6146942
1
Jan van Rijn
9954
Supervised Classification
6952
sklearn.pipeline.Pipeline(imputation=openmlstudy14.preprocessing.ConditionalImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,variencethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,classifier=sklearn.svm.classes.SVC)(1)
4180281
axis
0
6947
categorical_features
[]
6947
copy
true
6947
fill_empty
0
6947
missing_values
"NaN"
6947
strategy
"mean"
6947
strategy_nominal
"most_frequent"
6947
verbose
0
6947
categorical_features
[]
6948
dtype
{"oml-python:serialized_object": "type", "value": "np.float64"}
6948
handle_unknown
"ignore"
6948
n_values
"auto"
6948
sparse
true
6948
threshold
0.0
6949
C
171.42849955193327
6953
cache_size
200
6953
class_weight
null
6953
coef0
0.1889548134601673
6953
decision_function_shape
null
6953
degree
3
6953
gamma
0.09670554946887729
6953
kernel
"sigmoid"
6953
max_iter
-1
6953
probability
true
6953
random_state
41876
6953
shrinking
false
6953
tol
5.703935811639041e-05
6953
verbose
false
6953
openml-pimp
openml-python
Sklearn_0.18.1.
1491
one-hundred-plants-margin
https://www.openml.org/data/download/1592283/phpCsX3fx
-1
13224733
description
https://api.openml.org/data/download/13224733/description.xml
-1
13224734
predictions
https://api.openml.org/data/download/13224734/predictions.arff
area_under_roc_curve
0.9930922506313137 [0.988242,0.999645,1,1,0.999566,0.993371,0.998895,0.999803,0.993805,0.999842,0.997159,0.999132,0.997356,0.965949,0.999684,0.999961,1,0.980903,0.971117,0.972143,0.986308,0.999645,0.992227,1,0.995384,0.970802,0.974077,0.998658,0.99854,0.999961,0.999842,1,0.99929,0.9884,0.996449,0.998501,0.985677,0.969105,0.999724,0.999961,0.994871,0.99712,1,0.99854,0.998856,0.993687,0.99925,0.988834,0.998146,0.995384,0.991477,0.995739,0.996686,0.981613,0.994121,0.968434,1,0.999448,0.99128,0.979009,0.998974,0.99854,0.992779,0.997317,0.998777,0.992779,0.984099,0.999882,0.988991,0.990609,0.985519,0.997199,0.988281,0.999605,0.975734,0.999211,0.999527,0.98544,1,0.999369,0.993292,0.997711,0.998422,0.994594,0.995423,0.999408,1,0.996291,0.999171,0.99562,0.988439,0.999369,0.998067,0.992148,0.998303,0.99633,0.984533,0.991556,0.95202,0.994279]
average_cost
0
f_measure
0.752469775789221 [0.666667,0.848485,1,1,0.9375,0.454545,0.909091,0.969697,0.717949,0.896552,0.8,0.864865,0.740741,0.571429,1,0.969697,1,0.322581,0.26087,0.230769,0.526316,0.903226,0.647059,1,0.787879,0.294118,0.272727,0.8,0.903226,0.896552,0.969697,0.896552,0.848485,0.486486,0.83871,0.8,0.4,0.5,0.848485,0.967742,0.702703,0.857143,0.933333,0.777778,0.9375,0.823529,0.83871,0.689655,0.769231,0.83871,0.787879,0.785714,0.875,0.608696,0.787879,0.206897,1,0.903226,0.634146,0.709677,0.848485,0.909091,0.702703,0.848485,0.875,0.666667,0.228571,1,0.645161,0.689655,0.516129,0.692308,0.384615,0.83871,0.692308,0.914286,0.903226,0.536585,1,0.9375,0.666667,0.903226,0.903226,0.48,0.8,0.875,0.933333,0.903226,0.909091,0.896552,0.689655,0.8,0.758621,0.736842,0.914286,0.736842,0.642857,0.611111,0.266667,0.774194]
kappa
0.7518939393939394
kb_relative_information_score
907.5570687114242
mean_absolute_error
0.016856366245401124
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
0.7689773278197998 [0.6,0.823529,1,1,0.9375,0.833333,0.882353,0.941176,0.608696,1,0.857143,0.761905,0.909091,0.526316,1,0.941176,1,0.333333,0.428571,0.3,0.454545,0.933333,0.611111,1,0.764706,0.277778,0.214286,0.736842,0.933333,1,0.941176,1,0.823529,0.428571,0.866667,0.857143,0.428571,0.583333,0.823529,1,0.619048,0.789474,1,0.7,0.9375,0.777778,0.866667,0.769231,0.652174,0.866667,0.764706,0.916667,0.875,1,0.764706,0.230769,1,0.933333,0.52,0.733333,0.823529,0.882353,0.619048,0.823529,0.875,0.647059,0.210526,1,0.666667,0.769231,0.533333,0.9,0.5,0.866667,0.9,0.842105,0.933333,0.44,1,0.9375,0.714286,0.933333,0.933333,0.666667,0.736842,0.875,1,0.933333,0.882353,1,0.769231,0.857143,0.846154,0.636364,0.842105,0.636364,0.75,0.55,0.285714,0.8]
predictive_accuracy
0.754375
prior_entropy
6.6438561897747395
recall
0.754375 [0.75,0.875,1,1,0.9375,0.3125,0.9375,1,0.875,0.8125,0.75,1,0.625,0.625,1,1,1,0.3125,0.1875,0.1875,0.625,0.875,0.6875,1,0.8125,0.3125,0.375,0.875,0.875,0.8125,1,0.8125,0.875,0.5625,0.8125,0.75,0.375,0.4375,0.875,0.9375,0.8125,0.9375,0.875,0.875,0.9375,0.875,0.8125,0.625,0.9375,0.8125,0.8125,0.6875,0.875,0.4375,0.8125,0.1875,1,0.875,0.8125,0.6875,0.875,0.9375,0.8125,0.875,0.875,0.6875,0.25,1,0.625,0.625,0.5,0.5625,0.3125,0.8125,0.5625,1,0.875,0.6875,1,0.9375,0.625,0.875,0.875,0.375,0.875,0.875,0.875,0.875,0.9375,0.8125,0.625,0.75,0.6875,0.875,1,0.875,0.5625,0.6875,0.25,0.75]
relative_absolute_error
0.8513316285556108
root_mean_prior_squared_error
0.09949874371066209
root_mean_squared_error
0.08647233233980928
root_relative_squared_error
0.8690796397517034
total_cost
0
area_under_roc_curve
0.9917845911949683 [0.962264,1,1,1,1,1,1,1,0.993671,1,0.996835,0.993671,0.993671,0.914557,1,1,1,0.993671,0.962025,0.981132,0.974843,1,1,1,0.993711,0.981013,0.974684,1,1,1,1,1,0.996835,0.981013,0.981013,0.987421,0.993711,0.962264,1,1,1,0.993711,1,1,1,1,1,1,1,0.96519,0.993671,1,0.993711,0.990506,0.993711,0.993711,1,1,0.993711,0.993671,1,1,1,0.996835,1,1,1,1,1,0.899371,0.974684,1,1,1,1,1,1,0.977848,1,1,1,1,1,1,0.987342,0.996835,1,1,0.996835,1,0.996835,1,1,1,1,0.987342,0.962264,0.990506,0.889241,1]
area_under_roc_curve
0.9919463020460155 [0.987421,1,1,1,1,1,1,1,0.993671,1,0.996835,0.996835,1,0.908228,1,1,1,0.984177,0.993671,0.943396,0.993711,0.993711,1,1,1,0.968354,0.981013,1,1,1,1,1,0.996835,0.993671,0.996835,0.993711,0.987421,0.937107,1,1,1,1,1,1,1,1,1,1,1,1,1,0.993671,1,1,0.993711,0.949686,1,1,1,0.946203,1,1,0.990506,1,1,0.993671,0.984177,1,0.880503,1,0.981013,1,1,1,1,1,1,0.987342,1,0.993671,0.981013,1,1,0.981132,0.990506,1,1,1,1,1,0.977848,1,0.996835,0.981013,0.996835,1,0.968553,0.984177,0.968354,0.987421]
area_under_roc_curve
0.9930533994108748 [0.993671,1,1,1,1,0.993671,0.993711,1,0.990506,1,1,1,0.993711,0.996835,1,1,1,0.946203,0.968553,0.962025,0.937107,1,0.968354,1,1,0.981013,0.971519,0.993711,1,1,1,1,1,0.984177,1,1,1,0.899371,1,1,0.987342,0.993711,1,1,1,0.993711,1,0.987421,0.996835,1,0.993671,1,1,1,1,0.993671,1,1,0.974843,0.939873,1,1,1,0.981132,0.996835,0.993671,1,1,0.993711,0.993671,0.981013,0.996835,1,1,0.987421,1,1,0.996835,1,1,1,1,1,0.996835,1,1,1,1,1,0.993711,1,1,1,0.996835,0.993671,1,0.993671,1,0.918239,1]
area_under_roc_curve
0.9919485411193376 [0.990506,1,1,1,1,0.990506,1,1,0.987342,1,0.996835,1,1,0.996835,1,1,1,1,0.893082,0.974684,1,1,0.996835,1,0.974843,0.971519,0.952532,1,1,1,1,1,1,0.993671,0.993711,1,0.993711,0.930818,1,1,1,1,1,1,1,1,1,1,1,1,0.993671,1,0.993711,0.958861,1,0.952532,1,1,0.987421,0.987342,1,1,1,1,0.996835,1,0.96519,1,0.993711,0.990506,0.974684,0.996835,0.974843,1,0.987421,1,1,0.996835,1,1,1,1,1,1,1,1,1,1,1,0.993711,0.990506,1,0.993711,0.996835,1,0.987421,0.971519,0.990506,0.842767,0.971519]
area_under_roc_curve
0.994078894992437 [1,1,1,1,1,1,1,1,0.987421,1,0.990506,1,0.993711,0.924528,1,1,1,0.993671,0.981132,0.996835,1,0.996835,0.996835,1,0.993671,0.993671,0.981013,1,1,1,1,1,1,0.981013,0.993711,1,0.987342,0.955696,1,1,1,0.993671,1,1,1,0.974843,1,1,1,1,1,0.968553,0.996835,0.993711,0.987342,0.996835,1,0.996835,1,0.987421,1,1,0.987421,1,1,1,0.981132,1,0.993671,0.993671,0.996835,1,1,1,0.905063,1,0.993671,0.987342,1,1,0.993711,1,1,0.990506,0.974843,1,1,1,1,1,0.987421,0.996835,1,0.968553,0.990506,0.993711,1,1,0.993711,0.996835]
area_under_roc_curve
0.9932449645728841 [0.958861,1,1,1,1,0.987342,1,1,1,1,1,1,0.987421,1,1,1,1,0.990506,0.955975,0.933544,1,1,0.990506,1,0.993671,0.974684,0.974684,1,1,1,1,1,1,0.993671,0.993711,0.996835,0.987342,0.981013,1,1,1,1,1,1,1,0.974843,1,0.984177,1,0.996835,1,1,0.996835,1,0.996835,0.971519,1,1,0.996835,1,0.993671,1,0.987421,1,1,0.987342,0.987421,1,0.996835,1,0.990506,0.990506,1,1,0.987342,1,1,0.974684,1,1,0.987421,0.996835,1,0.987342,0.993711,1,1,1,1,0.987342,0.962264,1,1,1,1,1,0.990506,0.987421,0.949686,0.987342]
area_under_roc_curve
0.9934900187087011 [0.996835,1,1,1,1,0.996835,1,1,0.993711,1,1,1,0.993671,1,1,1,1,0.987421,0.981013,0.962025,0.993671,1,1,1,0.993671,0.855346,0.930818,0.993671,1,1,0.996835,1,1,0.981132,1,1,0.96519,0.977848,1,1,0.996835,1,1,1,0.981132,1,1,0.987342,1,1,0.987421,1,1,1,0.987342,0.968354,1,1,0.990506,0.993711,1,0.990506,1,0.996835,1,0.981132,0.993711,0.996835,0.990506,1,0.993711,1,0.996835,1,0.996835,1,1,0.968553,1,1,0.977848,1,1,1,1,1,1,0.962264,1,1,1,1,0.987342,0.987421,1,1,0.984177,0.974843,0.993671,1]
area_under_roc_curve
0.9946349315341134 [1,1,1,1,1,1,1,1,0.987421,1,0.987421,1,0.996835,1,1,1,1,0.924528,0.96519,0.996835,0.993671,1,0.993671,1,0.993671,0.968553,0.974843,1,0.993711,1,1,1,1,0.987421,0.996835,1,0.977848,0.968354,1,1,1,1,1,1,1,1,1,0.987342,1,1,0.949686,0.996835,0.996835,1,0.996835,0.955696,1,1,0.984177,0.993711,1,1,0.993711,1,1,0.962264,0.949686,1,0.996835,0.996835,1,1,0.996835,1,0.993671,1,1,1,1,1,0.996835,1,0.993671,1,1,1,1,0.987421,1,0.996835,0.993711,1,1,1,1,0.993671,0.996835,0.974843,0.993671,1]
area_under_roc_curve
0.993762688082159 [0.981132,1,1,1,1,0.993711,0.996835,1,1,1,0.993711,1,1,0.993671,1,1,1,0.981132,0.996835,0.987421,1,1,0.974843,1,1,1,0.981132,1,1,1,1,1,1,0.987421,0.996835,1,0.977848,0.990506,1,1,0.987421,1,1,0.990506,1,0.981013,1,0.990506,0.993711,0.993711,0.987342,0.996835,1,0.943038,0.990506,0.90566,1,1,1,0.996835,0.996835,1,1,0.996835,1,0.993711,0.968354,1,0.990506,0.993711,1,0.987421,0.949367,1,0.996835,0.993671,1,0.993711,1,0.996835,1,0.993711,1,0.981132,1,1,1,1,1,0.996835,0.993671,1,1,0.993671,0.993711,0.990506,0.981132,1,0.968354,1]
area_under_roc_curve
0.9949080984794202 [0.993711,1,1,1,1,0.993711,1,1,0.993671,1,1,1,1,0.990506,1,1,1,0.943396,0.981013,0.962264,0.952532,1,1,1,1,0.974843,1,1,0.996835,1,1,1,1,1,1,1,0.990506,1,1,1,1,0.996835,1,1,1,1,1,0.996835,1,1,0.996835,1,1,0.984177,0.996835,0.981132,1,1,0.981013,0.987342,1,1,0.984177,1,0.993711,0.993711,0.977848,1,1,0.981132,0.993711,1,0.987342,0.996835,0.987342,0.993671,1,0.987421,1,1,1,0.981132,0.993711,0.981132,1,1,1,0.996835,1,0.990506,0.993671,1,1,0.993671,1,0.996835,0.968553,0.993671,0.993671,1]
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
0.715606114468539
kappa
0.7597787435796127
kappa
0.7472353870458136
kappa
0.7346390775548887
kappa
0.766183498558395
kappa
0.7220028431527404
kappa
0.7472154198593886
kappa
0.7724579284190567
kappa
0.7598641336545676
kappa
0.7914774298013506
kb_relative_information_score
90.89162335118601
kb_relative_information_score
89.77404050099031
kb_relative_information_score
90.63235088047901
kb_relative_information_score
89.98844473838257
kb_relative_information_score
90.06718865450992
kb_relative_information_score
89.07609071948745
kb_relative_information_score
92.98090092779631
kb_relative_information_score
91.75129420712848
kb_relative_information_score
90.9475808672391
kb_relative_information_score
91.44755386422342
mean_absolute_error
0.016774946771573502
mean_absolute_error
0.016935401183860374
mean_absolute_error
0.01687107113496967
mean_absolute_error
0.016911246969461342
mean_absolute_error
0.01694572974339952
mean_absolute_error
0.017011784559676474
mean_absolute_error
0.01665256352154496
mean_absolute_error
0.016784065006962876
mean_absolute_error
0.016857130325002898
mean_absolute_error
0.016819723237559453
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
0.71875
predictive_accuracy
0.7625
predictive_accuracy
0.75
predictive_accuracy
0.7375
predictive_accuracy
0.76875
predictive_accuracy
0.725
predictive_accuracy
0.75
predictive_accuracy
0.775
predictive_accuracy
0.7625
predictive_accuracy
0.79375
prior_entropy
6.6438561897747395
prior_entropy
6.6438561897747395
prior_entropy
6.6438561897747395
prior_entropy
6.6438561897747395
prior_entropy
6.6438561897747395
prior_entropy
6.6438561897747395
prior_entropy
6.6438561897747395
prior_entropy
6.6438561897747395
prior_entropy
6.6438561897747395
prior_entropy
6.6438561897747395
recall
0.71875 [1,0.5,1,1,1,0,1,1,1,1,0.5,1,0.5,0,1,1,1,0.5,0.5,0,0,1,1,1,0,0,0.5,1,1,0,1,0.5,0.5,0.5,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0,1,0,1,1,0,1,1,1,1,1,1,1,0.5,1,1,0,0.5,1,0.5,1,0,1,0.5,0.5,1,1,1,1,1,0,1,0.5,0.5,1,0.5,1,1,1,0.5,0.5,1,0.5,0,1,0,1]
recall
0.7625 [1,1,1,1,1,0,0.5,1,1,1,0.5,1,1,0.5,1,1,1,0.5,1,0,0,0,0,1,1,0.5,0.5,0.5,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0,1,1,1,0.5,1,1,1,1,1,1,0.5,1,0,0,0.5,1,0,0.5,0,1,0.5,1,1,0.5,0,1,1,0,0.5,1,1,1,1,0,0.5,1,1,1,1,1,0,0.5,0.5,0]
recall
0.75 [0.5,1,1,1,1,0.5,1,1,1,1,1,1,0,1,1,1,1,0.5,0,0,0,1,0,1,1,0.5,0.5,1,1,1,1,1,1,0,1,1,0,0,1,0.5,0,1,1,1,1,1,0.5,1,0.5,1,1,1,1,1,1,0.5,1,1,1,0,1,1,0.5,0,1,1,0,1,0,1,0.5,1,0,1,1,1,1,0,1,1,1,1,1,0,1,1,1,1,1,1,1,0,0,1,1,1,0.5,0.5,0,1]
recall
0.7375 [1,0.5,1,1,0.5,0,1,1,0.5,0.5,0.5,1,0,0.5,1,1,1,0.5,0,0,1,1,1,1,0,0.5,0.5,1,1,1,1,1,1,1,0,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,0,1,1,1,0.5,1,1,1,0,0.5,0,0,1,0,0.5,0.5,0.5,0,1,1,1,1,1,1,1,1,1,0.5,0,1,1,1,1,1,1,0,1,1,1,1,1,0.5,1,0,0.5]
recall
0.76875 [0.5,1,1,1,1,0.5,1,1,1,0.5,1,1,0,0,1,1,1,0,0,0.5,1,1,0.5,1,1,0.5,0.5,1,1,0.5,1,1,0.5,0.5,1,1,1,0.5,1,1,1,1,1,1,1,0,1,0.5,1,1,1,0,0.5,0,0.5,0.5,1,0.5,0.5,1,1,1,1,1,0.5,1,0,1,0.5,0.5,1,0.5,0,1,0.5,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,0.5,0,1,1,1,0.5,0,1,1]
recall
0.725 [0.5,1,1,1,1,0,1,1,1,0.5,1,1,0,1,1,1,1,0.5,0,0.5,1,0.5,1,1,1,0.5,0.5,0,1,0.5,1,1,1,1,1,0.5,0.5,0.5,1,1,1,1,1,1,1,1,1,0,1,0.5,0,1,1,0,1,0,1,1,0.5,1,0.5,1,1,1,1,0.5,0,1,1,1,0.5,0,1,1,0.5,1,1,0.5,1,1,0,0.5,1,0.5,0,1,1,1,1,0,0,0.5,1,1,1,1,0.5,1,0,0]
recall
0.75 [1,1,1,1,1,0.5,1,1,0,1,1,1,1,1,1,1,1,0,0,0,0.5,1,1,1,1,0,0,1,1,1,1,1,1,0,1,1,0,0,1,1,1,0.5,1,1,0,0.5,0,0.5,1,1,1,1,1,0,0.5,0,1,1,1,0,1,1,1,1,1,0,0,1,1,1,0,0.5,0.5,0,1,1,1,0,1,1,0.5,1,1,1,1,1,1,0,1,1,1,1,0,1,1,1,1,0,0,1]
recall
0.775 [0.5,1,1,1,1,0.5,1,1,1,1,0,1,0.5,1,1,1,1,0,0,0.5,0.5,1,0.5,1,0.5,0,0,1,0,1,1,1,1,0,1,1,0.5,1,1,1,1,1,1,1,1,1,1,0.5,1,0,0,0.5,1,0,1,0.5,1,1,1,1,1,0.5,1,1,1,0,0,1,1,1,0,0.5,1,1,1,1,1,1,1,1,0.5,1,0.5,0.5,1,0.5,1,0,1,1,0,1,1,0,1,1,1,0,0.5,1]
recall
0.7625 [1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,0,0,1,1,1,1,1,1,0,1,1,0.5,0.5,0,1,0,1,0.5,0,1,1,1,1,1,1,1,0.5,0.5,0.5,0.5,0,1,0,1,1,0.5,1,1,1,1,1,0.5,1,0.5,0,1,0,0,0.5,0.5,1,1,1,1,1,0.5,1,1,0,1,1,1,1,1,1,0.5,0.5,1,1,1,0.5,0,1,0,1]
recall
0.79375 [1,1,1,1,1,0,1,1,1,1,1,1,1,0.5,1,1,1,0,0,0,0.5,1,1,1,1,0,0,1,0.5,1,1,0,1,1,1,0.5,0.5,1,1,1,1,1,0.5,1,1,1,1,0.5,1,1,0.5,0.5,1,0.5,1,0,1,1,1,1,1,1,0,1,1,1,0.5,1,0.5,0,0,1,0,1,0,1,1,1,1,1,1,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1]
relative_absolute_error
0.8472195339178522
relative_absolute_error
0.8553232921141588
relative_absolute_error
0.8520742997459415
relative_absolute_error
0.854103382296026
relative_absolute_error
0.8558449365353278
relative_absolute_error
0.8591810383674973
relative_absolute_error
0.8410385616941884
relative_absolute_error
0.8476800508567095
relative_absolute_error
0.8513702184344883
relative_absolute_error
0.8494809715939102
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
0.08620111077361681
root_mean_squared_error
0.08673916877831987
root_mean_squared_error
0.08659980304223235
root_mean_squared_error
0.08670349400918848
root_mean_squared_error
0.08684842376105012
root_mean_squared_error
0.087298652230909
root_mean_squared_error
0.0854840492488134
root_mean_squared_error
0.08603384723049573
root_mean_squared_error
0.08647661210918689
root_mean_squared_error
0.08632527188084274
root_relative_squared_error
0.8663537604483311
root_relative_squared_error
0.871761446863626
root_relative_squared_error
0.8703607685144321
root_relative_squared_error
0.8714029019433492
root_relative_squared_error
0.8728595007551199
root_relative_squared_error
0.8773844671322648
root_relative_squared_error
0.8591470209653826
root_relative_squared_error
0.8646726985888218
root_relative_squared_error
0.8691226530523545
root_relative_squared_error
0.8676016265277964
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
2102.692513000001
usercpu_time_millis
1950.9491050000013
usercpu_time_millis
1919.454179999999
usercpu_time_millis
1923.778284000001
usercpu_time_millis
1921.8195070000022
usercpu_time_millis
1908.1069959999973
usercpu_time_millis
1925.6812540000005
usercpu_time_millis
1922.9449719999998
usercpu_time_millis
1906.9201589999984
usercpu_time_millis
1911.0449679999988
usercpu_time_millis_testing
167.80878600000017
usercpu_time_millis_testing
162.36005900000094
usercpu_time_millis_testing
162.45684699999964
usercpu_time_millis_testing
161.40331500000116
usercpu_time_millis_testing
164.1422040000009
usercpu_time_millis_testing
160.99691699999852
usercpu_time_millis_testing
163.29651200000228
usercpu_time_millis_testing
161.81072299999855
usercpu_time_millis_testing
161.26553199999805
usercpu_time_millis_testing
159.75269799999836
usercpu_time_millis_training
1934.8837270000008
usercpu_time_millis_training
1788.5890460000003
usercpu_time_millis_training
1756.9973329999993
usercpu_time_millis_training
1762.3749689999997
usercpu_time_millis_training
1757.6773030000013
usercpu_time_millis_training
1747.1100789999987
usercpu_time_millis_training
1762.3847419999984
usercpu_time_millis_training
1761.1342490000013
usercpu_time_millis_training
1745.6546270000003
usercpu_time_millis_training
1751.2922700000004