8978800
1
Jan van Rijn
9954
Supervised Classification
8330
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)(2)
6914381
axis
0
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categorical_features
[]
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copy
true
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fill_empty
0
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missing_values
"NaN"
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strategy
"most_frequent"
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strategy_nominal
"most_frequent"
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verbose
0
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categorical_features
[]
7105
dtype
{"oml-python:serialized_object": "type", "value": "np.float64"}
7105
handle_unknown
"ignore"
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n_values
"auto"
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sparse
true
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threshold
0.0
7106
C
752.5256692420229
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cache_size
200
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class_weight
null
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coef0
-0.0950558313714962
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decision_function_shape
null
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degree
2
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gamma
0.006833588566949055
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kernel
"sigmoid"
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max_iter
-1
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probability
true
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random_state
32584
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shrinking
false
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tol
0.06830658569213303
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verbose
false
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copy
true
7713
with_mean
false
7713
with_std
true
7713
openml-pimp
openml-python
Sklearn_0.18.1.
1491
one-hundred-plants-margin
https://www.openml.org/data/download/1592283/phpCsX3fx
-1
18872667
description
https://api.openml.org/data/download/18872667/description.xml
-1
18872668
predictions
https://api.openml.org/data/download/18872668/predictions.arff
area_under_roc_curve
0.9964768781565654 [0.98907,0.999882,1,0.999961,0.997988,0.994871,0.999842,0.999566,0.997909,0.999961,0.998343,0.999605,0.999684,0.98544,0.998461,0.999763,1,0.990688,0.984178,0.97455,0.99854,0.999448,0.997356,1,0.998146,0.974392,0.992937,0.999329,0.998816,1,0.999921,1,1,0.98986,0.999605,0.999132,0.99345,0.981297,0.999921,1,0.999369,0.999645,1,0.998935,0.997238,0.999803,0.999211,0.995739,0.997396,0.996291,0.994318,0.999171,0.998303,0.990096,0.997041,0.99203,1,0.999645,0.992464,0.996252,0.999171,0.999369,0.997435,0.99925,0.999448,0.99562,0.987926,1,0.998422,0.993845,0.995975,0.999566,0.996567,0.998264,0.98761,0.999605,0.999605,0.990688,1,1,0.99416,0.998146,0.997711,0.99566,0.99929,0.999763,1,0.99929,0.999605,1,0.999092,0.999014,0.998974,0.997317,0.997475,0.997435,0.997396,0.998264,0.967251,0.998619]
average_cost
0
f_measure
0.8264382033949981 [0.742857,0.9375,1,1,0.933333,0.827586,0.969697,0.967742,0.875,0.967742,0.774194,0.909091,0.909091,0.709677,0.914286,0.933333,1,0.533333,0.4,0.242424,0.8125,0.967742,0.888889,1,0.866667,0.424242,0.5625,0.848485,0.933333,0.896552,0.967742,1,1,0.5,0.903226,0.848485,0.529412,0.4375,0.909091,1,0.8,0.969697,1,0.875,0.785714,0.9375,0.83871,0.666667,0.764706,0.8125,0.75,0.827586,0.866667,0.705882,0.689655,0.625,1,0.9375,0.684211,0.764706,0.933333,0.848485,0.75,0.909091,0.909091,0.742857,0.580645,1,0.866667,0.685714,0.787879,0.896552,0.645161,0.967742,0.8,0.909091,0.9375,0.628571,1,1,0.774194,0.875,0.903226,0.482759,0.848485,0.967742,0.933333,0.875,0.967742,0.967742,0.823529,0.827586,0.909091,0.866667,0.9375,0.777778,0.8,0.742857,0.482759,0.9375]
kappa
0.8238636363636365
kb_relative_information_score
976.4353945316408
mean_absolute_error
0.016274931745061737
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
0.8325243233718463 [0.684211,0.9375,1,1,1,0.923077,0.941176,1,0.875,1,0.8,0.882353,0.882353,0.733333,0.842105,1,1,0.571429,0.368421,0.235294,0.8125,1,0.8,1,0.928571,0.411765,0.5625,0.823529,1,1,1,1,1,0.583333,0.933333,0.823529,0.5,0.4375,0.882353,1,0.736842,0.941176,1,0.875,0.916667,0.9375,0.866667,0.714286,0.722222,0.8125,0.75,0.923077,0.928571,0.666667,0.769231,0.625,1,0.9375,0.590909,0.722222,1,0.823529,0.75,0.882353,0.882353,0.684211,0.6,1,0.928571,0.631579,0.764706,1,0.666667,1,0.736842,0.882353,0.9375,0.578947,1,1,0.8,0.875,0.933333,0.538462,0.823529,1,1,0.875,1,1,0.777778,0.923077,0.882353,0.928571,0.9375,0.7,0.736842,0.684211,0.538462,0.9375]
predictive_accuracy
0.825625
prior_entropy
6.6438561897747395
recall
0.825625 [0.8125,0.9375,1,1,0.875,0.75,1,0.9375,0.875,0.9375,0.75,0.9375,0.9375,0.6875,1,0.875,1,0.5,0.4375,0.25,0.8125,0.9375,1,1,0.8125,0.4375,0.5625,0.875,0.875,0.8125,0.9375,1,1,0.4375,0.875,0.875,0.5625,0.4375,0.9375,1,0.875,1,1,0.875,0.6875,0.9375,0.8125,0.625,0.8125,0.8125,0.75,0.75,0.8125,0.75,0.625,0.625,1,0.9375,0.8125,0.8125,0.875,0.875,0.75,0.9375,0.9375,0.8125,0.5625,1,0.8125,0.75,0.8125,0.8125,0.625,0.9375,0.875,0.9375,0.9375,0.6875,1,1,0.75,0.875,0.875,0.4375,0.875,0.9375,0.875,0.875,0.9375,0.9375,0.875,0.75,0.9375,0.8125,0.9375,0.875,0.875,0.8125,0.4375,0.9375]
relative_absolute_error
0.8219662497505914
root_mean_prior_squared_error
0.09949874371066209
root_mean_squared_error
0.08331967259275316
root_relative_squared_error
0.8373942171073341
total_cost
0
area_under_roc_curve
0.9964040482445663 [0.993711,1,1,1,1,1,1,1,1,1,1,0.996835,1,0.996835,1,0.993711,1,0.990506,0.984177,0.987421,0.993711,1,1,1,1,0.996835,0.996835,1,1,1,1,1,1,0.990506,1,0.993711,1,0.993711,1,1,1,1,1,1,1,1,1,1,1,0.977848,1,1,1,1,0.993711,1,1,1,1,1,1,1,1,1,1,1,0.974684,1,1,0.968553,0.993671,1,1,1,1,1,1,0.955696,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.996835,1,0.987342,0.987421,0.996835,0.924051,1]
area_under_roc_curve
0.9966008379109944 [1,1,1,1,1,1,1,1,0.996835,1,1,1,1,0.917722,1,1,1,0.981013,0.993671,1,1,1,0.993711,1,1,0.974684,0.974684,1,1,1,1,1,1,0.996835,1,1,0.987421,0.993711,1,1,1,1,1,1,1,1,1,1,0.996835,1,1,1,1,0.996835,1,0.993711,1,1,1,0.993671,1,1,1,1,1,0.996835,1,1,1,1,0.993671,1,1,1,1,1,1,0.993671,1,1,0.974684,0.996835,1,0.987421,0.996835,1,1,0.996835,1,1,1,1,1,0.993671,1,1,1,0.996835,1,0.974843]
area_under_roc_curve
0.9968769902873973 [1,1,1,1,1,1,1,0.996835,0.996835,1,1,1,1,0.993671,0.990506,1,1,0.993671,1,0.943038,1,1,0.996835,1,1,0.933544,1,1,1,1,1,1,1,0.984177,1,1,0.993711,1,1,1,0.996835,0.993711,1,1,1,1,1,0.993711,0.996835,1,1,1,1,1,1,0.996835,1,1,0.981132,0.984177,1,1,1,0.987421,1,0.996835,1,1,1,0.984177,1,0.996835,1,1,1,1,1,0.996835,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.996835,1,1,1,1,1]
area_under_roc_curve
0.9967219966563171 [1,1,1,1,0.996835,0.993671,1,1,0.996835,1,1,1,1,1,1,1,1,0.987342,0.943396,0.968354,1,1,1,1,0.993711,0.984177,1,1,1,1,1,1,1,0.993671,1,1,1,0.968553,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.981013,1,0.981013,1,1,0.993711,1,1,1,1,1,1,0.996835,0.987342,1,1,0.981013,0.971519,1,0.981132,1,0.993711,1,1,0.996835,1,1,1,1,0.993671,0.996835,1,1,1,1,1,1,1,1,0.993711,1,1,1,0.996835,1,1,1]
area_under_roc_curve
0.9964453467080647 [1,1,1,1,1,0.993671,1,1,1,1,0.993671,1,1,0.974843,0.993711,1,1,0.990506,0.987421,0.990506,1,1,1,1,0.996835,0.993671,0.993671,1,1,1,1,1,1,0.977848,1,1,0.990506,0.984177,1,1,1,1,1,1,0.993711,1,1,1,1,1,1,0.987421,1,1,0.990506,0.996835,1,0.996835,1,1,1,1,0.993711,1,1,1,1,1,0.996835,1,1,1,1,1,0.946203,1,0.993671,1,1,1,1,1,1,0.987342,0.993711,0.993711,1,1,1,1,1,0.996835,1,1,0.974684,0.993711,1,1,0.949686,1]
area_under_roc_curve
0.9957300871745881 [0.920886,1,1,1,1,0.984177,1,1,1,1,1,1,1,0.993711,1,1,1,1,1,0.955696,1,1,1,1,0.993671,0.987342,0.987342,1,1,1,1,1,1,0.993671,1,0.993671,0.996835,0.96519,1,1,0.996835,1,1,1,1,1,1,0.996835,0.993671,0.996835,1,1,1,1,1,0.990506,1,1,0.993671,1,0.990506,1,0.993711,1,1,0.981013,1,1,0.996835,1,1,1,1,1,0.987342,1,1,1,1,1,0.987421,0.993671,1,0.993671,1,1,1,1,1,1,1,0.996835,1,1,1,1,1,1,0.968553,1]
area_under_roc_curve
0.995340737202452 [1,1,1,1,1,1,1,1,0.993711,1,1,1,1,1,1,1,1,0.993711,0.993671,0.968354,1,1,0.990506,1,1,0.880503,0.974843,0.993671,1,1,0.996835,1,1,0.987421,1,1,0.977848,0.993671,1,1,1,1,1,1,0.974843,0.996835,1,0.990506,1,1,0.993711,1,1,1,1,1,1,1,0.987342,1,1,1,1,0.996835,1,0.993711,1,1,0.996835,1,1,1,0.996835,1,1,1,1,0.993711,1,1,0.968354,1,1,1,1,1,1,1,1,1,1,1,0.993671,1,1,0.996835,1,1,0.89557,1]
area_under_roc_curve
0.9976337970702968 [0.996835,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.993711,0.987342,1,1,1,1,1,0.993671,0.993711,1,1,0.974843,1,1,1,1,1,1,1,0.987342,0.993671,1,1,1,1,1,1,1,1,1,0.990506,1,0.987421,0.955975,1,0.996835,1,1,0.984177,1,1,0.993671,1,1,1,1,1,1,0.974843,0.955975,1,1,0.996835,1,1,1,1,1,1,1,0.981132,1,1,0.993671,1,0.993671,1,1,1,1,1,1,1,1,1,1,1,1,0.993671,1,1,1,1]
area_under_roc_curve
0.9971178150624948 [1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.987421,0.990506,0.955975,1,1,0.993711,1,1,0.987421,0.993711,1,1,1,1,1,1,0.993711,1,1,1,0.943038,1,1,1,1,1,0.993671,1,1,1,0.993671,0.993711,1,0.990506,1,1,0.958861,0.996835,0.981132,1,1,1,1,1,1,1,1,1,1,0.984177,1,0.996835,1,1,0.993711,0.990506,1,1,1,1,0.993711,1,1,1,1,1,0.987421,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1]
area_under_roc_curve
0.9976300652814265 [0.993711,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.971519,0.987421,1,1,1,1,1,1,1,0.996835,1,1,1,1,1,0.993711,1,0.993671,0.996835,1,1,1,1,1,1,1,0.996835,1,1,1,0.993711,1,1,1,1,0.996835,0.996835,1,1,1,0.987342,1,1,1,0.981013,1,0.993711,0.993711,0.993671,1,1,1,1,1,0.993671,0.990506,1,0.993671,1,1,1,1,1,0.968553,1,0.993711,1,1,1,0.993671,1,1,0.993671,1,1,0.987342,1,1,0.993711,0.990506,1,1]
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
0.7978681405448086
kappa
0.842040832444813
kappa
0.8862873613140126
kappa
0.8168252339031227
kappa
0.8041615667074664
kappa
0.797876120168963
kappa
0.8104789355233545
kappa
0.8293906243829233
kappa
0.8610233733417562
kappa
0.7916008841174613
kb_relative_information_score
97.82616061210243
kb_relative_information_score
96.94716490831644
kb_relative_information_score
98.00717710222014
kb_relative_information_score
96.88617222986475
kb_relative_information_score
96.77070664486537
kb_relative_information_score
95.89837464925382
kb_relative_information_score
99.50168866790281
kb_relative_information_score
97.78579877919182
kb_relative_information_score
98.46463459685205
kb_relative_information_score
98.34751634107117
mean_absolute_error
0.016171039605225465
mean_absolute_error
0.01636799770006529
mean_absolute_error
0.016273133400800548
mean_absolute_error
0.016371552803902602
mean_absolute_error
0.016397638289088648
mean_absolute_error
0.016451173378614858
mean_absolute_error
0.016051916206766628
mean_absolute_error
0.016240043099385926
mean_absolute_error
0.01620006835208831
mean_absolute_error
0.01622475461467917
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
0.8
predictive_accuracy
0.84375
predictive_accuracy
0.8875
predictive_accuracy
0.81875
predictive_accuracy
0.80625
predictive_accuracy
0.8
predictive_accuracy
0.8125
predictive_accuracy
0.83125
predictive_accuracy
0.8625
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
0.8 [1,0.5,1,1,0.5,1,1,1,1,1,0.5,1,1,0,1,0,1,0.5,0,0,0,1,1,1,1,0.5,0.5,1,1,0,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,0.5,1,1,0,1,1,1,1,1,1,1,0.5,1,1,1,0,1,1,0,1,1,1,1,1,1,0.5,0,1,1,1,1,1,1,1,1,0.5,1,0.5,1,1,1,1,1,1,0.5,0,1,0,1]
recall
0.84375 [1,1,1,1,1,1,1,1,1,1,0.5,1,1,0.5,1,1,1,0.5,0.5,1,1,1,1,1,1,0.5,0,1,1,1,1,1,1,1,0.5,0,0,0,1,1,1,1,1,0.5,1,1,1,1,0.5,1,1,1,1,0.5,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,0,1,1,0,0.5,1,1,1,1,1,0.5,1,1,0.5,1,1,1,1,0.5,0]
recall
0.8875 [1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,0.5,1,0,1,1,1,1,1,0.5,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,0.5,1,1,1,0.5,1,0.5,1,0.5,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,0,1,0,1,1,1,1,1,1,0,1]
recall
0.81875 [0.5,1,1,1,0.5,0.5,1,1,0.5,1,1,0.5,1,0.5,1,1,1,0.5,0,0.5,1,1,1,1,0,0,1,1,1,1,1,1,1,0.5,1,1,1,0,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,0.5,1,0.5,1,1,1,1,1,1,1,1,0.5,0.5,0.5,1,1,0.5,0,1,0,1,1,1,1,0.5,1,1,1,1,0.5,0.5,1,1,1,1,1,1,1,1,1,1,1,1,0.5,0.5,1,1]
recall
0.80625 [1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,0,1,0.5,0.5,1,1,1,1,1,0.5,1,1,0.5,1,1,1,0,1,1,0,0,1,1,1,1,1,0,0,1,1,0.5,1,1,0,0,0.5,1,0,0.5,1,1,1,1,1,1,0,1,1,1,1,1,0.5,0.5,1,1,1,1,0.5,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,0.5,1,0,0.5,1,1,1,0,1]
recall
0.8 [0.5,1,1,1,1,0.5,1,0.5,1,0.5,1,1,0,1,1,1,1,0.5,1,0,1,0.5,1,1,1,1,0.5,0,1,1,1,1,1,0.5,1,0.5,0.5,0,1,1,1,1,1,1,1,1,1,0.5,0.5,0.5,1,1,0.5,1,1,1,1,1,0.5,1,1,0.5,1,1,1,0.5,1,1,0.5,1,0.5,0.5,1,1,0.5,1,1,0.5,1,1,1,0.5,1,0.5,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,0,1]
recall
0.8125 [1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,0.5,1,1,0,0,1,1,1,1,1,0,0,0.5,1,1,0.5,1,1,0,1,1,0.5,0.5,1,1,1,1,1,1,0,0.5,0,0,1,1,1,1,1,1,0.5,0.5,1,1,0,1,1,0.5,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,0,1,1,1,1,0.5,1,1,1,1,1,0,1]
recall
0.83125 [0.5,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,0,0.5,1,1,1,0.5,0,1,1,0,0.5,1,1,1,1,1,1,0.5,1,1,1,0.5,1,1,1,0,1,1,0.5,1,0,0,0.5,0.5,1,1,0.5,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,0,1,1,0.5,1,0.5,0.5,0.5,0.5,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1]
recall
0.8625 [1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,0,0.5,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,0,0.5,1,1,1,1,1,1,1,1,0.5,1,1,0.5,1,1,0.5,0.5,0,1,0,1,1,0.5,1,1,1,1,1,0.5,1,1,1,1,0,0.5,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0.5,1,1,1,1,0.5,1,1,0.5,1]
recall
0.79375 [1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,0,1,1,1,1,1,0.5,0,0,1,0.5,1,1,1,1,0,0.5,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,0.5,1,0.5,0.5,1,1,1,1,0.5,0.5,1,0,1,1,1,0,1,0.5,1,1,0,0,0.5,1,0.5,1,1,1,1,1,0,1,0,1,1,0.5,0.5,1,1,1,1,1,0.5,1,1,1,0,1,1]
relative_absolute_error
0.8167191719810828
relative_absolute_error
0.8266665505083465
relative_absolute_error
0.8218754242828545
relative_absolute_error
0.8268461012072008
relative_absolute_error
0.8281635499539708
relative_absolute_error
0.8308673423542844
relative_absolute_error
0.8107028387255859
relative_absolute_error
0.8202041969386817
relative_absolute_error
0.8181852703074891
relative_absolute_error
0.8194320512464214
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
0.08290362636116666
root_mean_squared_error
0.08365044030823199
root_mean_squared_error
0.08325792569557705
root_mean_squared_error
0.08378227044139049
root_mean_squared_error
0.08393468762971665
root_mean_squared_error
0.08421048352320779
root_mean_squared_error
0.08227035694920848
root_mean_squared_error
0.08312805771417134
root_mean_squared_error
0.08289336617855998
root_mean_squared_error
0.0831473803531661
root_relative_squared_error
0.8332127951509289
root_relative_squared_error
0.8407185577285656
root_relative_squared_error
0.8367736374409652
root_relative_squared_error
0.8420435004187151
root_relative_squared_error
0.8435753507983478
root_relative_squared_error
0.8463472038208657
root_relative_squared_error
0.8268481980882797
root_relative_squared_error
0.8354684151179239
root_relative_squared_error
0.8331096764358173
root_relative_squared_error
0.8356626149467274
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
1609.8183789999894
usercpu_time_millis
1456.444936999958
usercpu_time_millis
1449.5724689999747
usercpu_time_millis
1453.1645819999994
usercpu_time_millis
1460.173568000016
usercpu_time_millis
1477.4666669999874
usercpu_time_millis
1513.2636220000109
usercpu_time_millis
1483.7443970000095
usercpu_time_millis
1466.2144079999848
usercpu_time_millis
1455.5525959999613
usercpu_time_millis_testing
172.95942100003003
usercpu_time_millis_testing
165.0268980000078
usercpu_time_millis_testing
166.3614349999989
usercpu_time_millis_testing
163.9652910000109
usercpu_time_millis_testing
170.1335910000239
usercpu_time_millis_testing
171.21004299997367
usercpu_time_millis_testing
170.72124700001723
usercpu_time_millis_testing
164.88537300000417
usercpu_time_millis_testing
170.8837909999943
usercpu_time_millis_testing
165.1152169999932
usercpu_time_millis_training
1436.8589579999593
usercpu_time_millis_training
1291.41803899995
usercpu_time_millis_training
1283.2110339999758
usercpu_time_millis_training
1289.1992909999885
usercpu_time_millis_training
1290.0399769999922
usercpu_time_millis_training
1306.2566240000137
usercpu_time_millis_training
1342.5423749999936
usercpu_time_millis_training
1318.8590240000053
usercpu_time_millis_training
1295.3306169999905
usercpu_time_millis_training
1290.4373789999681