklearn_0.21.2.
1491
one-hundred-plants-margin
https://www.openml.org/data/download/1592283/phpCsX3fx
-1
21737456
description
https://api.openml.org/data/download/21737456/description.xml
-1
21737457
predictions
https://api.openml.org/data/download/21737457/predictions.arff
area_under_roc_curve
0.596906565656566 [0.554293,0.617109,0.624369,0.624369,0.622475,0.620581,0.624053,0.619318,0.560922,0.625,0.58649,0.620581,0.621528,0.561553,0.623422,0.620581,0.625,0.520202,0.578598,0.557449,0.530934,0.53125,0.588068,0.622159,0.5625,0.498106,0.555871,0.590278,0.623106,0.5625,0.623106,0.5625,0.621843,0.619634,0.610164,0.621528,0.619003,0.553977,0.621212,0.623737,0.587121,0.618056,0.624369,0.621843,0.589646,0.622475,0.622475,0.621212,0.618371,0.585859,0.559659,0.589331,0.619318,0.591225,0.620265,0.527146,0.624684,0.586806,0.584912,0.621528,0.62279,0.592803,0.618371,0.56029,0.619003,0.586806,0.554924,0.623737,0.590278,0.585859,0.593119,0.592803,0.619318,0.592487,0.557134,0.620581,0.621528,0.620896,0.623737,0.62279,0.529356,0.590909,0.620265,0.590593,0.621212,0.619949,0.624369,0.557134,0.593119,0.616162,0.52904,0.624684,0.621843,0.613636,0.615215,0.623106,0.616162,0.559343,0.498106,0.621528]
average_cost
0
f_measure
0.21543417525862044 [0.090909,0.177778,0.363636,0.363636,0.285714,0.235294,0.347826,0.210526,0.173913,0.4,0.142857,0.235294,0.258065,0.190476,0.32,0.235294,0.4,0.038462,0.089552,0.117647,0.111111,0.117647,0.162162,0.275862,0.222222,0,0.102564,0.2,0.307692,0.222222,0.307692,0.222222,0.266667,0.216216,0.119403,0.258065,0.205128,0.088889,0.25,0.333333,0.15,0.190476,0.363636,0.266667,0.1875,0.285714,0.285714,0.25,0.195122,0.136364,0.148148,0.181818,0.210526,0.222222,0.228571,0.066667,0.380952,0.146341,0.12766,0.258065,0.296296,0.272727,0.195122,0.16,0.205128,0.146341,0.095238,0.333333,0.2,0.136364,0.285714,0.272727,0.210526,0.26087,0.114286,0.235294,0.258065,0.242424,0.333333,0.296296,0.086957,0.214286,0.228571,0.206897,0.25,0.222222,0.363636,0.114286,0.285714,0.166667,0.083333,0.380952,0.266667,0.142857,0.156863,0.307692,0.166667,0.142857,0,0.258065]
kappa
0.1938131313131313
kb_relative_information_score
0.20013316984408963
mean_absolute_error
0.015962499999999716
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
0.3085859875122658 [0.071429,0.137931,0.666667,0.666667,0.333333,0.222222,0.571429,0.181818,0.285714,1,0.115385,0.222222,0.266667,0.4,0.444444,0.222222,1,0.027778,0.058824,0.111111,0.5,1,0.142857,0.307692,1,0,0.086957,0.214286,0.4,1,0.4,1,0.285714,0.190476,0.078431,0.266667,0.173913,0.068966,0.25,0.5,0.125,0.153846,0.666667,0.285714,0.1875,0.333333,0.333333,0.25,0.16,0.107143,0.181818,0.176471,0.181818,0.272727,0.210526,0.071429,0.8,0.12,0.096774,0.266667,0.363636,0.5,0.16,0.222222,0.173913,0.12,0.076923,0.5,0.214286,0.107143,0.6,0.5,0.181818,0.428571,0.105263,0.222222,0.266667,0.235294,0.5,0.363636,0.142857,0.25,0.210526,0.230769,0.25,0.2,0.666667,0.105263,0.6,0.125,0.125,0.8,0.285714,0.1,0.114286,0.4,0.125,0.166667,0,0.266667]
predictive_accuracy
0.201875
prior_entropy
6.643856189774611
recall
0.201875 [0.125,0.25,0.25,0.25,0.25,0.25,0.25,0.25,0.125,0.25,0.1875,0.25,0.25,0.125,0.25,0.25,0.25,0.0625,0.1875,0.125,0.0625,0.0625,0.1875,0.25,0.125,0,0.125,0.1875,0.25,0.125,0.25,0.125,0.25,0.25,0.25,0.25,0.25,0.125,0.25,0.25,0.1875,0.25,0.25,0.25,0.1875,0.25,0.25,0.25,0.25,0.1875,0.125,0.1875,0.25,0.1875,0.25,0.0625,0.25,0.1875,0.1875,0.25,0.25,0.1875,0.25,0.125,0.25,0.1875,0.125,0.25,0.1875,0.1875,0.1875,0.1875,0.25,0.1875,0.125,0.25,0.25,0.25,0.25,0.25,0.0625,0.1875,0.25,0.1875,0.25,0.25,0.25,0.125,0.1875,0.25,0.0625,0.25,0.25,0.25,0.25,0.25,0.25,0.125,0,0.25]
relative_absolute_error
0.8061868686868529
root_mean_prior_squared_error
0.09949874371066209
root_mean_squared_error
0.12634278768493165
root_relative_squared_error
1.2697927930862207
total_cost
0
area_under_roc_curve
0.5943396226415091 [0.481132,0.5,0.5,1,0.5,0.984277,0.5,0.990566,0.5,1,0.5,0.5,0.5,0.5,0.5,0.996855,0.5,0.5,0.5,0.977987,0.496855,0.5,0.974843,0.993711,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.984277,0.996855,0.987421,0.990566,0.5,0.974843,0.987421,0.5,0.5,0.5,0.5,0.993711,0.993711,0.5,0.5,0.5,0.5,0.987421,0.5,0.993711,0.490566,0.5,0.965409,0.493711,0.5,0.993711,0.993711,0.5,0.5,0.984277,0.5,0.5,0.993711,0.990566,0.477987,0.5,0.993711,0.5,0.5,0.481132,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.993711,0.993711,0.5,0.5,0.5,0.5,0.5,0.987421,0.5,1,0.5,0.5,0.5,0.5,0.984277,0.5,0.5,0.990566]
area_under_roc_curve
0.6069182389937106 [0.965409,0.5,0.5,1,0.5,0.993711,0.5,0.981132,0.5,1,0.5,0.5,0.5,0.5,0.5,0.993711,0.5,0.5,0.5,0.987421,1,0.5,0.481132,0.993711,1,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.990566,0.993711,0.984277,0.990566,0.5,0.981132,0.981132,0.5,0.5,0.5,0.5,1,0.987421,0.5,0.5,0.5,0.5,0.974843,0.5,0.996855,0.487421,0.5,0.971698,0.987421,0.5,0.996855,0.996855,0.5,0.5,0.990566,0.5,0.5,0.996855,0.490566,0.987421,0.5,0.996855,0.5,0.5,0.493711,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.984277,0.990566,0.5,0.5,0.5,0.5,0.5,0.981132,0.5,1,0.5,0.5,0.5,0.5,0.990566,0.5,0.5,0.987421]
area_under_roc_curve
0.5974842767295596 [0.5,0.5,0.5,0.996855,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.987421,0.5,0.5,0.5,0.5,0.5,0.484277,0.5,0.5,0.5,0.5,0.987421,1,0.5,0.5,0.990566,0.5,0.5,1,0.5,0.5,0.5,0.959119,0.996855,0.971698,0.468553,0.990566,0.5,0.5,0.984277,1,0.977987,0.5,0.990566,0.5,0.990566,0.5,0.5,0.5,0.993711,0.990566,0.5,0.981132,0.5,1,0.5,0.962264,0.5,0.996855,0.5,0.5,0.487421,0.5,0.5,0.5,0.5,0.990566,0.5,0.5,0.5,0.981132,0.5,0.984277,0.5,0.5,0.5,0.5,0.5,0.496855,0.5,0.5,0.5,0.996855,0.990566,0.996855,0.5,0.5,0.977987,0.5,0.996855,1,0.5,0.5,1,0.5,0.5,0.496855,0.5]
area_under_roc_curve
0.6069182389937104 [0.5,0.5,0.5,0.996855,0.5,0.5,0.996855,0.5,0.5,0.5,0.5,0.5,0.993711,0.5,0.5,0.5,0.5,0.5,0.987421,0.5,0.5,1,0.5,0.996855,0.5,0.5,0.5,0.987421,0.5,0.5,0.996855,0.5,0.5,0.5,0.974843,0.993711,0.977987,0.474843,0.990566,0.5,0.5,0.977987,0.996855,0.993711,0.5,0.990566,0.5,0.990566,0.5,0.5,0.5,0.990566,0.990566,0.5,0.981132,0.5,1,0.5,0.968553,0.5,0.990566,1,0.5,0.5,0.5,0.5,0.5,0.5,0.993711,0.5,0.5,0.5,0.984277,0.5,0.987421,0.5,0.5,0.5,0.5,0.5,0.993711,0.5,0.5,0.5,0.987421,0.984277,1,0.5,0.5,0.965409,0.5,1,0.993711,0.5,0.5,0.987421,0.5,0.5,0.490566,0.5]
area_under_roc_curve
0.5911949685534589 [0.5,0.987421,0.5,0.5,0.990566,0.5,0.996855,0.5,0.496855,0.5,0.5,0.5,0.993711,0.496855,0.993711,0.5,0.5,0.5,0.930818,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.993711,0.996855,0.5,0.990566,0.5,0.5,0.5,0.965409,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,1,0.987421,0.996855,0.5,0.5,0.5,0.5,0.5,0.490566,0.5,0.490566,0.5,0.5,0.996855,0.5,0.5,0.987421,0.5,0.5,0.971698,0.996855,0.5,0.5,0.471698,0.5,0.5,0.5,0.5,0.5,0.987421,0.996855,0.5,0.996855,0.5,0.5,0.5,0.993711,0.493711,0.5,0.5,0.5,0.987421,0.993711,0.996855,0.987421,0.5,0.5,0.493711,0.5,0.981132,0.977987,0.5,0.996855,0.5,0.984277,0.5,0.5]
area_under_roc_curve
0.60377358490566 [0.5,0.987421,0.5,0.5,0.993711,0.5,0.996855,0.5,1,0.5,0.5,0.5,0.990566,0.493711,0.996855,0.5,0.5,0.5,0.946541,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.493711,1,0.5,0.993711,1,0.5,0.5,0.95283,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.996855,0.996855,0.987421,0.996855,0.5,0.5,0.5,0.5,1,0.981132,0.5,0.993711,0.5,0.5,1,0.5,0.5,0.993711,0.5,0.5,0.977987,0.993711,0.5,0.5,0.965409,0.5,0.5,0.5,0.5,0.5,0.990566,0.490566,0.5,0.990566,0.5,0.5,0.5,0.993711,0.496855,0.5,0.5,0.5,0.990566,0.981132,1,0.990566,0.5,0.5,0.490566,0.5,0.993711,0.984277,0.5,0.996855,0.5,0.990566,0.493711,0.5]
area_under_roc_curve
0.5943396226415094 [0.5,0.974843,1,0.5,0.996855,0.5,0.5,0.5,0.993711,0.5,0.987421,0.984277,0.5,1,0.996855,0.5,1,0.974843,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.493711,0.468553,0.5,0.993711,0.5,0.5,0.5,0.990566,0.981132,0.5,0.5,0.5,0.5,0.5,0.990566,0.5,0.5,0.5,0.5,0.493711,0.5,0.5,0.5,0.981132,0.987421,0.490566,0.5,0.5,0.993711,0.5,0.5,0.5,0.5,0.5,0.990566,0.5,0.5,0.990566,0.5,0.5,0.971698,0.493711,0.5,0.5,0.5,1,0.5,0.5,1,0.5,0.984277,0.990566,0.990566,1,0.996855,0.5,0.990566,0.5,0.5,0.5,0.5,0.5,0.484277,0.5,0.5,1,0.5,0.5,0.959119,0.981132,0.5,0.5,0.496855,0.5,0.5]
area_under_roc_curve
0.5943396226415093 [0.5,0.971698,1,0.5,0.993711,0.5,0.5,0.5,0.493711,0.5,0.484277,0.990566,0.5,1,0.996855,0.5,1,0.459119,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.493711,0.993711,0.5,0.990566,0.5,0.5,1,0.990566,0.990566,0.5,0.5,0.5,0.5,0.5,0.996855,0.5,0.5,0.5,0.5,0.990566,0.5,0.5,0.5,0.987421,0.484277,0.981132,0.5,0.5,0.996855,0.5,0.5,0.5,0.5,0.5,0.993711,0.5,0.5,0.993711,0.5,0.5,0.471698,0.993711,0.5,0.5,0.5,0.996855,0.5,0.5,1,0.5,0.984277,0.987421,0.981132,1,0.993711,0.5,0.993711,0.5,0.5,0.5,0.5,0.5,0.484277,1,0.5,0.493711,0.5,0.5,0.965409,0.977987,0.5,0.5,0.496855,0.5,0.5]
area_under_roc_curve
0.5974842767295596 [0.477987,0.5,1,0.5,0.5,0.987421,0.5,0.990566,0.5,1,0.974843,0.981132,0.5,0.5,0.5,0.984277,1,0.481132,0.5,0.487421,0.5,0.5,0.993711,0.5,0.5,0.5,0.987421,0.5,0.5,1,0.5,0.5,0.993711,0.987421,0.5,0.5,0.5,0.5,0.5,1,0.493711,0.5,0.5,0.5,0.5,0.5,0.990566,0.5,0.981132,0.974843,0.5,0.5,0.5,0.5,0.5,0.490566,0.5,0.496855,0.5,0.5,0.5,0.5,0.5,0.5,0.987421,0.993711,0.5,1,0.5,0.977987,0.996855,0.5,0.5,0.5,0.5,0.5,0.996855,0.993711,0.993711,0.5,0.5,0.993711,0.990566,0.990566,0.5,0.5,0.5,0.5,0.993711,0.5,0.5,0.5,0.5,0.5,0.965409,0.5,0.971698,0.5,0.5,0.996855]
area_under_roc_curve
0.5974842767295595 [0.993711,0.5,0.993711,0.5,0.5,0.990566,0.5,0.981132,0.5,1,0.981132,1,0.5,0.5,0.5,0.981132,1,0.474843,0.5,0.496855,0.5,0.5,0.993711,0.5,0.5,0.493711,0.484277,0.5,0.5,0.5,0.5,0.5,0.993711,0.987421,0.5,0.5,0.5,0.5,0.5,1,0.984277,0.5,0.5,0.5,0.5,0.5,0.990566,0.5,0.984277,0.974843,0.5,0.5,0.5,0.5,0.5,0.990566,0.5,0.996855,0.5,0.5,0.5,0.5,0.5,0.5,0.977987,0.993711,0.5,0.996855,0.5,0.977987,0.5,1,0.5,0.5,0.5,0.5,0.990566,0.993711,0.993711,0.5,0.5,0.493711,0.984277,0.493711,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.977987,0.5,0.965409,0.5,0.5,0.990566]
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
0.18867924528301885
kappa
0.21383647798742136
kappa
0.1949685534591195
kappa
0.21383647798742136
kappa
0.18238993710691823
kappa
0.20754716981132074
kappa
0.18867924528301885
kappa
0.18867924528301885
kappa
0.1949685534591195
kappa
0.1949685534591195
kb_relative_information_score
0.19199043782213684
kb_relative_information_score
0.21704499788966752
kb_relative_information_score
0.19825407783901952
kb_relative_information_score
0.21704499788966752
kb_relative_information_score
0.1857267978052542
kb_relative_information_score
0.21078135787278487
kb_relative_information_score
0.19199043782213684
kb_relative_information_score
0.1919904378221369
kb_relative_information_score
0.19825407783901952
kb_relative_information_score
0.19825407783901952
mean_absolute_error
0.01612500000000001
mean_absolute_error
0.01562500000000001
mean_absolute_error
0.01600000000000001
mean_absolute_error
0.01562500000000001
mean_absolute_error
0.01625000000000001
mean_absolute_error
0.01575000000000001
mean_absolute_error
0.01612500000000001
mean_absolute_error
0.01612500000000001
mean_absolute_error
0.01600000000000001
mean_absolute_error
0.01600000000000001
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
0.19375
predictive_accuracy
0.21875
predictive_accuracy
0.2
predictive_accuracy
0.21875
predictive_accuracy
0.1875
predictive_accuracy
0.2125
predictive_accuracy
0.19375
predictive_accuracy
0.19375
predictive_accuracy
0.2
predictive_accuracy
0.2
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
0.19375 [0,0,0,1,0,1,0,1,0,1,0,0,0,0,0,1,0,0,0,1,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,0,1,1,0,0,0,0,1,1,0,0,0,0,1,0,1,0,0,1,0,0,1,1,0,0,1,0,0,1,1,0,0,1,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,1,0,1,0,0,0,0,1,0,0,1]
recall
0.21875 [1,0,0,1,0,1,0,1,0,1,0,0,0,0,0,1,0,0,0,1,1,0,0,1,1,0,0,0,0,1,0,0,0,0,0,1,1,1,1,0,1,1,0,0,0,0,1,1,0,0,0,0,1,0,1,0,0,1,1,0,1,1,0,0,1,0,0,1,0,1,0,1,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,1,0,1,0,0,0,0,1,0,0,1]
recall
0.2 [0,0,0,1,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,1,1,0,0,1,0,0,1,0,0,0,1,1,1,0,1,0,0,1,1,1,0,1,0,1,0,0,0,1,1,0,1,0,1,0,1,0,1,0,0,0,0,0,0,0,1,0,0,0,1,0,1,0,0,0,0,0,0,0,0,0,1,1,1,0,0,1,0,1,1,0,0,1,0,0,0,0]
recall
0.21875 [0,0,0,1,0,0,1,0,0,0,0,0,1,0,0,0,0,0,1,0,0,1,0,1,0,0,0,1,0,0,1,0,0,0,1,1,1,0,1,0,0,1,1,1,0,1,0,1,0,0,0,1,1,0,1,0,1,0,1,0,1,1,0,0,0,0,0,0,1,0,0,0,1,0,1,0,0,0,0,0,1,0,0,0,1,1,1,0,0,1,0,1,1,0,0,1,0,0,0,0]
recall
0.1875 [0,1,0,0,1,0,1,0,0,0,0,0,1,0,1,0,0,0,1,0,0,0,0,0,0,0,0,1,1,0,1,0,0,0,1,0,0,0,0,0,0,0,1,1,1,1,0,0,0,0,0,0,0,0,0,0,1,0,0,1,0,0,1,1,0,0,0,0,0,0,0,0,1,1,0,1,0,0,0,1,0,0,0,0,1,1,1,1,0,0,0,0,1,1,0,1,0,1,0,0]
recall
0.2125 [0,1,0,0,1,0,1,0,1,0,0,0,1,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,1,0,1,1,0,0,1,0,0,0,0,0,0,0,1,1,1,1,0,0,0,0,1,1,0,1,0,0,1,0,0,1,0,0,1,1,0,0,1,0,0,0,0,0,1,0,0,1,0,0,0,1,0,0,0,0,1,1,1,1,0,0,0,0,1,1,0,1,0,1,0,0]
recall
0.19375 [0,1,1,0,1,0,0,0,1,0,1,1,0,1,1,0,1,1,0,0,0,0,0,0,0,0,0,0,1,0,0,0,1,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1,1,0,0,0,1,0,0,0,0,0,1,0,0,1,0,0,1,0,0,0,0,1,0,0,1,0,1,1,1,1,1,0,1,0,0,0,0,0,0,0,0,1,0,0,1,1,0,0,0,0,0]
recall
0.19375 [0,1,1,0,1,0,0,0,0,0,0,1,0,1,1,0,1,0,0,0,0,0,0,0,0,0,1,0,1,0,0,1,1,1,0,0,0,0,0,1,0,0,0,0,1,0,0,0,1,0,1,0,0,1,0,0,0,0,0,1,0,0,1,0,0,0,1,0,0,0,1,0,0,1,0,1,1,1,1,1,0,1,0,0,0,0,0,0,1,0,0,0,0,1,1,0,0,0,0,0]
recall
0.2 [0,0,1,0,0,1,0,1,0,1,1,1,0,0,0,1,1,0,0,0,0,0,1,0,0,0,1,0,0,1,0,0,1,1,0,0,0,0,0,1,0,0,0,0,0,0,1,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,1,0,1,1,0,0,0,0,0,1,1,1,0,0,1,1,1,0,0,0,0,1,0,0,0,0,0,1,0,1,0,0,1]
recall
0.2 [1,0,1,0,0,1,0,1,0,1,1,1,0,0,0,1,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,1,1,0,0,0,0,0,1,0,1,1,0,0,0,0,0,1,0,1,0,0,0,0,0,0,1,1,0,1,0,1,0,1,0,0,0,0,1,1,1,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,1,0,1,0,0,1]
relative_absolute_error
0.8143939393939387
relative_absolute_error
0.7891414141414134
relative_absolute_error
0.8080808080808072
relative_absolute_error
0.7891414141414134
relative_absolute_error
0.8207070707070698
relative_absolute_error
0.7954545454545446
relative_absolute_error
0.8143939393939387
relative_absolute_error
0.8143939393939387
relative_absolute_error
0.8080808080808072
relative_absolute_error
0.8080808080808072
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
0.12698425099200297
root_mean_squared_error
0.12500000000000003
root_mean_squared_error
0.12649110640673522
root_mean_squared_error
0.12500000000000003
root_mean_squared_error
0.12747548783981966
root_mean_squared_error
0.12549900398011138
root_mean_squared_error
0.12698425099200297
root_mean_squared_error
0.12698425099200297
root_mean_squared_error
0.12649110640673522
root_mean_squared_error
0.12649110640673522
root_relative_squared_error
1.2762397418933003
root_relative_squared_error
1.2562972690740146
root_relative_squared_error
1.271283452327456
root_relative_squared_error
1.2562972690740146
root_relative_squared_error
1.2811768579763452
root_relative_squared_error
1.2613124477737823
root_relative_squared_error
1.2762397418933003
root_relative_squared_error
1.2762397418933003
root_relative_squared_error
1.271283452327456
root_relative_squared_error
1.271283452327456
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
702.4353809997592
usercpu_time_millis
701.9127900002786
usercpu_time_millis
704.9251260000347
usercpu_time_millis
703.3005590001267
usercpu_time_millis
702.3452580001504
usercpu_time_millis
705.2368889999343
usercpu_time_millis
706.1946039998475
usercpu_time_millis
706.9407290000527
usercpu_time_millis
706.5142050000759
usercpu_time_millis
703.2581419998678
usercpu_time_millis_testing
62.67283299985138
usercpu_time_millis_testing
62.509138000223174
usercpu_time_millis_testing
62.73911900007079
usercpu_time_millis_testing
62.775106000117376
usercpu_time_millis_testing
62.664240000231075
usercpu_time_millis_testing
62.61563499992917
usercpu_time_millis_testing
62.71797699992021
usercpu_time_millis_testing
63.17151300027035
usercpu_time_millis_testing
62.616836999950465
usercpu_time_millis_testing
62.443149000046105
usercpu_time_millis_training
639.7625479999078
usercpu_time_millis_training
639.4036520000554
usercpu_time_millis_training
642.1860069999639
usercpu_time_millis_training
640.5254530000093
usercpu_time_millis_training
639.6810179999193
usercpu_time_millis_training
642.6212540000051
usercpu_time_millis_training
643.4766269999272
usercpu_time_millis_training
643.7692159997823
usercpu_time_millis_training
643.8973680001254
usercpu_time_millis_training
640.8149929998217
wall_clock_time_millis
702.4376392364502
wall_clock_time_millis
701.9245624542236
wall_clock_time_millis
704.9374580383301
wall_clock_time_millis
703.3176422119141
wall_clock_time_millis
702.3463249206543
wall_clock_time_millis
705.2402496337891
wall_clock_time_millis
706.1982154846191
wall_clock_time_millis
706.9528102874756
wall_clock_time_millis
706.519365310669
wall_clock_time_millis
703.2644748687744
wall_clock_time_millis_testing
62.677860260009766
wall_clock_time_millis_testing
62.515974044799805
wall_clock_time_millis_testing
62.746286392211914
wall_clock_time_millis_testing
62.78228759765625
wall_clock_time_millis_testing
62.67094612121582
wall_clock_time_millis_testing
62.622785568237305
wall_clock_time_millis_testing
62.72435188293457
wall_clock_time_millis_testing
63.17925453186035
wall_clock_time_millis_testing
62.624454498291016
wall_clock_time_millis_testing
62.44993209838867
wall_clock_time_millis_training
639.7597789764404
wall_clock_time_millis_training
639.4085884094238
wall_clock_time_millis_training
642.1911716461182
wall_clock_time_millis_training
640.5353546142578
wall_clock_time_millis_training
639.6753787994385
wall_clock_time_millis_training
642.6174640655518
wall_clock_time_millis_training
643.4738636016846
wall_clock_time_millis_training
643.7735557556152
wall_clock_time_millis_training
643.8949108123779
wall_clock_time_millis_training
640.8145427703857