6014992
1
Jan van Rijn
9954
Supervised Classification
6969
sklearn.pipeline.Pipeline(imputation=openmlstudy14.preprocessing.ConditionalImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,variencethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,classifier=sklearn.ensemble.forest.RandomForestClassifier)(1)
4049681
bootstrap
false
6902
class_weight
null
6902
criterion
"entropy"
6902
max_depth
null
6902
max_features
0.6323285404876702
6902
max_leaf_nodes
null
6902
min_impurity_split
1e-07
6902
min_samples_leaf
14
6902
min_samples_split
17
6902
min_weight_fraction_leaf
0.0
6902
n_estimators
100
6902
n_jobs
1
6902
oob_score
false
6902
random_state
51331
6902
verbose
0
6902
warm_start
false
6902
axis
0
6947
categorical_features
[]
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copy
true
6947
fill_empty
0
6947
missing_values
"NaN"
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strategy
"mean"
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strategy_nominal
"most_frequent"
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verbose
0
6947
categorical_features
[]
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dtype
{"oml-python:serialized_object": "type", "value": "np.float64"}
6948
handle_unknown
"ignore"
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n_values
"auto"
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sparse
false
6948
threshold
0.0
6949
openml-pimp
openml-python
Sklearn_0.18.1.
study_71
1491
one-hundred-plants-margin
https://www.openml.org/data/download/1592283/phpCsX3fx
-1
12953117
description
https://api.openml.org/data/download/12953117/description.xml
-1
12953118
predictions
https://api.openml.org/data/download/12953118/predictions.arff
area_under_roc_curve
0.9898390151515153 [0.978969,0.998856,0.999763,0.999842,0.998264,0.990451,0.99783,0.995699,0.995344,0.999014,0.997041,0.997909,0.99562,0.973998,0.99783,0.994003,0.999487,0.97163,0.978496,0.962555,0.998106,0.998146,0.988913,1,0.993411,0.964962,0.978378,0.990964,0.997317,0.998856,0.999605,0.999921,0.992188,0.980942,0.995818,0.997909,0.976207,0.984414,0.996843,0.999605,0.987966,0.996883,0.999053,0.994358,0.995857,0.989583,0.997041,0.990609,0.983625,0.991004,0.986466,0.987255,0.994397,0.957978,0.988123,0.965436,1,0.999132,0.9927,0.976207,0.999448,0.995344,0.993687,0.995265,0.99633,0.991043,0.968277,0.999842,0.962082,0.96508,0.986585,0.998067,0.989149,0.995699,0.948509,0.991517,0.998303,0.966935,0.998698,0.997711,0.988557,0.991635,0.989268,0.992661,0.993647,0.982481,0.999684,0.985795,0.996607,0.999605,0.998935,0.999014,0.99128,0.98473,0.994358,0.997672,0.994003,0.991162,0.955414,0.991043]
average_cost
0
kappa
0.6464646464646465
kb_relative_information_score
1056.9926018316512
mean_absolute_error
0.014698735669379967
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
0.65
prior_entropy
6.6438561897747395
recall
0.65 [0.4375,0.9375,1,0.875,0.875,0.3125,0.8125,0.9375,0.6875,0.9375,0.75,0.8125,0.6875,0.3125,0.75,0.625,1,0.375,0.6875,0.0625,0.9375,0.8125,0.625,1,0.6875,0.125,0.375,0.75,0.9375,1,0.6875,1,0.875,0.4375,0.875,0.9375,0.4375,0.5,0.5625,1,0.5625,0.8125,0.9375,0.625,0.6875,0.75,0.75,0.5,0.5625,0.75,0.625,0.5,0.6875,0.25,0.5,0,1,0.9375,0.375,0.5,0.9375,0.8125,0.625,0.75,0.875,0.375,0.1875,1,0.125,0.1875,0.25,0.9375,0.625,0.8125,0.375,0.875,0.9375,0,0.9375,0.8125,0.5625,0.5,0.625,0.375,0.625,0.875,0.8125,0.5625,0.4375,0.9375,1,1,0.4375,0.0625,0.4375,0.75,0.6875,0.5625,0,0.5625]
relative_absolute_error
0.7423603873424213
root_mean_prior_squared_error
0.09949874371066209
root_mean_squared_error
0.07950278082191609
root_relative_squared_error
0.7990330114429046
total_cost
0
area_under_roc_curve
0.9897614640554098 [1,1,1,1,0.996835,1,1,1,0.993671,1,0.990506,0.993671,0.993671,0.958861,1,1,1,0.943038,0.952532,0.943396,1,0.993711,0.993711,1,1,0.987342,0.987342,1,0.996835,0.993711,1,1,0.993671,0.984177,1,0.987421,1,0.993711,1,1,1,1,1,1,1,1,1,1,1,0.974684,0.927215,1,0.987421,0.987342,1,0.993711,1,1,0.987421,0.974684,1,1,0.996835,0.993671,1,0.996835,0.993671,1,1,0.955975,0.981013,1,0.987342,0.990506,1,1,1,0.974684,0.996835,1,1,0.984177,1,1,1,0.911392,1,0.993671,0.996835,1,1,1,1,0.984177,1,1,1,0.996835,0.851266,1]
area_under_roc_curve
0.9907158068625112 [1,1,1,1,1,1,0.993671,1,0.996835,1,1,0.996835,0.990506,0.927215,1,1,0.996835,0.949367,0.996835,0.987421,1,0.987421,1,1,1,0.943038,0.987342,0.968354,1,1,1,1,1,0.990506,0.996835,1,0.943396,1,1,1,1,1,1,0.993671,1,0.984177,1,1,0.990506,1,1,0.955696,1,0.990506,0.993711,0.918239,1,1,1,0.924051,1,1,1,0.993671,1,0.993671,0.996835,1,0.930818,1,0.996835,1,0.990506,1,1,1,1,0.955696,1,0.996835,0.987342,0.993671,0.968553,0.981132,1,1,0.993671,0.993671,0.981013,1,1,1,1,0.987342,0.996835,0.996835,0.993711,0.977848,1,1]
area_under_roc_curve
0.9902771972772868 [0.974684,0.996835,1,1,0.990506,0.984177,1,1,0.987342,1,0.996835,1,1,0.993671,0.987342,0.996835,1,0.990506,0.974843,0.901899,1,0.993711,0.939873,1,0.962264,0.993671,1,1,1,1,1,1,1,0.955696,0.993711,1,0.993711,0.943396,1,1,0.993671,1,1,1,0.996835,1,0.993671,1,0.914557,1,0.990506,1,1,0.977848,1,0.993671,1,0.996835,0.987421,0.968354,1,0.987421,0.996835,1,0.996835,0.974684,0.984177,1,0.981132,0.955696,1,1,0.987421,0.993671,1,1,1,0.974684,0.996835,1,1,1,1,0.996835,1,1,1,1,0.993671,1,1,1,0.993711,0.971519,0.993671,1,0.993671,0.990506,0.993711,0.996835]
area_under_roc_curve
0.9893718652973487 [0.996835,0.996835,1,1,0.996835,0.987342,1,1,0.993671,1,0.996835,1,1,1,1,1,1,0.977848,0.855346,0.987342,1,1,1,1,0.981132,0.962025,0.933544,1,1,1,1,1,1,0.993671,1,0.981132,1,1,1,1,0.996835,1,1,1,1,1,1,1,0.996835,1,0.993671,1,0.993711,0.927215,1,0.990506,1,1,1,0.990506,1,1,0.996835,1,0.990506,0.993671,0.952532,1,0.993711,0.89557,0.984177,0.993671,0.981132,1,0.987421,0.958861,1,0.927215,1,0.993671,0.949686,0.981013,1,0.984177,1,1,1,1,1,1,1,1,0.962264,0.993671,1,0.993711,0.987342,0.996835,1,0.962025]
area_under_roc_curve
0.9883486087891086 [0.987342,1,1,1,1,0.987342,0.993711,1,1,1,1,0.993671,1,0.886792,1,0.990506,1,0.996835,1,0.990506,0.981013,0.993671,1,1,0.996835,0.977848,0.990506,1,1,1,1,1,0.996835,0.943038,1,1,0.987342,0.984177,0.993671,1,1,1,0.987421,1,1,1,1,0.993671,1,0.996835,0.993711,0.949686,0.996835,0.981132,0.958861,0.952532,1,0.987342,0.996835,0.993711,1,1,1,1,0.996835,1,0.830189,1,0.892405,0.984177,1,1,0.993711,0.987421,0.848101,1,0.993671,0.962025,1,1,1,1,0.993671,0.990506,0.981132,1,1,1,1,1,1,0.993671,0.993711,0.987421,0.984177,1,0.996835,1,0.987421,0.984177]
area_under_roc_curve
0.987192003025237 [0.917722,1,1,1,1,0.987342,1,1,1,0.996835,1,1,1,0.993711,1,0.996835,1,1,1,0.911392,1,0.996835,0.971519,1,0.990506,0.993671,0.971519,0.993711,1,1,1,1,0.958861,0.987342,0.955975,1,0.914557,0.984177,1,1,1,0.984177,1,1,1,1,0.996835,0.990506,0.981013,0.962025,0.993711,0.993711,1,1,0.971519,0.943038,1,1,1,1,1,0.993671,0.987421,1,1,0.996835,0.981132,1,0.977848,1,0.952532,0.990506,1,1,0.851266,1,0.996835,0.974684,1,0.993711,1,0.984177,1,0.990506,0.993711,1,1,0.974843,0.984177,1,1,0.996835,0.974843,1,1,1,1,0.974843,0.974843,0.984177]
area_under_roc_curve
0.9911195864182785 [0.993671,1,1,1,1,1,1,1,0.993711,1,1,1,0.981013,0.981132,0.993711,0.987342,1,0.943396,0.990506,0.971519,0.987342,0.996835,1,1,0.990506,0.855346,0.993711,0.974684,1,1,1,1,1,1,1,0.996835,0.990506,1,1,1,0.996835,0.993671,1,0.996835,1,0.996835,0.996835,0.974684,1,1,0.993711,0.990506,0.996835,0.987421,0.996835,0.977848,1,1,0.990506,0.981132,0.996835,0.996835,1,0.971519,1,0.987421,0.955975,1,0.984177,0.96519,0.993711,1,1,1,0.996835,1,1,0.981132,1,1,0.987342,1,0.974684,0.996835,1,1,1,0.899371,1,1,1,1,0.984177,0.981132,0.987421,0.996835,1,0.987421,0.920886,1]
area_under_roc_curve
0.9918664417641905 [1,1,1,1,1,0.990506,0.996835,1,0.993711,1,0.993711,1,0.996835,1,1,0.993671,1,0.937107,0.993671,0.968354,0.993671,1,1,1,0.996835,0.955975,0.955975,0.987342,1,0.996835,1,1,1,1,1,1,0.987342,0.974684,1,1,1,1,1,0.984177,1,0.996835,1,1,0.993711,1,0.968553,0.990506,0.981013,1,1,0.977848,1,1,0.987342,1,1,0.993671,0.993711,0.996835,1,0.968553,0.962264,1,0.955696,0.971519,0.993711,1,1,0.968553,0.993671,1,1,0.968553,1,1,0.981013,1,0.96519,0.996835,0.987342,0.987342,1,0.987421,1,1,1,0.996835,0.993671,0.974843,1,1,0.977848,1,0.962025,0.987342]
area_under_roc_curve
0.9918651978345674 [0.962264,1,1,1,1,1,0.993671,1,0.996835,1,0.987421,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.981132,1,0.987342,1,1,1,1,0.981132,0.996835,1,0.993671,0.968354,0.996835,1,0.886792,1,1,0.981013,0.990506,0.968354,1,1,0.968553,1,1,1,0.993671,0.857595,0.987342,0.955975,1,1,0.996835,0.974684,1,1,1,1,1,1,0.987342,1,0.977848,0.981132,1,0.993711,0.977848,1,0.993671,0.974684,1,0.993711,1,0.990506,1,0.987421,0.993711,0.993711,0.993671,1,1,0.990506,1,1,1,0.996835,1,0.977848,0.987421,0.990506,0.993711,1,0.990506,1]
area_under_roc_curve
0.9947946520977627 [0.962264,0.996835,0.993711,1,1,1,1,0.943396,0.996835,1,1,1,0.993671,0.987342,0.996835,1,1,0.987421,0.990506,0.993711,1,1,1,1,1,0.930818,1,1,0.993671,1,1,1,1,0.974843,0.996835,0.996835,0.987342,1,1,1,0.993711,1,1,0.996835,1,0.977848,1,0.981013,0.993711,0.993711,1,0.993671,1,0.987342,0.996835,0.974843,1,1,0.990506,1,1,0.993671,0.974684,1,0.987421,0.993711,0.993671,1,0.996835,0.974843,0.981132,1,0.977848,1,0.993671,0.996835,1,0.993711,0.981132,1,1,0.968553,1,0.974843,1,1,1,1,1,1,1,1,1,1,1,1,0.993711,1,1,1]
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
0.646269245953415
kappa
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kappa
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kappa
0.6525858665613897
kappa
0.6336504678062452
kappa
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kappa
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kappa
0.6273193841294907
kappa
0.6273635179410255
kappa
0.6967183982940409
kb_relative_information_score
106.31380796957313
kb_relative_information_score
105.75136449569462
kb_relative_information_score
104.32449570510099
kb_relative_information_score
104.6282324314566
kb_relative_information_score
105.32461333267177
kb_relative_information_score
103.68331541580781
kb_relative_information_score
105.9260919195899
kb_relative_information_score
105.99176081148849
kb_relative_information_score
107.36712173894266
kb_relative_information_score
107.68179801132628
mean_absolute_error
0.014564593326065531
mean_absolute_error
0.01467751313478519
mean_absolute_error
0.014812388078489214
mean_absolute_error
0.014783130864468464
mean_absolute_error
0.014666650264413625
mean_absolute_error
0.01481241480815571
mean_absolute_error
0.014708054448144478
mean_absolute_error
0.014705323589913796
mean_absolute_error
0.01458992894972406
mean_absolute_error
0.014667359229639496
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
0.65
predictive_accuracy
0.6625
predictive_accuracy
0.64375
predictive_accuracy
0.65625
predictive_accuracy
0.6375
predictive_accuracy
0.63125
predictive_accuracy
0.65625
predictive_accuracy
0.63125
predictive_accuracy
0.63125
predictive_accuracy
0.7
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
0.65 [1,1,1,1,0.5,0,1,1,1,1,0.5,0.5,0.5,0,1,1,1,0,0.5,0,1,0,1,1,1,0,0,1,1,1,1,1,1,0,1,0,0,1,1,1,1,1,1,1,1,1,1,1,0.5,0.5,0.5,0.5,1,0,1,0,1,1,0,0.5,1,1,0.5,0.5,1,0.5,0,1,0,0,0,1,0.5,1,1,1,1,0,1,1,0.5,0.5,1,1,0.5,0.5,1,0.5,0,0,1,1,1,0.5,0,0.5,1,0.5,0,1]
recall
0.6625 [1,1,1,1,1,1,0,1,0.5,1,1,1,0.5,0.5,1,1,1,0,0.5,0,1,0,0,1,1,0.5,0.5,0,1,1,0.5,1,1,0.5,1,1,0,1,0,1,1,1,1,1,0.5,1,1,0,0,1,1,0.5,1,0,1,0,1,1,1,0.5,1,1,1,1,1,0,0.5,1,0,0,0.5,1,0.5,1,1,1,1,0,1,0.5,0,0.5,0,0,1,1,0.5,1,0.5,1,1,1,0,0,0.5,1,1,0,0,1]
recall
0.64375 [0,1,1,1,0.5,0,1,1,0,1,0.5,1,1,0.5,0,0.5,1,0.5,0,0,1,0,0.5,1,0,0.5,0.5,1,1,1,1,1,1,0,1,1,1,0,1,1,0,1,1,1,0.5,1,0.5,1,0.5,0.5,1,1,1,0.5,1,0,1,1,1,0,1,1,0.5,1,0.5,0.5,0.5,1,0,0,0.5,1,0,0.5,1,1,1,0,0.5,1,1,0.5,1,0.5,1,1,1,0.5,1,1,1,1,1,0,1,1,0.5,0.5,0,0.5]
recall
0.65625 [0.5,1,1,1,1,0,1,1,0.5,1,1,0.5,1,0.5,1,1,1,0.5,0,0,1,1,0.5,1,0,0,0.5,1,1,1,1,1,1,0.5,1,1,1,1,1,1,0.5,1,1,1,1,1,0.5,1,1,1,0,1,0,0,1,0,1,1,0,0.5,1,1,1,1,0.5,0,0,1,0,0.5,0,0.5,0,1,0,0.5,1,0,1,1,0,0.5,1,0,1,1,1,1,0.5,1,1,1,0,0,1,0,0.5,1,0,0]
recall
0.6375 [0.5,1,1,1,1,0.5,0,1,1,1,1,0.5,1,0,1,0.5,1,1,1,0,0.5,1,1,1,0.5,0,0.5,1,1,1,1,1,0.5,0,1,1,1,0,0.5,1,1,1,1,1,1,0,1,0,0.5,0.5,0,0,0,0,0,0,1,0.5,1,1,1,1,1,1,1,0,0,1,0,0.5,0,1,1,0,0,1,0.5,0,1,1,1,1,0.5,0,0,1,1,1,1,1,1,1,0,0,0.5,1,0.5,1,0,0.5]
recall
0.63125 [0,1,1,0.5,1,0.5,1,1,1,0.5,0,1,1,1,1,1,1,0.5,1,0,1,1,0.5,1,1,0,0.5,1,1,1,0,1,0.5,1,0,1,0.5,0.5,0.5,1,1,0.5,1,1,1,1,1,0,0.5,0.5,1,0,1,1,0,0,1,1,0,1,1,0.5,0,1,1,0.5,0,1,0,0.5,0.5,1,1,1,0,1,1,0,1,0,1,0,1,0.5,0,1,1,0,0,1,1,1,0,0,0,1,1,0,0,0.5]
recall
0.65625 [0.5,1,1,0.5,1,0.5,1,1,1,1,1,1,0.5,0,0,0.5,1,0,1,0.5,1,1,0.5,1,1,0,0,0.5,1,1,0.5,1,1,1,1,1,0,1,1,1,0,0.5,1,0,0,0.5,0.5,0.5,1,1,0,1,1,0,0.5,0,1,1,0,0,0.5,1,1,0,1,1,0,1,0,0,1,1,1,1,1,1,1,0,1,1,0.5,1,0.5,0.5,1,1,0.5,0,0,1,1,1,0.5,0,0,0.5,1,0,0,1]
recall
0.63125 [1,1,1,1,1,0,1,1,1,1,1,1,0.5,0,1,0.5,1,0,1,0,1,1,0.5,1,0.5,0,0,0.5,1,1,0,1,1,1,1,1,0,0,1,1,0.5,1,1,0,1,1,0.5,1,1,1,0,0.5,0.5,1,0.5,0,1,1,0.5,1,1,0.5,1,1,1,0,1,1,0,0,0,1,1,0,0,1,1,0,1,1,0,0,0,0.5,0,0.5,1,0,1,1,1,1,0,0,0,1,0.5,1,0,0.5]
recall
0.63125 [0,1,1,1,1,1,1,1,0.5,1,1,1,1,0,1,0,1,1,1,0,1,1,1,1,0.5,0,0,1,1,1,1,1,1,1,0.5,1,1,0,0,1,0,0.5,1,0.5,0,0.5,1,0.5,0,1,1,0,1,0,0,0,1,1,0,0,1,1,0.5,0.5,1,1,0,1,0.5,0,0,1,0.5,1,0.5,0.5,1,0,1,0.5,1,1,0,1,0.5,1,0.5,0.5,0,1,1,1,0.5,0,0,0.5,0,0.5,0,1]
recall
0.7 [0,0.5,1,1,1,0,1,0,1,1,1,1,0.5,0.5,0.5,0,1,0,0.5,0,1,1,1,1,1,0,1,1,0.5,1,1,1,1,0,1,1,0,1,0,1,1,1,0.5,0.5,1,0.5,1,0.5,1,1,1,0.5,0.5,0.5,1,0,1,1,0.5,1,1,0.5,0,1,1,1,0,1,0.5,0,0,1,0.5,1,0,1,1,0,1,1,1,0,1,0,1,1,1,0.5,0,1,1,1,1,0,1,1,1,1,0,0]
relative_absolute_error
0.73558552151846
relative_absolute_error
0.7412885421608669
relative_absolute_error
0.7481004080045045
relative_absolute_error
0.7466227709327494
relative_absolute_error
0.7407399123441213
relative_absolute_error
0.7481017579876608
relative_absolute_error
0.7428310327345684
relative_absolute_error
0.7426931106017056
relative_absolute_error
0.7368650984709109
relative_absolute_error
0.7407757186686602
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
0.07874877425462107
root_mean_squared_error
0.0790465751859735
root_mean_squared_error
0.08009541953124573
root_mean_squared_error
0.07979189531181352
root_mean_squared_error
0.0794720837650097
root_mean_squared_error
0.08047501882292454
root_mean_squared_error
0.07972102596622782
root_mean_squared_error
0.07945936419919872
root_mean_squared_error
0.07884664864892453
root_mean_squared_error
0.07935427528421579
root_relative_squared_error
0.791454960312052
root_relative_squared_error
0.7944479722863379
root_relative_squared_error
0.804989254579532
root_relative_squared_error
0.8019387213957678
root_relative_squared_error
0.7987244944128239
root_relative_squared_error
0.80880437100736
root_relative_squared_error
0.8012264576732048
root_relative_squared_error
0.7985966579664868
root_relative_squared_error
0.7924386349862576
root_relative_squared_error
0.7975404746312629
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
6386.890012000094
usercpu_time_millis
6187.3607740000125
usercpu_time_millis
6185.1855540001
usercpu_time_millis
6123.548511000081
usercpu_time_millis
7236.9086579999475
usercpu_time_millis
6634.535682999967
usercpu_time_millis
6366.463980000049
usercpu_time_millis
6161.424165000085
usercpu_time_millis
7332.670531999952
usercpu_time_millis
6288.163464000036
usercpu_time_millis_testing
34.56757900005414
usercpu_time_millis_testing
34.23503900000924
usercpu_time_millis_testing
34.035040000048866
usercpu_time_millis_testing
33.837607000009484
usercpu_time_millis_testing
39.03810799999974
usercpu_time_millis_testing
33.69979000001422
usercpu_time_millis_testing
33.689028000026155
usercpu_time_millis_testing
33.77833299998656
usercpu_time_millis_testing
46.28244699995321
usercpu_time_millis_testing
34.00961800002733
usercpu_time_millis_training
6352.32243300004
usercpu_time_millis_training
6153.125735000003
usercpu_time_millis_training
6151.150514000051
usercpu_time_millis_training
6089.710904000071
usercpu_time_millis_training
7197.870549999948
usercpu_time_millis_training
6600.835892999953
usercpu_time_millis_training
6332.7749520000225
usercpu_time_millis_training
6127.645832000098
usercpu_time_millis_training
7286.388084999999
usercpu_time_millis_training
6254.153846000008