8832409
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)
6807459
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
[]
7661
dtype
{"oml-python:serialized_object": "type", "value": "np.float64"}
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handle_unknown
"ignore"
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n_values
"auto"
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sparse
true
7661
threshold
0.0
7662
copy
true
7663
with_mean
false
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with_std
true
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C
0.8303865226317884
7708
cache_size
200
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class_weight
null
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coef0
0.5965833577366391
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decision_function_shape
null
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degree
5
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gamma
0.001804239661055018
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kernel
"poly"
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max_iter
-1
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probability
true
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random_state
10155
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shrinking
false
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tol
0.00040225916292384165
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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
18580582
description
https://api.openml.org/data/download/18580582/description.xml
-1
18580583
predictions
https://api.openml.org/data/download/18580583/predictions.arff
area_under_roc_curve
0.9719949494949494 [0.906645,0.996922,1,0.999803,0.998382,0.990451,0.998658,0.999408,0.993332,1,0.997751,0.999132,0.979601,0.965554,0.999684,0.961687,1,0.915956,0.949574,0.901594,0.974077,0.997988,0.974747,0.999487,0.989386,0.938565,0.909249,0.986545,0.983428,0.993766,0.998382,0.999882,0.866832,0.983112,0.975221,0.992977,0.968,0.92586,0.998382,0.999448,0.922191,0.992977,1,0.968829,0.997041,0.900568,0.997633,0.990609,0.976918,0.972696,0.93383,0.99491,0.985283,0.922506,0.990136,0.952375,1,0.99779,0.975537,0.944089,0.987374,0.878275,0.988834,0.991556,0.997435,0.977549,0.88084,0.999961,0.985638,0.966974,0.925545,0.996094,0.969973,0.997277,0.957939,0.993924,0.997396,0.888336,0.997633,0.998935,0.949653,0.990412,0.978733,0.976681,0.965593,0.9927,0.999921,0.976286,0.963936,0.987768,0.929411,0.999645,0.995462,0.967764,0.974235,0.989583,0.961056,0.990254,0.841896,0.965633]
average_cost
0
kappa
0.5145202020202021
kb_relative_information_score
646.5274459708766
mean_absolute_error
0.018139661856765143
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]
predictive_accuracy
0.519375
prior_entropy
6.6438561897747395
recall
0.519375 [0,0.75,1,0.875,0.875,0.625,1,1,0.5,0.875,0.9375,1,0.25,0.625,0.9375,0.625,1,0,0,0,0.5625,0.9375,0.0625,1,0.6875,0,0.125,0.5625,0.375,1,0.875,0.9375,0.125,0.25,0.3125,1,0.1875,0.0625,0.9375,0.9375,0.1875,0.8125,1,0.25,0.9375,0.25,0.75,0.5625,0.3125,0.25,0.0625,0.8125,0.25,0.0625,0.1875,0,1,0.75,0.875,0.25,0.6875,0.25,0.125,0.625,0.9375,0.375,0,1,0.4375,0.375,0.0625,0.625,0.1875,0.9375,0.25,0.5625,1,0.0625,0.9375,0.9375,0.25,0.625,0.375,0.1875,0.125,0.625,0.875,0.125,0.375,0.375,0.1875,0.75,0.75,0.1875,0.6875,0.625,0.25,0.5625,0.0625,0.1875]
relative_absolute_error
0.9161445382204602
root_mean_prior_squared_error
0.09949874371066209
root_mean_squared_error
0.0925794521742909
root_relative_squared_error
0.9304585035114394
total_cost
0
area_under_roc_curve
0.9752654545816417 [0.886792,1,1,1,1,1,1,1,0.993671,1,1,0.996835,0.974684,0.93038,1,0.949686,1,0.955696,0.939873,0.861635,0.962264,1,1,1,0.987421,0.927215,0.911392,0.996835,0.993671,0.981132,1,1,0.870253,0.984177,0.984177,0.993711,1,0.943396,1,1,0.987421,0.987421,1,0.981013,1,0.898734,1,1,0.987342,0.943038,0.924051,1,0.987421,0.952532,0.987421,0.981132,1,1,0.993711,0.924051,0.993711,0.968553,0.987342,0.993671,1,0.977848,0.917722,1,1,0.918239,0.901899,1,0.990506,1,1,1,1,0.882911,1,0.996835,1,0.996835,0.993711,0.993711,0.974684,0.996835,1,0.993671,0.962025,0.993711,0.927215,1,1,0.977848,0.981013,0.987342,0.949686,0.981013,0.879747,0.987421]
area_under_roc_curve
0.9733649789029538 [0.949686,1,1,1,1,1,1,1,0.993671,1,0.996835,1,0.987342,0.882911,1,1,1,0.958861,0.962025,0.886792,1,1,0.962264,1,1,0.955696,0.89557,0.993671,0.987342,1,1,1,0.876582,0.987342,0.96519,0.993711,0.993711,0.91195,1,1,0.974843,0.993711,1,0.96519,1,0.892405,1,1,0.987342,0.981013,0.93038,0.990506,1,0.93038,0.993711,0.943396,1,1,0.962264,0.949367,0.993711,0.930818,0.993671,0.990506,1,0.981013,0.873418,1,0.955975,0.987421,0.924051,1,0.971519,1,1,1,0.996835,0.892405,0.993671,1,0.933544,0.987342,1,0.968553,0.987342,1,1,0.993671,0.974684,1,0.96519,1,0.996835,0.927215,0.981013,0.993671,0.955975,0.981013,0.794304,0.974843]
area_under_roc_curve
0.9795338746915055 [0.949367,0.996835,1,1,1,0.993671,0.993711,1,0.990506,1,1,1,0.987421,0.996835,1,0.984177,1,0.892405,0.955975,0.962025,0.955975,0.981132,0.968354,1,0.993711,0.955696,0.889241,0.993711,0.990506,1,1,1,0.85443,0.977848,0.987421,1,0.955975,0.937107,0.993711,0.996835,0.955696,0.981132,1,1,1,0.937107,1,0.987421,0.987342,0.990506,0.974684,1,0.993711,0.968354,1,0.974684,1,0.993671,0.949686,0.977848,0.993711,0.974843,0.996835,0.974843,0.996835,0.96519,0.908228,1,0.993711,0.968354,0.968354,0.990506,1,1,0.987421,0.996835,1,0.962025,0.990506,1,0.968553,0.981013,0.987342,0.96519,1,1,1,0.996835,0.968354,0.981132,0.911392,1,1,0.971519,0.977848,1,0.977848,0.993671,0.924528,0.974684]
area_under_roc_curve
0.9767678727808295 [0.933544,0.996835,1,1,0.996835,0.987342,1,1,0.987342,1,0.996835,1,0.987421,0.990506,1,0.987342,1,0.924051,0.886792,0.936709,1,1,0.990506,1,0.981132,0.93038,0.892405,1,0.996835,1,1,1,0.860759,0.987342,0.993711,1,0.981132,0.968553,1,1,0.96519,1,1,1,1,0.955975,0.996835,1,0.984177,0.993671,0.984177,1,0.993711,0.939873,1,0.952532,1,1,0.955975,0.936709,0.987421,0.974843,0.990506,1,0.996835,0.987342,0.908228,1,1,0.943038,0.920886,0.996835,0.974843,1,0.974843,1,1,0.876582,1,1,0.949686,0.984177,0.974684,0.984177,1,1,1,0.993671,0.996835,1,0.920886,1,0.981132,0.996835,0.987342,0.993711,0.939873,0.981013,0.767296,0.958861]
area_under_roc_curve
0.9743561420269085 [0.958861,1,1,1,1,1,1,1,0.987421,1,0.990506,1,0.993711,0.943396,1,0.946203,1,0.939873,0.918239,0.882911,0.984177,1,0.987342,1,0.993671,0.920886,0.901899,1,0.993711,1,1,1,0.810127,0.977848,0.981132,1,0.955696,0.892405,0.996835,1,0.958861,0.996835,1,0.993711,1,0.955975,1,1,0.996835,0.981013,0.981132,0.981132,1,1,0.996835,0.955696,1,0.996835,0.974684,0.981132,0.974684,0.835443,0.981132,1,1,1,0.943396,1,0.984177,0.990506,0.920886,1,1,1,0.835443,1,0.990506,0.911392,1,1,0.968553,0.996835,0.990506,0.96519,0.981132,0.987421,1,1,0.987342,0.990506,0.930818,1,1,0.955975,0.96519,0.993711,0.987342,1,0.823899,0.987342]
area_under_roc_curve
0.9724932330228484 [0.889241,1,1,1,1,0.971519,1,1,1,1,1,1,0.974843,0.987421,1,0.977848,1,0.914557,0.962264,0.876582,0.96519,0.981013,0.984177,1,0.968354,0.917722,0.901899,1,1,1,1,1,0.863924,0.993671,0.937107,0.993671,0.971519,0.911392,0.996835,1,0.927215,0.996835,1,0.974843,1,0.955975,1,0.977848,0.990506,0.990506,0.987421,1,0.984177,0.968553,0.981013,0.927215,1,1,0.987342,0.987421,0.977848,0.85443,0.981132,1,1,0.977848,0.886792,1,0.990506,0.981013,0.908228,0.993671,1,1,0.974684,1,1,0.822785,1,1,0.949686,1,0.987342,0.955696,1,1,1,0.993711,0.955696,0.990506,0.968553,1,0.993711,1,0.984177,1,0.962025,1,0.861635,0.955696]
area_under_roc_curve
0.9767743412148713 [0.936709,1,1,1,1,1,1,1,0.993711,1,1,1,0.968354,1,1,0.924051,1,0.861635,0.987342,0.873418,0.996835,1,0.936709,1,0.990506,0.899371,0.974843,0.984177,1,0.987342,0.993671,1,0.886792,0.981132,0.987342,1,0.958861,0.920886,1,1,0.939873,0.987342,1,0.987342,0.974843,0.939873,0.993671,0.981013,0.981132,0.987421,0.949686,1,0.981013,0.968553,0.984177,0.952532,1,1,0.977848,1,0.993671,0.81962,1,0.993671,1,0.974843,0.924528,1,0.987342,0.996835,0.987421,1,0.984177,1,0.987342,1,1,0.867925,1,1,0.89557,1,0.971519,0.977848,0.987342,1,1,1,0.987421,0.981013,0.974843,1,0.990506,0.987421,1,1,0.952532,0.981132,0.898734,0.981013]
area_under_roc_curve
0.9775316455696199 [0.977848,1,1,1,1,1,0.996835,1,0.987421,1,1,1,0.958861,1,1,0.962025,1,0.861635,0.958861,0.936709,0.987342,1,0.987342,1,1,0.962264,0.955975,0.996835,0.918239,0.987342,1,1,0.90566,1,0.974684,1,0.939873,0.920886,1,1,0.867089,0.993671,1,0.981013,0.993711,0.914557,1,0.996835,0.981132,0.949686,0.842767,0.996835,0.987342,0.987421,0.996835,0.936709,1,1,0.962025,0.943396,0.990506,0.844937,0.993711,1,1,0.955975,0.805031,1,0.990506,0.990506,0.981132,1,0.996835,1,0.981013,0.993711,1,1,1,1,0.955696,1,0.974684,0.977848,0.977848,0.993671,1,1,0.993711,0.990506,0.987421,1,1,1,1,0.993671,0.974684,1,0.892405,0.958861]
area_under_roc_curve
0.9794604828437222 [0.943396,0.990506,1,1,1,1,1,1,0.990506,1,0.993711,1,0.993671,0.993671,1,1,1,0.924528,0.968354,0.893082,0.990506,1,0.955975,0.993671,1,0.974843,0.943396,0.996835,1,1,1,1,0.899371,0.987421,0.987342,1,0.96519,0.949367,1,1,1,1,1,0.974684,1,0.873418,1,0.987342,0.981132,0.974843,0.952532,0.996835,0.990506,0.908228,0.990506,0.918239,1,1,0.987342,0.990506,0.990506,0.892405,0.996835,0.993671,1,0.987421,0.860759,1,0.993671,0.993711,0.968553,0.987421,0.917722,1,0.990506,0.996835,1,0.981132,0.993711,1,0.968354,0.993711,0.993711,0.987421,0.977848,1,1,0.993671,1,0.987342,0.917722,1,0.993671,0.974684,0.981132,0.958861,0.981132,1,0.860759,1]
area_under_roc_curve
0.97894499840777 [0.955975,0.993671,1,1,1,1,1,1,0.993671,1,1,1,0.977848,0.984177,1,0.981132,1,0.962264,0.958861,0.893082,0.939873,1,1,1,0.996835,0.981132,0.962264,0.990506,0.993671,0.993711,1,1,0.849057,1,0.987342,0.993671,0.981013,0.927215,1,1,1,0.987342,1,0.984177,0.996835,0.958861,1,0.996835,0.981132,0.987421,0.974684,1,0.987342,0.924051,0.996835,0.955975,1,1,0.968354,0.911392,0.993671,0.914557,0.987342,0.993671,0.993711,0.968553,0.886076,1,1,1,0.974843,1,1,0.987342,0.96519,0.984177,1,0.937107,1,1,0.990506,0.974843,0.987421,0.993711,0.981013,1,1,0.977848,1,0.981013,0.886076,1,1,0.977848,1,0.987342,0.943396,0.987342,0.794304,0.993711]
average_cost
0
average_cost
0
average_cost
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average_cost
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average_cost
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average_cost
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average_cost
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average_cost
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average_cost
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average_cost
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kappa
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kappa
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kappa
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kappa
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kappa
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kappa
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kappa
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kappa
0.5331414376404716
kappa
0.5017344686218859
kappa
0.5142338932260864
kb_relative_information_score
64.0652247042145
kb_relative_information_score
64.41630969329955
kb_relative_information_score
64.60388485361051
kb_relative_information_score
63.598500252792526
kb_relative_information_score
64.00052788674495
kb_relative_information_score
64.73402886639599
kb_relative_information_score
65.98696747115216
kb_relative_information_score
64.57600082833721
kb_relative_information_score
64.80132568496185
kb_relative_information_score
65.74467572936828
mean_absolute_error
0.018110113658516596
mean_absolute_error
0.01813299616228941
mean_absolute_error
0.018183693374284386
mean_absolute_error
0.018294182152196622
mean_absolute_error
0.0182451297222698
mean_absolute_error
0.018122925225806694
mean_absolute_error
0.017984985375378716
mean_absolute_error
0.01822906431444115
mean_absolute_error
0.018091712334452333
mean_absolute_error
0.018001816248015813
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
0.50625
predictive_accuracy
0.5
predictive_accuracy
0.525
predictive_accuracy
0.5
predictive_accuracy
0.55
predictive_accuracy
0.53125
predictive_accuracy
0.51875
predictive_accuracy
0.5375
predictive_accuracy
0.50625
predictive_accuracy
0.51875
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
0.50625 [0,0.5,1,0,0.5,1,1,1,0,1,0.5,1,0,0,1,1,1,0,0,0,1,1,0,1,0,0,0,1,0.5,1,1,1,0,0.5,0,1,0,0,1,1,1,1,1,0,1,0,1,1,0.5,0,0,1,1,0,1,0,1,1,1,0,1,1,0,0,1,0.5,0,1,1,1,0,1,0,1,0,0.5,1,0,1,1,0,1,1,1,0,0,0.5,0,0,1,0,1,0.5,0,1,0,1,1,0,1]
recall
0.5 [0,0.5,1,0,1,1,1,1,0.5,1,1,1,0,0.5,1,1,1,0,0,0,1,1,0,1,1,0,0,0.5,1,1,1,1,0,0,0.5,1,0,1,1,1,1,1,1,0,1,0,1,1,0,0,0,0.5,1,0,0,0,1,1,1,0.5,1,1,0,0.5,1,0,0,1,1,1,0,1,0,1,0,0,1,0,1,1,0,0.5,1,0,0,0,1,0,0,1,0,1,0.5,0,0.5,0.5,0,0.5,0,0]
recall
0.525 [0,0.5,1,1,1,1,1,1,0.5,1,1,1,1,1,1,0.5,1,0,0,0,1,1,0,1,1,0,0,1,0,1,1,1,0,0.5,1,1,0,0,1,0.5,0,1,1,1,1,1,0.5,1,0,0,0,1,0,0,0,0,1,0.5,1,0,1,1,0,1,1,0.5,0,1,1,0.5,0,0.5,0,1,1,0.5,1,0,0.5,1,1,0.5,0.5,0,1,1,1,0,0,1,0,0,1,0,0.5,1,0,0.5,0,0]
recall
0.5 [0,0.5,1,1,0.5,1,1,1,0,0.5,1,1,1,0.5,1,0,1,0,0,0,1,1,0,1,0,0,0,1,0,1,1,1,0,0,1,1,0,0,1,1,0,1,1,1,1,1,0.5,1,0,0,0,1,1,0,0,0,1,0.5,1,0,1,1,0,1,1,0,0,1,1,0.5,0,0.5,1,1,1,0.5,1,0,1,1,1,0,0.5,0,0,1,1,0,0,1,0,1,1,0,0.5,1,0.5,0.5,0,0]
recall
0.55 [0,1,1,1,1,0.5,1,1,1,1,1,1,0,0,1,1,1,0,0,0,0.5,1,0,1,1,0,0,1,1,1,1,1,0,0.5,1,1,0.5,0,1,1,0,0.5,1,1,1,1,1,0,0,0,0,0,0,0,0,0,1,0.5,1,1,0.5,0,0,1,1,0,0,1,0,0,0,1,1,1,0.5,1,1,0,1,1,1,1,0,0,1,1,1,1,0.5,0,0,0.5,1,1,0.5,1,0,1,1,0]
recall
0.53125 [0,1,1,1,1,0,1,1,1,0.5,1,1,0,1,1,0.5,1,0,0,0,1,0.5,0,1,1,0,0,1,1,1,1,1,0,0,1,1,0,0,1,1,0,1,1,1,1,1,1,0,0,0,0,1,0,0,0.5,0,1,1,1,1,1,0,1,1,1,0,0,1,0,0,0,0.5,1,1,0,1,1,0,1,1,1,0.5,0,0,0,1,1,1,0.5,0,1,0,1,1,0.5,1,0,1,0,0]
recall
0.51875 [0,1,1,1,1,0,1,1,1,1,1,1,0,1,1,1,1,0,0,0,0,1,0.5,1,0.5,0,0,0,1,1,0.5,0,1,1,0,1,0.5,0,1,1,0,0.5,1,0,0,0,0,0.5,1,1,1,1,0,0,0,0,1,0.5,1,0,0.5,0,0,0.5,1,1,0,1,1,0,1,1,0,1,0,1,1,1,1,1,0,1,0,0,0,1,1,0,1,0.5,1,1,0,1,1,0.5,0,1,0,0]
recall
0.5375 [0,1,1,1,1,0.5,1,1,1,1,1,1,1,1,0,0,1,0,0,0,0.5,1,0,1,0.5,0,1,0,0,1,0.5,1,0,0,0,1,0.5,0,1,1,0,1,1,0,1,0,1,1,1,1,0,0.5,0,1,0,0,1,1,1,1,0.5,0,1,0.5,0.5,1,0,1,0.5,0,0,0.5,0,1,0.5,1,1,0,1,1,0,1,0,0.5,0,0.5,1,0,1,0,1,1,1,0,1,1,0,1,0,0]
recall
0.50625 [0,1,1,1,1,1,1,1,0.5,1,1,1,0,1,1,1,1,0,0,0,0,1,0,1,0.5,0,1,0,0,1,1,1,0,0,0,1,0,0,0.5,1,0,1,1,0,1,0,1,0,1,1,0,1,0,0,0.5,0,1,1,0,0,0.5,0,0,0.5,1,1,0,1,0,1,0,0,0,1,0,1,1,0,1,0.5,0,1,1,1,0,1,1,0,1,0.5,0,1,1,0,1,0.5,1,0,0,1]
recall
0.51875 [0,1,1,1,1,1,1,1,0.5,1,1,1,0,0.5,1,1,1,0,0,0,0.5,1,0,1,1,0,0,1,0,1,1,1,1,0,0,1,0,0,1,1,1,0.5,1,0,1,0,1,1,1,1,0,1,0.5,0,0,0,1,1,1,0,0.5,0,0,1,1,1,0,1,0,1,0,0,0,0.5,0,0,1,0,1,1,0,0,1,0,0,0.5,0.5,0,1,0,0,1,1,0,1,0.5,1,0,0,1]
relative_absolute_error
0.9146522049755841
relative_absolute_error
0.915807886984312
relative_absolute_error
0.9183683522365836
relative_absolute_error
0.9239485935452825
relative_absolute_error
0.9214711980944327
relative_absolute_error
0.9152992538286194
relative_absolute_error
0.9083325947160954
relative_absolute_error
0.9206598138606625
relative_absolute_error
0.9137228451743588
relative_absolute_error
0.9091826387886759
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
0.09250974367382228
root_mean_squared_error
0.09245918846383451
root_mean_squared_error
0.0927115758339801
root_mean_squared_error
0.09309371249763965
root_mean_squared_error
0.09288085568947005
root_mean_squared_error
0.09257375007652796
root_mean_squared_error
0.09203065673624178
root_mean_squared_error
0.09272646880254362
root_mean_squared_error
0.09260286293988143
root_mean_squared_error
0.09220106976235484
root_relative_squared_error
0.9297579067212801
root_relative_squared_error
0.9292498077433193
root_relative_squared_error
0.9317863962542207
root_relative_squared_error
0.935627014229969
root_relative_squared_error
0.933487722815511
root_relative_squared_error
0.9304011952726592
root_relative_squared_error
0.9249429018306285
root_relative_squared_error
0.9319360762200987
root_relative_squared_error
0.9306937905584662
root_relative_squared_error
0.9266556171851925
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
1970.6821919990034
usercpu_time_millis
2035.119747999488
usercpu_time_millis
1995.9480720008287
usercpu_time_millis
1964.3899009988672
usercpu_time_millis
1986.2537829994835
usercpu_time_millis
1995.3051709999272
usercpu_time_millis
1994.7501180013205
usercpu_time_millis
1987.139427999864
usercpu_time_millis
1988.1742279994796
usercpu_time_millis
1992.19316700146
usercpu_time_millis_testing
157.32792500057258
usercpu_time_millis_testing
158.36207900065347
usercpu_time_millis_testing
158.14787999988766
usercpu_time_millis_testing
153.4796389987605
usercpu_time_millis_testing
159.1585579990351
usercpu_time_millis_testing
154.03565400083608
usercpu_time_millis_testing
162.71975000017846
usercpu_time_millis_testing
153.40501900027448
usercpu_time_millis_testing
151.56922999995004
usercpu_time_millis_testing
154.2719040007796
usercpu_time_millis_training
1813.3542669984308
usercpu_time_millis_training
1876.7576689988346
usercpu_time_millis_training
1837.800192000941
usercpu_time_millis_training
1810.9102620001067
usercpu_time_millis_training
1827.0952250004484
usercpu_time_millis_training
1841.2695169990911
usercpu_time_millis_training
1832.030368001142
usercpu_time_millis_training
1833.7344089995895
usercpu_time_millis_training
1836.6049979995296
usercpu_time_millis_training
1837.9212630006805