8703133
1
Jan van Rijn
9954
Supervised Classification
7707
sklearn.pipeline.Pipeline(imputation=openmlstudy14.preprocessing.ConditionalImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,scaling=sklearn.preprocessing.data.StandardScaler,variencethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,classifier=sklearn.svm.classes.SVC)(1)
6680552
axis
0
7660
categorical_features
[]
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copy
true
7660
fill_empty
0
7660
missing_values
"NaN"
7660
strategy
"median"
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strategy_nominal
"most_frequent"
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verbose
0
7660
categorical_features
[]
7661
dtype
{"oml-python:serialized_object": "type", "value": "np.float64"}
7661
handle_unknown
"ignore"
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n_values
"auto"
7661
sparse
true
7661
threshold
0.0
7662
copy
true
7663
with_mean
false
7663
with_std
true
7663
C
7534.946171736372
7708
cache_size
200
7708
class_weight
null
7708
coef0
-0.7977402015139905
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decision_function_shape
null
7708
degree
4
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gamma
6.694931259883326e-05
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kernel
"rbf"
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max_iter
-1
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probability
true
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random_state
35419
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shrinking
false
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tol
0.00532286869278853
7708
verbose
false
7708
openml-pimp
openml-python
Sklearn_0.18.1.
study_71
1491
one-hundred-plants-margin
https://www.openml.org/data/download/1592283/phpCsX3fx
-1
18323155
description
https://api.openml.org/data/download/18323155/description.xml
-1
18323156
predictions
https://api.openml.org/data/download/18323156/predictions.arff
area_under_roc_curve
0.9965593434343434 [0.989781,0.999961,1,1,0.998303,0.994673,0.999842,0.999921,0.997869,0.999961,0.998935,0.999605,0.999724,0.981376,0.999645,0.999645,1,0.990254,0.983665,0.973919,0.998264,0.999448,0.997238,0.999842,0.998343,0.974905,0.991832,0.999369,0.998777,1,0.999842,1,1,0.989702,0.999684,0.999171,0.993766,0.98327,0.999842,0.999961,0.999211,0.999448,1,0.999053,0.997751,0.999803,0.999487,0.999092,0.997475,0.996567,0.994594,0.99925,0.998382,0.990491,0.997159,0.993253,1,0.999566,0.992779,0.996528,0.999211,0.999369,0.997435,0.999369,0.999408,0.994949,0.988084,1,0.998461,0.994121,0.996094,0.999487,0.996725,0.998343,0.988715,0.999605,0.999566,0.990846,1,1,0.994989,0.99783,0.998027,0.995305,0.999211,0.999842,0.999961,0.999329,0.999605,1,0.999171,0.999527,0.998895,0.997751,0.997396,0.997909,0.997672,0.998422,0.966738,0.998343]
average_cost
0
f_measure
0.8305549091831095 [0.764706,0.9375,1,1,0.933333,0.827586,1,0.967742,0.875,0.933333,0.909091,0.875,0.9375,0.740741,0.967742,0.933333,1,0.645161,0.368421,0.266667,0.774194,0.967742,0.787879,1,0.875,0.424242,0.545455,0.848485,0.933333,0.896552,0.967742,1,1,0.5,0.848485,0.875,0.516129,0.484848,0.914286,0.967742,0.777778,0.909091,1,0.875,0.9375,0.941176,0.857143,0.83871,0.764706,0.8125,0.75,0.827586,0.866667,0.727273,0.733333,0.5,1,0.9375,0.684211,0.742857,0.896552,0.848485,0.774194,0.9375,0.909091,0.684211,0.580645,1,0.866667,0.685714,0.823529,0.933333,0.625,0.967742,0.756757,0.909091,0.9375,0.647059,1,1,0.774194,0.875,0.875,0.482759,0.848485,0.967742,0.933333,0.875,0.967742,0.967742,0.8125,0.903226,0.875,0.903226,0.967742,0.777778,0.8,0.823529,0.482759,0.866667]
kappa
0.827020202020202
kb_relative_information_score
990.4569244729369
mean_absolute_error
0.016059689472586246
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
0.8378992988435714 [0.722222,0.9375,1,1,1,0.923077,1,1,0.875,1,0.882353,0.875,0.9375,0.909091,1,1,1,0.666667,0.318182,0.285714,0.8,1,0.764706,1,0.875,0.411765,0.529412,0.823529,1,1,1,1,1,0.5,0.823529,0.875,0.533333,0.470588,0.842105,1,0.7,0.882353,1,0.875,0.9375,0.888889,1,0.866667,0.722222,0.8125,0.75,0.923077,0.928571,0.705882,0.785714,0.5,1,0.9375,0.590909,0.684211,1,0.823529,0.8,0.9375,0.882353,0.590909,0.6,1,0.928571,0.631579,0.777778,1,0.625,1,0.666667,0.882353,0.9375,0.611111,1,1,0.8,0.875,0.875,0.538462,0.823529,1,1,0.875,1,1,0.8125,0.933333,0.875,0.933333,1,0.7,0.736842,0.777778,0.538462,0.928571]
predictive_accuracy
0.82875
prior_entropy
6.6438561897747395
recall
0.82875 [0.8125,0.9375,1,1,0.875,0.75,1,0.9375,0.875,0.875,0.9375,0.875,0.9375,0.625,0.9375,0.875,1,0.625,0.4375,0.25,0.75,0.9375,0.8125,1,0.875,0.4375,0.5625,0.875,0.875,0.8125,0.9375,1,1,0.5,0.875,0.875,0.5,0.5,1,0.9375,0.875,0.9375,1,0.875,0.9375,1,0.75,0.8125,0.8125,0.8125,0.75,0.75,0.8125,0.75,0.6875,0.5,1,0.9375,0.8125,0.8125,0.8125,0.875,0.75,0.9375,0.9375,0.8125,0.5625,1,0.8125,0.75,0.875,0.875,0.625,0.9375,0.875,0.9375,0.9375,0.6875,1,1,0.75,0.875,0.875,0.4375,0.875,0.9375,0.875,0.875,0.9375,0.9375,0.8125,0.875,0.875,0.875,0.9375,0.875,0.875,0.875,0.4375,0.8125]
relative_absolute_error
0.8110954279083948
root_mean_prior_squared_error
0.09949874371066209
root_mean_squared_error
0.08238646492355677
root_relative_squared_error
0.8280151271370113
total_cost
0
area_under_roc_curve
0.9966015842687682 [1,1,1,1,1,1,1,1,1,1,1,0.996835,1,0.993671,1,0.993711,1,0.990506,0.981013,0.987421,0.993711,1,1,1,1,0.996835,0.996835,1,1,1,1,1,1,0.990506,1,0.993711,1,0.993711,1,1,1,1,1,1,1,1,1,1,1,0.977848,1,1,1,1,0.993711,1,1,1,1,1,1,1,1,1,1,1,0.974684,1,1,0.968553,0.996835,1,1,1,1,1,1,0.955696,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.996835,1,0.990506,0.987421,1,0.933544,1]
area_under_roc_curve
0.996522221558793 [1,1,1,1,1,1,1,1,1,1,1,1,1,0.905063,1,1,1,0.981013,0.993671,0.993711,1,1,0.993711,1,1,0.971519,0.971519,1,1,1,1,1,1,0.996835,1,1,0.987421,1,1,1,1,1,1,1,1,1,1,1,0.996835,1,1,1,1,1,1,0.993711,1,1,1,0.993671,1,1,1,1,1,0.996835,1,1,0.993711,1,0.996835,1,1,1,1,1,1,0.993671,1,1,0.981013,0.996835,1,0.981132,0.996835,1,1,1,1,1,1,1,1,0.993671,1,1,1,0.996835,1,0.974843]
area_under_roc_curve
0.9968767415014727 [1,1,1,1,1,1,1,1,0.996835,1,1,1,1,1,1,1,1,0.990506,1,0.936709,1,1,0.996835,1,1,0.933544,1,1,1,1,1,1,1,0.984177,1,1,0.993711,1,1,1,0.993671,0.987421,1,1,1,1,1,1,0.996835,1,1,1,1,1,1,1,1,1,0.981132,0.984177,1,1,1,0.993711,1,0.990506,1,1,1,0.984177,1,0.996835,1,1,1,1,1,0.996835,1,1,1,1,1,0.996835,1,1,1,1,1,1,1,1,1,1,0.993671,1,1,1,1,1]
area_under_roc_curve
0.9966428827322664 [1,1,1,1,1,0.993671,1,1,0.996835,1,1,1,1,1,1,1,1,0.987342,0.943396,0.958861,1,1,0.996835,1,0.993711,0.981013,1,1,1,1,1,1,1,0.990506,1,1,1,0.968553,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.981013,1,0.981013,1,1,0.993711,1,1,1,1,1,1,0.996835,0.993671,1,1,0.977848,0.974684,1,0.981132,1,0.993711,1,1,0.996835,1,1,1,1,0.993671,0.996835,1,1,1,1,1,1,1,1,0.993711,1,1,1,1,1,1,1]
area_under_roc_curve
0.9965632712363665 [1,1,1,1,1,0.993671,1,1,1,1,0.993671,1,1,0.968553,1,1,1,0.990506,0.987421,0.987342,1,1,1,1,0.996835,0.993671,0.993671,1,1,1,1,1,1,0.977848,1,1,0.993671,0.984177,1,1,1,1,1,1,1,1,1,1,1,1,0.993711,0.987421,1,1,0.990506,0.993671,1,0.996835,1,1,1,1,0.993711,1,1,1,1,1,0.996835,1,1,1,1,1,0.943038,1,0.993671,1,1,1,1,1,1,0.990506,0.993711,1,1,1,1,1,1,1,1,1,0.974684,0.993711,1,1,0.962264,1]
area_under_roc_curve
0.9962828894992436 [0.924051,1,1,1,1,0.984177,1,1,1,1,1,1,1,1,1,1,1,1,1,0.958861,1,1,1,1,0.993671,0.990506,0.990506,1,1,1,1,1,1,0.993671,1,0.993671,0.996835,0.971519,1,1,0.996835,1,1,1,1,1,1,1,0.990506,0.993671,1,1,1,1,1,0.990506,1,1,0.993671,1,0.996835,1,0.993711,1,1,0.981013,1,1,0.996835,1,1,1,1,1,0.993671,1,1,1,1,1,0.993711,0.993671,1,0.993671,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.981132,1]
area_under_roc_curve
0.995695505931056 [1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.993711,1,0.968354,1,1,0.990506,1,1,0.893082,0.974843,0.996835,1,1,0.996835,1,1,0.987421,1,1,0.974684,0.993671,1,1,1,1,1,1,0.981132,0.996835,1,0.996835,1,1,1,1,1,1,1,1,1,1,0.987342,1,1,1,1,0.996835,1,0.993711,1,1,1,1,1,1,0.996835,1,1,1,1,0.993711,1,1,0.971519,1,1,1,1,1,1,1,1,1,1,1,0.993671,1,1,1,1,1,0.886076,1]
area_under_roc_curve
0.9977124134224982 [1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.993711,0.987342,1,0.996835,1,1,1,0.993671,0.993711,1,1,0.974843,1,1,1,1,1,1,1,0.987342,0.993671,1,1,1,1,1,1,1,1,1,0.993671,1,0.987421,0.968553,1,0.996835,1,1,0.984177,1,1,0.993671,1,1,1,1,1,1,0.974843,0.955975,1,1,0.996835,1,1,1,1,1,1,1,0.981132,1,1,0.993671,1,0.993671,1,1,1,1,1,1,1,1,1,1,1,1,0.993671,1,1,1,0.996835]
area_under_roc_curve
0.9974332756149986 [1,1,1,1,1,1,1,1,1,1,1,1,1,0.996835,1,1,1,0.987421,0.987342,0.968553,1,1,0.993711,1,1,0.987421,0.993711,1,1,1,1,1,1,0.993711,1,1,1,0.946203,1,1,1,1,1,0.996835,1,1,1,1,0.993711,1,0.990506,1,1,0.962025,0.996835,0.993711,1,1,1,1,1,1,1,1,1,1,0.987342,1,0.996835,1,1,0.993711,0.990506,1,1,1,1,0.993711,1,1,1,1,1,0.987421,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1]
area_under_roc_curve
0.9978278500915533 [0.993711,1,1,1,1,1,1,1,1,1,1,1,1,0.993671,1,1,1,1,0.974684,0.987421,1,1,1,1,1,1,1,0.996835,1,1,1,1,1,0.993711,1,0.993671,0.996835,1,1,1,1,1,1,1,1,1,1,1,0.993711,1,1,1,1,0.996835,0.996835,1,1,1,0.984177,1,1,1,0.987342,1,0.993711,0.993711,0.993671,1,1,1,1,1,0.993671,0.990506,1,0.993671,1,1,1,1,1,0.968553,1,0.993711,1,1,1,0.996835,1,1,0.996835,1,1,0.990506,1,1,0.993711,0.993671,1,1]
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
0.8168180023687327
kappa
0.829397361977727
kappa
0.8799747315224258
kappa
0.8105163429654192
kappa
0.8104789355233545
kappa
0.810493900272415
kappa
0.8231206569804169
kappa
0.8230717586193278
kappa
0.867330016583748
kappa
0.7979080323662917
kb_relative_information_score
99.23163325094708
kb_relative_information_score
97.78060472329955
kb_relative_information_score
99.19989924245236
kb_relative_information_score
98.09876993290241
kb_relative_information_score
98.53271685930025
kb_relative_information_score
98.06650663049149
kb_relative_information_score
101.18654562168499
kb_relative_information_score
98.85194016475212
kb_relative_information_score
99.97356562157576
kb_relative_information_score
99.53474242552863
mean_absolute_error
0.01595449194044634
mean_absolute_error
0.016224921238366115
mean_absolute_error
0.016085702749693575
mean_absolute_error
0.0162031521775977
mean_absolute_error
0.01618029525333008
mean_absolute_error
0.01613717815809463
mean_absolute_error
0.015778633493217058
mean_absolute_error
0.016087651925587365
mean_absolute_error
0.01595453866472584
mean_absolute_error
0.01599032912480385
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
0.81875
predictive_accuracy
0.83125
predictive_accuracy
0.88125
predictive_accuracy
0.8125
predictive_accuracy
0.8125
predictive_accuracy
0.8125
predictive_accuracy
0.825
predictive_accuracy
0.825
predictive_accuracy
0.86875
predictive_accuracy
0.8
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
0.81875 [1,0.5,1,1,0.5,1,1,1,1,1,0.5,1,1,0,1,0,1,0.5,0,1,0,1,1,1,1,0.5,0.5,1,1,0,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0,1,1,0,1,1,1,1,1,1,0.5,0,1,1,1,1,1,1,1,1,0.5,1,0.5,1,1,1,1,1,1,0.5,0,1,0,1]
recall
0.83125 [1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0.5,0.5,0,1,1,0,1,1,0.5,0,1,1,1,1,1,1,1,0.5,0,0,0,1,1,1,1,1,0.5,1,1,1,1,0.5,1,1,0.5,1,0.5,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,0,1,1,0,0.5,1,1,1,1,1,0.5,1,0.5,1,1,1,1,1,0.5,0]
recall
0.88125 [1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,0.5,1,0,1,1,0.5,1,1,0.5,1,1,1,1,1,1,1,0.5,1,1,1,1,1,0.5,0.5,0,1,1,1,1,0.5,1,0.5,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,0,1]
recall
0.8125 [0.5,1,1,1,0.5,0.5,1,1,0.5,0.5,1,0.5,1,0.5,1,1,1,0.5,0,0.5,1,1,1,1,0,0,1,1,1,1,1,1,1,0.5,1,1,1,0,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,0.5,1,0.5,1,1,1,1,1,1,1,1,0.5,0.5,0.5,1,1,0.5,0,1,0,1,1,1,1,0.5,1,1,1,1,0.5,0.5,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,0.5]
recall
0.8125 [1,1,1,1,1,0.5,1,1,1,1,1,1,1,0,1,1,1,0.5,1,0.5,0.5,1,1,1,1,1,0.5,1,1,0.5,1,1,1,0,1,1,0.5,0,1,1,1,1,1,0,1,1,1,0.5,1,1,0,0,0.5,1,0,0,1,1,1,1,1,1,0,1,1,1,1,1,0.5,0.5,1,1,1,1,0.5,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,0.5,1,0,0.5,1,1,1,0,1]
recall
0.8125 [0.5,1,1,1,1,0.5,1,0.5,1,0.5,1,1,0,1,1,1,1,1,1,0,0.5,0.5,1,1,1,1,0.5,0,1,1,1,1,1,0.5,1,0.5,0,0.5,1,1,1,1,1,1,1,1,1,1,0.5,0.5,1,1,0.5,1,1,0.5,1,1,0.5,1,0.5,0.5,1,1,1,0.5,1,1,0.5,1,1,1,1,1,0.5,1,1,0.5,1,1,1,0.5,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1]
recall
0.825 [1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,0.5,1,1,0,0,1,1,1,1,1,0,0,0.5,1,1,0.5,1,1,1,1,1,0,0.5,1,1,1,1,1,1,0,1,0,0.5,1,1,1,1,1,1,0.5,0.5,1,1,0,1,1,0.5,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,0,1,1,1,1,0.5,1,1,1,1,1,0,1]
recall
0.825 [0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,0,0.5,1,1,1,0.5,0,1,1,0,0.5,1,1,1,1,1,1,0.5,1,1,1,0.5,1,1,1,1,1,1,0.5,1,0,0,0.5,0.5,1,1,0.5,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,0,1,1,0.5,1,0.5,0.5,0.5,0.5,1,1,1,1,0,0.5,1,1,1,1,1,1,1,0.5]
recall
0.86875 [1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,0,0.5,0,1,1,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,0.5,0.5,0,1,0,1,1,0.5,1,1,1,1,1,0.5,1,1,1,1,0,0.5,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0.5,1,1,1,1,0.5,1,1,0.5,1]
recall
0.8 [1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,0,1,1,1,1,1,1,0,0,1,0.5,1,1,1,1,0,0.5,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,0.5,1,0.5,0.5,1,1,1,1,0.5,0.5,1,0,1,1,1,0,1,0.5,1,1,0,0,0.5,1,0.5,1,1,1,1,1,0,1,0,1,1,0.5,0.5,1,1,1,1,1,0.5,1,1,1,0,1,1]
relative_absolute_error
0.8057824212346623
relative_absolute_error
0.8194404665841458
relative_absolute_error
0.8124092297825025
relative_absolute_error
0.8183410190705895
relative_absolute_error
0.8171866289560633
relative_absolute_error
0.8150089978835657
relative_absolute_error
0.7969006814756077
relative_absolute_error
0.8125076730094615
relative_absolute_error
0.8057847810467584
relative_absolute_error
0.8075923800405971
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
0.08200606124643277
root_mean_squared_error
0.08306491980239945
root_mean_squared_error
0.0823812481226794
root_mean_squared_error
0.08302032250356708
root_mean_squared_error
0.0828518355231612
root_mean_squared_error
0.08285911355394533
root_mean_squared_error
0.08108329949836843
root_mean_squared_error
0.08242500822113438
root_mean_squared_error
0.08188217953293275
root_mean_squared_error
0.08226993947282879
root_relative_squared_error
0.8241919263312788
root_relative_squared_error
0.8348338552288516
root_relative_squared_error
0.827962696315447
root_relative_squared_error
0.834385635511002
root_relative_squared_error
0.8326922776441346
root_relative_squared_error
0.8327654246057214
root_relative_squared_error
0.8149178218184852
root_relative_squared_error
0.8284025018529144
root_relative_squared_error
0.8229468682644125
root_relative_squared_error
0.8268440022927941
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
1668.8545209999575
usercpu_time_millis
1451.081803001216
usercpu_time_millis
1452.2847709995403
usercpu_time_millis
1475.4322299995692
usercpu_time_millis
1455.9621730004437
usercpu_time_millis
1471.4262260004034
usercpu_time_millis
1471.2415379999584
usercpu_time_millis
1476.1985140012257
usercpu_time_millis
1468.6595450020832
usercpu_time_millis
1464.3790280006215
usercpu_time_millis_testing
146.67451599962078
usercpu_time_millis_testing
145.5810890001885
usercpu_time_millis_testing
145.8024719995592
usercpu_time_millis_testing
153.91620499940473
usercpu_time_millis_testing
145.98325800034218
usercpu_time_millis_testing
153.2208589997026
usercpu_time_millis_testing
145.565925999108
usercpu_time_millis_testing
153.80578500116826
usercpu_time_millis_testing
145.23772500069754
usercpu_time_millis_testing
145.53971299937984
usercpu_time_millis_training
1522.1800050003367
usercpu_time_millis_training
1305.5007140010275
usercpu_time_millis_training
1306.4822989999811
usercpu_time_millis_training
1321.5160250001645
usercpu_time_millis_training
1309.9789150001016
usercpu_time_millis_training
1318.2053670007008
usercpu_time_millis_training
1325.6756120008504
usercpu_time_millis_training
1322.3927290000574
usercpu_time_millis_training
1323.4218200013856
usercpu_time_millis_training
1318.8393150012416