10401820
1
Jan van Rijn
9954
Supervised Classification
16360
sklearn.svm.classes.SVC(32)
8239589
C
14157.7694693682
16360
cache_size
200
16360
class_weight
null
16360
coef0
0.3782597505563763
16360
decision_function_shape
"ovr"
16360
degree
3
16360
gamma
0.0012505097632321644
16360
kernel
"sigmoid"
16360
max_iter
-1
16360
probability
false
16360
random_state
51399
16360
shrinking
true
16360
tol
0.009259120484187982
16360
verbose
false
16360
openml-python
Sklearn_0.21.2.
1491
one-hundred-plants-margin
https://www.openml.org/data/download/1592283/phpCsX3fx
-1
21725424
description
https://api.openml.org/data/download/21725424/description.xml
-1
21725426
predictions
https://api.openml.org/data/download/21725426/predictions.arff
area_under_roc_curve
0.8147095959595965 [0.779672,0.714331,1,1,0.905619,0.684028,0.90625,0.999053,0.68529,0.90625,0.842487,0.998106,0.653725,0.624684,1,0.904987,1,0.52399,0.556503,0.557134,0.624053,0.90625,0.77904,1,0.810922,0.62279,0.620896,0.93529,0.937184,0.875,0.999053,0.96875,0.873737,0.808712,0.778409,0.90404,0.618687,0.557449,0.935606,0.96875,0.809659,0.90404,0.999369,0.840278,0.9375,0.873737,0.873737,0.622475,0.93529,0.842487,0.779672,0.779672,0.841225,0.717803,0.841225,0.526515,0.999684,0.968434,0.68529,0.716856,0.966856,0.874369,0.903409,0.874053,0.935606,0.716225,0.555556,1,0.684659,0.746528,0.686869,0.780934,0.715278,0.905303,0.624053,0.905934,0.968119,0.653093,1,0.968434,0.717803,0.936869,0.842172,0.809659,0.81029,0.937184,1,0.654356,0.905619,0.620265,0.717803,0.967172,0.717487,0.652778,0.998422,0.842487,0.618371,0.623106,0.498737,0.873422]
average_cost
0
f_measure
0.6315173328479278 [0.6,0.378378,1,1,0.83871,0.363636,0.896552,0.914286,0.413793,0.896552,0.709677,0.842105,0.344828,0.380952,1,0.787879,1,0.05,0.108108,0.114286,0.347826,0.896552,0.5625,1,0.645161,0.296296,0.242424,0.756757,0.903226,0.857143,0.914286,0.967742,0.75,0.526316,0.529412,0.722222,0.2,0.117647,0.777778,0.967742,0.571429,0.722222,0.941176,0.578947,0.933333,0.75,0.75,0.285714,0.756757,0.709677,0.6,0.6,0.628571,0.538462,0.628571,0.0625,0.969697,0.9375,0.413793,0.482759,0.810811,0.8,0.684211,0.774194,0.777778,0.451613,0.1,1,0.387097,0.457143,0.5,0.692308,0.411765,0.8125,0.347826,0.866667,0.909091,0.322581,1,0.9375,0.538462,0.875,0.6875,0.571429,0.606061,0.903226,1,0.37037,0.83871,0.228571,0.538462,0.833333,0.518519,0.3125,0.864865,0.709677,0.195122,0.307692,0,0.727273]
kappa
0.6294191919191919
kb_relative_information_score
0.6323243310089982
mean_absolute_error
0.007337499999999899
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
0.6474888740688276 [0.642857,0.333333,1,1,0.866667,0.352941,1,0.842105,0.461538,1,0.733333,0.727273,0.384615,0.8,1,0.764706,1,0.041667,0.095238,0.105263,0.571429,1,0.5625,1,0.666667,0.363636,0.235294,0.666667,0.933333,1,0.842105,1,0.75,0.454545,0.5,0.65,0.166667,0.111111,0.7,1,0.526316,0.65,0.888889,0.5,1,0.75,0.75,0.333333,0.666667,0.733333,0.642857,0.642857,0.578947,0.7,0.578947,0.0625,0.941176,0.9375,0.461538,0.538462,0.714286,0.857143,0.590909,0.8,0.7,0.466667,0.083333,1,0.4,0.421053,0.75,0.9,0.388889,0.8125,0.571429,0.928571,0.882353,0.333333,1,0.9375,0.7,0.875,0.6875,0.526316,0.588235,0.933333,1,0.454545,0.866667,0.210526,0.7,0.75,0.636364,0.3125,0.761905,0.733333,0.16,0.4,0,0.705882]
predictive_accuracy
0.633125
prior_entropy
6.643856189774611
recall
0.633125 [0.5625,0.4375,1,1,0.8125,0.375,0.8125,1,0.375,0.8125,0.6875,1,0.3125,0.25,1,0.8125,1,0.0625,0.125,0.125,0.25,0.8125,0.5625,1,0.625,0.25,0.25,0.875,0.875,0.75,1,0.9375,0.75,0.625,0.5625,0.8125,0.25,0.125,0.875,0.9375,0.625,0.8125,1,0.6875,0.875,0.75,0.75,0.25,0.875,0.6875,0.5625,0.5625,0.6875,0.4375,0.6875,0.0625,1,0.9375,0.375,0.4375,0.9375,0.75,0.8125,0.75,0.875,0.4375,0.125,1,0.375,0.5,0.375,0.5625,0.4375,0.8125,0.25,0.8125,0.9375,0.3125,1,0.9375,0.4375,0.875,0.6875,0.625,0.625,0.875,1,0.3125,0.8125,0.25,0.4375,0.9375,0.4375,0.3125,1,0.6875,0.25,0.25,0,0.75]
relative_absolute_error
0.3705808080808023
root_mean_prior_squared_error
0.09949874371066209
root_mean_squared_error
0.08565920849505848
root_relative_squared_error
0.8609074376270682
total_cost
0
area_under_roc_curve
0.8048125149271552 [0.493711,0.5,1,1,1,0.987421,0.75,0.996855,0.5,1,0.75,1,0.5,0.5,1,1,1,0.5,0.5,0.984277,0.5,1,0.993711,1,0.5,0.5,0.75,0.996835,1,0.5,1,1,0.5,0.487342,0.5,0.493711,0.996855,0.987421,0.996855,1,0.996855,0.993711,0.996835,0.996835,1,1,1,0.993711,1,0.746835,1,0.5,0.993711,0.5,0.996855,0.490566,1,1,0.5,1,0.996855,0.993711,1,0.75,1,0.75,0.5,1,0.996855,0.490566,0.75,1,0.996835,1,0.493711,1,0.75,0.5,1,1,0.5,0.996835,1,1,0.75,0.75,1,0.75,0.75,0.990566,0.75,1,0.5,0.5,1,0.496835,0.984277,0.5,0.5,0.996855]
area_under_roc_curve
0.8393440012737837 [1,0.5,1,1,1,0.993711,0.75,0.996855,0.5,1,0.75,1,0.5,0.75,1,0.996855,1,0.5,0.5,0.987421,1,0.5,0.496855,1,1,0.5,0.496835,0.996835,1,1,0.996835,1,0.996835,1,1,0.996855,0.993711,0.993711,0.996855,1,0.996855,0.996855,1,0.996835,0.75,0.75,0.996855,0.990566,0.746835,1,1,0.746835,0.993711,1,1,0.490566,1,1,1,0.75,0.996855,1,0.996835,0.75,0.996855,1,0.5,1,0.493711,0.996855,0.746835,1,1,0.75,0.5,0.746835,1,0.993671,1,0.75,0.5,1,0.996855,1,0.746835,1,1,0.75,0.75,0.990566,0.5,1,0.5,0.5,0.996835,0.75,0.993711,0.5,0.5,0.5]
area_under_roc_curve
0.8110620173553057 [0.5,0.5,1,1,0.75,1,0.5,1,0.996835,1,1,1,0.993711,0.5,1,0.5,1,0.5,0.5,0.490506,0.5,0.5,0.75,1,0.996855,0.75,0.746835,0.996855,1,1,1,1,1,0.5,0.990566,0.996855,0.977987,0.487421,0.996855,0.75,0.496835,0.996855,1,0.987421,1,1,0.75,1,0.75,1,0.5,1,1,0.5,0.990566,0.5,1,1,0.993711,0.5,0.996855,0.5,0.75,0.493711,0.993671,0.5,0.496835,1,0.993711,0.746835,0.5,0.996835,0.990566,1,1,0.75,1,0.496835,1,1,0.996855,1,1,0.5,1,1,1,0.5,0.996835,0.981132,0.75,0.996855,1,0.5,1,1,0.5,0.75,0.496855,1]
area_under_roc_curve
0.8016479579651298 [0.746835,0.746835,1,1,0.75,0.5,1,1,0.746835,0.75,0.75,1,0.996855,0.5,1,1,1,0.5,0.490566,0.496835,0.5,1,0.993671,1,0.493711,0.5,0.496835,0.993711,0.75,1,1,1,0.75,0.75,0.993711,0.996855,0.987421,0.481132,0.996855,1,1,0.990566,1,0.996855,1,0.996855,0.75,0.990566,1,1,0.5,1,0.993711,0.5,1,0.5,1,1,0.993711,0.5,0.996855,1,0.996835,0.5,0.746835,0.5,0.496835,1,0.493711,0.746835,0.5,0.75,0.490566,0.746835,1,1,1,0.5,1,1,1,1,0.75,0.5,0.987421,1,1,0.5,1,0.990566,0.5,1,1,0.5,1,0.996855,0.5,0.75,0.490566,0.75]
area_under_roc_curve
0.804732903431255 [0.75,1,1,1,1,0.5,1,1,0.496855,0.75,1,1,0.993711,0.496855,1,0.996835,1,0.5,0.968553,0.5,0.5,1,0.5,1,0.746835,0.746835,0.5,1,0.996855,0.75,0.996855,0.5,0.75,0.996835,0.996855,1,0.5,0.5,1,1,0.996835,0.5,1,1,1,0.996855,1,0.5,1,0.5,0.5,0.493711,0.5,0.496855,0.743671,0.496835,0.996855,0.996835,0.5,0.993711,1,1,0.996855,1,0.75,0.75,0.477987,1,0.5,0.496835,0.5,0.75,0.993711,1,0.75,1,0.996835,0.5,1,1,0.996855,1,0.5,0.993671,0.993711,1,1,0.996855,1,0.5,0.996855,0.746835,0.990566,0.993711,1,0.996855,0.5,0.993711,0.5,0.996835]
area_under_roc_curve
0.8172518111615317 [0.75,0.990566,1,1,0.996855,0.5,1,1,1,0.75,0.5,1,0.990566,1,1,1,1,0.496835,0.981132,0.5,0.5,0.75,0.746835,1,0.746835,0.743671,0.5,0.5,1,0.75,1,1,0.996835,0.746835,0.993711,0.75,0.496835,0.5,1,1,0.996835,0.75,1,0.996855,1,0.996855,0.996835,0.5,1,0.75,1,0.996855,0.746835,1,0.746835,0.496835,1,1,0.5,0.996855,1,1,0.993711,0.996855,1,0.5,0.971698,1,0.5,0.75,0.75,0.5,0.993711,0.996855,0.75,1,1,0.5,1,1,0.496855,0.75,0.75,0.990506,1,1,1,0.996855,0.996835,0.5,0.496855,0.996835,0.996855,0.996855,1,1,0.5,0.996855,0.5,0.5]
area_under_roc_curve
0.8109824058594057 [1,0.987421,1,1,0.996855,0.5,1,1,0.993711,1,0.996855,0.990566,0.5,0.5,1,1,1,0.990566,0.5,0.5,0.493671,1,0.75,1,0.75,0.496855,0.484277,0.75,1,1,0.996835,1,1,0.993711,0.75,0.996835,0.490506,0.5,0.993671,1,0.746835,1,1,0.5,0.5,0.5,0.5,0.5,0.993711,1,0.993711,1,1,0.996855,0.746835,0.5,1,1,0.5,0.996855,0.993671,1,0.993711,1,1,0.493711,0.496855,1,0.746835,0.75,1,0.75,0.5,1,0.5,1,1,0.493711,1,1,0.75,1,0.996835,0.996835,0.5,1,1,0.493711,0.5,0.5,0.996855,0.996835,0.5,0.987421,0.996855,1,0.5,0.5,0.5,1]
area_under_roc_curve
0.8299896505055328 [1,0.984277,1,1,1,0.5,1,1,0.993711,1,1,0.996855,0.75,1,1,0.75,1,0.477987,0.5,0.5,0.746835,1,0.75,1,0.75,0.990566,0.996855,0.993671,0.5,1,1,1,1,0.996855,0.496835,1,0.493671,0.5,1,1,0.496835,1,0.996835,0.5,1,0.75,1,0.5,0.993711,0.5,0.490566,0.75,0.75,0.996855,1,0.5,1,1,1,0.993711,1,0.75,0.996855,1,1,0.987421,0.990566,1,0.75,0.75,1,0.75,0.5,1,0.496835,1,1,0.993711,1,1,0.75,1,0.75,1,0.5,0.75,1,0.493711,1,0.5,0.5,1,1,0.987421,1,0.996835,0.5,0.5,0.5,1]
area_under_roc_curve
0.8142862829392559 [0.493711,0.746835,1,1,0.75,0.993711,1,1,0.5,1,0.993711,0.993711,0.5,0.75,1,0.996855,1,0.484277,0.5,0.490566,0.75,1,1,1,1,0.5,0.990566,1,1,1,1,1,0.996855,0.996855,0.75,1,0.5,0.5,0.75,1,0.5,1,1,0.746835,1,0.996835,0.996855,0.5,0.996855,0.993711,1,0.746835,0.746835,0.75,0.5,0.490566,1,0.5,0.493671,0.5,0.75,0.75,1,1,1,0.993711,0.5,1,0.746835,0.996855,1,0.5,0.5,1,0.5,1,0.996855,0.993711,1,1,0.75,1,0.993711,0.493711,1,1,1,0.75,1,0.5,0.75,1,0.5,0.75,0.990566,0.75,0.977987,0.496835,0.5,0.996855]
area_under_roc_curve
0.8173911312793567 [1,0.75,1,1,1,0.990566,1,0.996855,0.5,1,0.996855,1,0.5,0.5,1,0.996855,1,0.477987,0.5,0.496855,0.75,1,0.996855,1,1,0.5,0.496855,1,1,0.5,1,1,0.996855,0.993711,0.75,0.746835,0.5,0.5,0.75,1,0.993711,1,1,0.993671,1,1,0.996855,0.5,0.996855,0.996855,0.75,0.75,1,0.75,1,0.987421,1,1,0.746835,0.5,1,0.75,0.496835,1,0.993711,1,0.5,1,0.75,0.990566,0.496855,1,0.5,0.746835,0.5,0.75,1,0.996855,1,0.996835,0.75,0.496855,0.996855,0.496855,1,0.996835,1,0.5,1,0.5,1,0.996835,0.75,0.5,1,0.75,0.977987,0.493671,0.5,0.993711]
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
0.6088636542859397
kappa
0.6781192063429451
kappa
0.6214361765053827
kappa
0.6025706738161889
kappa
0.6088173823888955
kappa
0.6340116737655781
kappa
0.6213465862028162
kappa
0.6592656860038648
kappa
0.6277749300106462
kappa
0.6340549706218699
kb_relative_information_score
0.6116543189532763
kb_relative_information_score
0.6805543591389857
kb_relative_information_score
0.6241815989870414
kb_relative_information_score
0.6053906789363939
kb_relative_information_score
0.6116543189532764
kb_relative_information_score
0.6367088790208071
kb_relative_information_score
0.6241815989870416
kb_relative_information_score
0.6617634390883376
kb_relative_information_score
0.6304452390039245
kb_relative_information_score
0.6367088790208072
mean_absolute_error
0.007750000000000004
mean_absolute_error
0.006375000000000003
mean_absolute_error
0.007500000000000004
mean_absolute_error
0.007875000000000004
mean_absolute_error
0.007750000000000004
mean_absolute_error
0.007250000000000004
mean_absolute_error
0.007500000000000004
mean_absolute_error
0.006750000000000003
mean_absolute_error
0.007375000000000004
mean_absolute_error
0.007250000000000004
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
0.6125
predictive_accuracy
0.68125
predictive_accuracy
0.625
predictive_accuracy
0.60625
predictive_accuracy
0.6125
predictive_accuracy
0.6375
predictive_accuracy
0.625
predictive_accuracy
0.6625
predictive_accuracy
0.63125
predictive_accuracy
0.6375
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
0.6125 [0,0,1,1,1,1,0.5,1,0,1,0.5,1,0,0,1,1,1,0,0,1,0,1,1,1,0,0,0.5,1,1,0,1,1,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,0,1,0,1,0,1,1,0,1,1,1,1,0.5,1,0.5,0,1,1,0,0.5,1,1,1,0,1,0.5,0,1,1,0,1,1,1,0.5,0.5,1,0.5,0.5,1,0.5,1,0,0,1,0,1,0,0,1]
recall
0.68125 [1,0,1,1,1,1,0.5,1,0,1,0.5,1,0,0.5,1,1,1,0,0,1,1,0,0,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,0.5,1,1,0.5,1,1,0.5,1,1,1,0,1,1,1,0.5,1,1,1,0.5,1,1,0,1,0,1,0.5,1,1,0.5,0,0.5,1,1,1,0.5,0,1,1,1,0.5,1,1,0.5,0.5,1,0,1,0,0,1,0.5,1,0,0,0]
recall
0.625 [0,0,1,1,0.5,1,0,1,1,1,1,1,1,0,1,0,1,0,0,0,0,0,0.5,1,1,0.5,0.5,1,1,1,1,1,1,0,1,1,1,0,1,0.5,0,1,1,1,1,1,0.5,1,0.5,1,0,1,1,0,1,0,1,1,1,0,1,0,0.5,0,1,0,0,1,1,0.5,0,1,1,1,1,0.5,1,0,1,1,1,1,1,0,1,1,1,0,1,1,0.5,1,1,0,1,1,0,0.5,0,1]
recall
0.60625 [0.5,0.5,1,1,0.5,0,1,1,0.5,0.5,0.5,1,1,0,1,1,1,0,0,0,0,1,1,1,0,0,0,1,0.5,1,1,1,0.5,0.5,1,1,1,0,1,1,1,1,1,1,1,1,0.5,1,1,1,0,1,1,0,1,0,1,1,1,0,1,1,1,0,0.5,0,0,1,0,0.5,0,0.5,0,0.5,1,1,1,0,1,1,1,1,0.5,0,1,1,1,0,1,1,0,1,1,0,1,1,0,0.5,0,0.5]
recall
0.6125 [0.5,1,1,1,1,0,1,1,0,0.5,1,1,1,0,1,1,1,0,1,0,0,1,0,1,0.5,0.5,0,1,1,0.5,1,0,0.5,1,1,1,0,0,1,1,1,0,1,1,1,1,1,0,1,0,0,0,0,0,0.5,0,1,1,0,1,1,1,1,1,0.5,0.5,0,1,0,0,0,0.5,1,1,0.5,1,1,0,1,1,1,1,0,1,1,1,1,1,1,0,1,0.5,1,1,1,1,0,1,0,1]
recall
0.6375 [0.5,1,1,1,1,0,1,1,1,0.5,0,1,1,1,1,1,1,0,1,0,0,0.5,0.5,1,0.5,0.5,0,0,1,0.5,1,1,1,0.5,1,0.5,0,0,1,1,1,0.5,1,1,1,1,1,0,1,0.5,1,1,0.5,1,0.5,0,1,1,0,1,1,1,1,1,1,0,1,1,0,0.5,0.5,0,1,1,0.5,1,1,0,1,1,0,0.5,0.5,1,1,1,1,1,1,0,0,1,1,1,1,1,0,1,0,0]
recall
0.625 [1,1,1,1,1,0,1,1,1,1,1,1,0,0,1,1,1,1,0,0,0,1,0.5,1,0.5,0,0,0.5,1,1,1,1,1,1,0.5,1,0,0,1,1,0.5,1,1,0,0,0,0,0,1,1,1,1,1,1,0.5,0,1,1,0,1,1,1,1,1,1,0,0,1,0.5,0.5,1,0.5,0,1,0,1,1,0,1,1,0.5,1,1,1,0,1,1,0,0,0,1,1,0,1,1,1,0,0,0,1]
recall
0.6625 [1,1,1,1,1,0,1,1,1,1,1,1,0.5,1,1,0.5,1,0,0,0,0.5,1,0.5,1,0.5,1,1,1,0,1,1,1,1,1,0,1,0,0,1,1,0,1,1,0,1,0.5,1,0,1,0,0,0.5,0.5,1,1,0,1,1,1,1,1,0.5,1,1,1,1,1,1,0.5,0.5,1,0.5,0,1,0,1,1,1,1,1,0.5,1,0.5,1,0,0.5,1,0,1,0,0,1,1,1,1,1,0,0,0,1]
recall
0.63125 [0,0.5,1,1,0.5,1,1,1,0,1,1,1,0,0.5,1,1,1,0,0,0,0.5,1,1,1,1,0,1,1,1,1,1,1,1,1,0.5,1,0,0,0.5,1,0,1,1,0.5,1,1,1,0,1,1,1,0.5,0.5,0.5,0,0,1,0,0,0,0.5,0.5,1,1,1,1,0,1,0.5,1,1,0,0,1,0,1,1,1,1,1,0.5,1,1,0,1,1,1,0.5,1,0,0.5,1,0,0.5,1,0.5,1,0,0,1]
recall
0.6375 [1,0.5,1,1,1,1,1,1,0,1,1,1,0,0,1,1,1,0,0,0,0.5,1,1,1,1,0,0,1,1,0,1,1,1,1,0.5,0.5,0,0,0.5,1,1,1,1,1,1,1,1,0,1,1,0.5,0.5,1,0.5,1,1,1,1,0.5,0,1,0.5,0,1,1,1,0,1,0.5,1,0,1,0,0.5,0,0.5,1,1,1,1,0.5,0,1,0,1,1,1,0,1,0,1,1,0.5,0,1,0.5,1,0,0,1]
relative_absolute_error
0.39141414141414105
relative_absolute_error
0.3219696969696966
relative_absolute_error
0.3787878787878784
relative_absolute_error
0.39772727272727226
relative_absolute_error
0.39141414141414105
relative_absolute_error
0.36616161616161574
relative_absolute_error
0.3787878787878784
relative_absolute_error
0.3409090909090905
relative_absolute_error
0.37247474747474707
relative_absolute_error
0.36616161616161574
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
0.08803408430829507
root_mean_squared_error
0.07984359711335658
root_mean_squared_error
0.08660254037844389
root_mean_squared_error
0.08874119674649426
root_mean_squared_error
0.08803408430829507
root_mean_squared_error
0.08514693182963202
root_mean_squared_error
0.08660254037844389
root_mean_squared_error
0.08215838362577493
root_mean_squared_error
0.08587782018658836
root_mean_squared_error
0.08514693182963202
root_relative_squared_error
0.884775837615541
root_relative_squared_error
0.8024583440524458
root_relative_squared_error
0.870388279778489
root_relative_squared_error
0.8918825850158444
root_relative_squared_error
0.884775837615541
root_relative_squared_error
0.8557588634207839
root_relative_squared_error
0.870388279778489
root_relative_squared_error
0.82572282384477
root_relative_squared_error
0.8631045677955218
root_relative_squared_error
0.8557588634207839
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
423.8188959998297
usercpu_time_millis
419.3196579999494
usercpu_time_millis
418.8718240000071
usercpu_time_millis
418.87384500000735
usercpu_time_millis
424.1016039998158
usercpu_time_millis
418.6408600000959
usercpu_time_millis
419.8410930000591
usercpu_time_millis
419.98905999980707
usercpu_time_millis
417.3484080001799
usercpu_time_millis
418.6474589998852
usercpu_time_millis_testing
63.996532999908595
usercpu_time_millis_testing
63.592602999960945
usercpu_time_millis_testing
63.57291399990572
usercpu_time_millis_testing
63.87716399990495
usercpu_time_millis_testing
63.96790999997393
usercpu_time_millis_testing
64.0809450001143
usercpu_time_millis_testing
63.5913480000454
usercpu_time_millis_testing
63.61272599997392
usercpu_time_millis_testing
63.28593700004603
usercpu_time_millis_testing
65.18737099986538
usercpu_time_millis_training
359.8223629999211
usercpu_time_millis_training
355.72705499998847
usercpu_time_millis_training
355.2989100001014
usercpu_time_millis_training
354.9966810001024
usercpu_time_millis_training
360.13369399984185
usercpu_time_millis_training
354.55991499998163
usercpu_time_millis_training
356.2497450000137
usercpu_time_millis_training
356.37633399983315
usercpu_time_millis_training
354.0624710001339
usercpu_time_millis_training
353.4600880000198
wall_clock_time_millis
423.83289337158203
wall_clock_time_millis
419.31986808776855
wall_clock_time_millis
418.86258125305176
wall_clock_time_millis
418.87617111206055
wall_clock_time_millis
424.11136627197266
wall_clock_time_millis
418.6427593231201
wall_clock_time_millis
419.8315143585205
wall_clock_time_millis
419.9941158294678
wall_clock_time_millis
417.339563369751
wall_clock_time_millis
418.66326332092285
wall_clock_time_millis_testing
64.00179862976074
wall_clock_time_millis_testing
63.59672546386719
wall_clock_time_millis_testing
63.576698303222656
wall_clock_time_millis_testing
63.881874084472656
wall_clock_time_millis_testing
63.97271156311035
wall_clock_time_millis_testing
64.08476829528809
wall_clock_time_millis_testing
63.59529495239258
wall_clock_time_millis_testing
63.630104064941406
wall_clock_time_millis_testing
63.28916549682617
wall_clock_time_millis_testing
65.2155876159668
wall_clock_time_millis_training
359.8310947418213
wall_clock_time_millis_training
355.72314262390137
wall_clock_time_millis_training
355.2858829498291
wall_clock_time_millis_training
354.9942970275879
wall_clock_time_millis_training
360.1386547088623
wall_clock_time_millis_training
354.55799102783203
wall_clock_time_millis_training
356.23621940612793
wall_clock_time_millis_training
356.36401176452637
wall_clock_time_millis_training
354.0503978729248
wall_clock_time_millis_training
353.44767570495605