6003764
1
Jan van Rijn
9956
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)
4038495
bootstrap
false
6902
class_weight
null
6902
criterion
"entropy"
6902
max_depth
null
6902
max_features
0.26139488613162076
6902
max_leaf_nodes
null
6902
min_impurity_split
1e-07
6902
min_samples_leaf
7
6902
min_samples_split
4
6902
min_weight_fraction_leaf
0.0
6902
n_estimators
100
6902
n_jobs
1
6902
oob_score
false
6902
random_state
33355
6902
verbose
0
6902
warm_start
false
6902
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
false
6948
threshold
0.0
6949
openml-pimp
openml-python
Sklearn_0.18.1.
study_71
1493
one-hundred-plants-texture
https://www.openml.org/data/download/1592285/phpoOxxNn
-1
12930631
description
https://api.openml.org/data/download/12930631/description.xml
-1
12930632
predictions
https://api.openml.org/data/download/12930632/predictions.arff
area_under_roc_curve
0.9933105570094616 [0.995455,1,0.976666,0.997394,0.982233,0.997671,0.995183,0.997118,0.989221,0.999052,0.996605,0.986221,0.999566,0.998934,0.990208,0.999842,0.984405,0.996012,0.999961,0.993959,1,0.981128,0.99771,0.999842,0.934559,0.99696,0.977653,0.963795,1,0.999763,0.999131,0.999921,0.980812,0.999842,0.998144,0.984602,0.997986,0.999803,0.988787,0.999329,0.999645,0.995065,0.992459,0.972086,0.987761,0.999447,0.982707,0.998026,0.990919,0.995736,0.996131,0.997315,0.999092,0.993525,0.991196,0.997986,1,0.954102,0.999447,1,1,0.999526,0.999368,1,0.999368,0.99775,1,0.990287,0.998737,0.991038,0.999131,0.99009,0.999961,0.991669,0.999882,0.999645,0.989932,0.999526,0.999487,0.992577,0.9985,0.990919,0.988313,0.997631,0.995696,0.99921,0.951181,0.999131,0.999724,0.998934,0.982154,0.989103,0.999368,0.999882,0.994551,0.993999,0.999921,0.999645,0.99775,0.999487]
average_cost
0
f_measure
0.7667197485048537 [0.827586,0.857143,0.4,0.827586,0.6875,0.866667,0.8125,0.756757,0.8,0.8125,0.83871,0.83871,0.909091,0.875,0.689655,0.941176,0.529412,0.705882,0.967742,0.823529,0.888889,0.25,0.75,0.888889,0.111111,0.764706,0.8,0.210526,0.969697,0.882353,0.857143,0.882353,0.692308,0.8,0.8125,0.4,0.736842,0.888889,0.666667,0.83871,0.83871,0.580645,0.615385,0.48,0.62069,0.882353,0.571429,0.882353,0.764706,0.6875,0.722222,0.722222,0.8,0.8125,0.516129,0.705882,0.914286,0.758621,0.909091,0.941176,0.9375,0.833333,0.882353,0.8,0.933333,0.764706,0.914286,0.705882,0.848485,0.583333,0.810811,0.62069,0.941176,0.8,0.9375,0.864865,0.83871,0.9375,0.875,0.62069,0.903226,0.758621,0.5,0.645161,0.75,0.875,0.692308,0.714286,0.882353,0.810811,0.756757,0.3,0.875,0.909091,0.810811,0.785714,0.914286,1,0.848485,0.909091]
kappa
0.7789020441042322
kb_relative_information_score
1141.914941906294
mean_absolute_error
0.012998552779773766
mean_prior_absolute_error
0.019799992711748222
number_of_instances
1599 [15,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16]
precision
0.7837337915451749 [0.857143,0.789474,1,0.923077,0.6875,0.928571,0.8125,0.666667,0.857143,0.8125,0.866667,0.866667,0.882353,0.875,0.769231,0.888889,0.5,0.666667,1,0.777778,0.8,0.375,0.75,0.8,0.5,0.722222,0.857143,0.666667,0.941176,0.833333,1,0.833333,0.9,0.666667,0.8125,0.555556,0.636364,0.8,0.714286,0.866667,0.866667,0.6,0.8,0.666667,0.692308,0.833333,0.526316,0.833333,0.722222,0.6875,0.65,0.65,0.666667,0.8125,0.533333,0.666667,0.842105,0.846154,0.882353,0.888889,0.9375,0.75,0.833333,0.666667,1,0.722222,0.842105,0.666667,0.823529,0.875,0.714286,0.692308,0.888889,0.736842,0.9375,0.761905,0.866667,0.9375,0.875,0.692308,0.933333,0.846154,0.583333,0.666667,0.75,0.875,0.9,0.576923,0.833333,0.714286,0.666667,0.75,0.875,0.882353,0.714286,0.916667,0.842105,1,0.823529,0.882353]
predictive_accuracy
0.7811131957473421
prior_entropy
6.6438309601245775
recall
0.7811131957473421 [0.8,0.9375,0.25,0.75,0.6875,0.8125,0.8125,0.875,0.75,0.8125,0.8125,0.8125,0.9375,0.875,0.625,1,0.5625,0.75,0.9375,0.875,1,0.1875,0.75,1,0.0625,0.8125,0.75,0.125,1,0.9375,0.75,0.9375,0.5625,1,0.8125,0.3125,0.875,1,0.625,0.8125,0.8125,0.5625,0.5,0.375,0.5625,0.9375,0.625,0.9375,0.8125,0.6875,0.8125,0.8125,1,0.8125,0.5,0.75,1,0.6875,0.9375,1,0.9375,0.9375,0.9375,1,0.875,0.8125,1,0.75,0.875,0.4375,0.9375,0.5625,1,0.875,0.9375,1,0.8125,0.9375,0.875,0.5625,0.875,0.6875,0.4375,0.625,0.75,0.875,0.5625,0.9375,0.9375,0.9375,0.875,0.1875,0.875,0.9375,0.9375,0.6875,1,1,0.875,0.9375]
relative_absolute_error
0.6564928062857893
root_mean_prior_squared_error
0.09949872432040595
root_mean_squared_error
0.07141051283945232
root_relative_squared_error
0.7177027979725256
total_cost
0
area_under_roc_curve
0.9926866889578857 [1,1,0.968553,1,0.96519,0.971519,0.977848,1,1,1,1,1,1,1,0.987342,1,0.996835,1,1,1,1,0.936709,1,1,0.993671,1,1,0.990506,1,1,1,1,1,1,0.993711,0.981013,1,1,0.990506,0.993671,1,1,0.993711,1,1,1,0.93038,0.993711,0.990506,1,1,1,1,1,0.937107,1,1,0.993711,1,1,1,1,1,1,0.996835,1,1,1,1,0.996835,1,1,1,1,1,1,1,1,1,1,1,1,0.996835,1,1,0.996835,0.962025,1,1,0.996835,0.911392,0.984177,1,1,0.968354,0.958861,1,1,1,1]
area_under_roc_curve
0.9940783974205877 [1,1,1,1,0.996835,0.996835,1,1,1,1,1,1,1,1,1,1,0.958861,1,1,0.993671,1,0.984177,1,1,0.968354,0.987342,0.874214,0.996835,1,1,1,1,1,1,0.987421,0.955696,1,1,0.996835,1,1,1,0.974843,0.911392,1,1,0.996835,1,1,1,1,1,0.993711,1,1,1,1,1,1,1,1,1,1,1,1,0.990506,1,0.90566,1,0.974684,1,0.984177,1,1,1,1,1,0.996835,1,1,1,1,0.962264,1,1,1,0.996835,0.996835,1,1,1,0.993671,1,1,1,1,1,1,1,1]
area_under_roc_curve
0.9952976972374813 [1,1,0.987342,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.996835,1,1,1,0.987342,0.996835,1,0.987421,1,1,0.96519,1,1,1,1,0.993671,1,1,0.968553,1,1,1,1,1,0.993711,1,1,0.990506,1,0.996835,1,1,0.987421,1,0.987342,1,1,1,1,1,0.981132,0.987421,1,1,1,1,1,1,1,1,1,0.987421,1,1,0.955696,1,1,1,1,1,1,1,0.993671,1,0.968354,0.993711,1,0.993711,1,0.882911,1,1,0.993711,1,0.984177,1,1,1,1,1,1,1,1]
area_under_roc_curve
0.9945550712522886 [1,1,0.990506,1,1,1,1,1,1,1,1,1,1,1,0.946203,1,0.981013,0.996835,1,1,1,0.990506,1,1,0.786164,0.993671,1,0.974684,1,1,0.996835,1,1,1,0.996835,1,1,1,0.937107,1,1,0.993711,0.943396,0.993671,1,1,1,0.993671,1,1,1,0.996835,1,0.987342,0.996835,0.996835,1,1,1,1,1,0.987421,1,1,1,1,1,1,1,1,1,0.990506,1,1,1,0.996835,0.927215,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.993671,1,1,1,1,1,1,1,1]
area_under_roc_curve
0.9955007065520262 [0.996835,1,0.990506,1,1,1,1,0.993671,0.867925,1,1,0.968553,1,1,0.981132,1,0.971519,0.996835,1,1,1,0.968553,1,1,1,0.996835,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.993671,1,0.990506,1,0.974684,1,1,1,0.993671,0.996835,1,0.981132,0.977848,1,1,0.996835,1,1,1,1,1,1,1,1,1,1,1,0.984177,1,1,1,0.993671,1,1,0.993711,1,1,0.993671,1,0.984177,0.993711,0.993711,1,1,0.968354,1,1,1,1,0.993671,1,1,1,0.993711,1,1,0.981013,1]
area_under_roc_curve
0.9920832586975559 [1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.990506,0.993671,1,1,1,0.987421,0.996835,1,1,1,0.933544,0.685535,1,1,0.987421,1,1,1,1,1,1,1,1,1,1,0.996835,0.996835,0.990506,0.977848,1,1,1,1,1,0.993671,0.993711,1,1,0.996835,0.993671,1,0.761076,1,1,1,1,1,1,1,1,1,0.987342,0.993671,1,1,1,1,1,1,1,1,1,1,1,0.990506,1,0.996835,1,0.974684,1,1,0.981132,1,1,1,0.987342,0.996835,1,1,1,1,1,1,1]
area_under_roc_curve
0.9930800195048166 [1,1,0.952532,0.987421,1,1,1,1,1,1,0.984177,0.898734,1,1,1,1,1,1,1,1,1,1,1,1,0.936709,1,0.990506,0.993711,1,1,1,1,0.946203,1,0.996835,0.996835,1,1,0.990506,1,1,1,1,1,0.962025,1,1,1,1,1,1,1,1,1,1,0.987421,1,0.936709,1,1,1,1,1,1,1,1,1,1,0.993671,0.987421,1,1,1,0.939873,1,1,0.987421,1,1,1,1,1,0.958861,1,1,1,1,1,1,1,1,0.993711,1,1,1,0.993671,1,1,1,1]
area_under_roc_curve
0.9900510508717459 [0.955975,1,0.905063,1,1,1,0.993711,0.993671,0.987342,1,0.987342,1,1,1,1,1,0.981132,0.990506,1,0.968354,1,1,1,1,0.810127,1,1,0.993711,1,1,1,1,0.952532,1,1,0.987342,1,1,0.968354,1,0.993711,0.993671,1,0.930818,1,1,1,1,1,0.990506,0.993671,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.996835,1,1,0.993711,1,1,1,1,1,1,1,0.996835,0.955696,1,1,0.996835,1,0.987342,0.993711,0.672956,1,1,1,1,1,1,1,1,0.987342,1,1,1,1]
area_under_roc_curve
0.9955758399012815 [0.968553,1,1,1,0.977848,1,1,0.987342,0.996835,1,1,1,1,1,0.990506,1,1,1,1,1,1,0.968354,1,1,0.987342,1,1,0.990506,1,1,1,0.996835,0.987421,1,1,1,0.981013,1,1,1,1,1,1,0.949686,1,1,1,1,0.943038,0.993671,0.990506,1,1,0.971519,0.993671,0.993711,1,1,1,1,1,1,1,1,0.993671,1,1,1,0.996835,0.955975,1,0.987342,1,1,1,0.996835,1,1,1,1,0.996835,1,0.987342,1,1,1,1,1,1,1,1,0.987421,1,1,1,1,1,1,1,0.996835]
area_under_roc_curve
0.9953229513857724 [1,1,0.993671,0.987261,0.926752,1,0.996815,1,1,1,0.993671,1,1,1,1,1,0.962025,0.993671,1,1,1,0.990446,0.993671,1,0.914013,1,1,1,1,1,1,1,1,1,1,1,1,1,0.993631,1,1,0.987261,1,0.873418,1,1,0.955696,1,0.996815,0.996815,0.984076,1,1,1,1,1,1,1,0.996815,1,1,1,1,1,1,1,1,1,1,0.993671,1,1,1,1,1,1,1,1,1,1,1,1,1,0.990446,1,1,1,1,1,0.990446,1,0.993671,1,1,1,1,1,1,1,1]
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
0.7473950110514683
kappa
0.7852603323727944
kappa
0.8041692987997473
kappa
0.7789531854424884
kappa
0.7599115463591849
kappa
0.7915021323645554
kappa
0.8167963043392427
kappa
0.7725657427149965
kappa
0.741079886327755
kappa
0.7901871401151632
kb_relative_information_score
112.26771130743964
kb_relative_information_score
113.08931139663187
kb_relative_information_score
115.01672676084047
kb_relative_information_score
113.48737589702449
kb_relative_information_score
114.50680889003822
kb_relative_information_score
116.38638008316391
kb_relative_information_score
114.01171962001365
kb_relative_information_score
113.30854795124618
kb_relative_information_score
113.91403150310931
kb_relative_information_score
115.92632849678657
mean_absolute_error
0.013152205942443498
mean_absolute_error
0.013162383044039258
mean_absolute_error
0.013034675505049827
mean_absolute_error
0.013177124569874816
mean_absolute_error
0.01292834718753429
mean_absolute_error
0.012563266441891216
mean_absolute_error
0.012954897723804112
mean_absolute_error
0.0130766180902431
mean_absolute_error
0.01317928141303151
mean_absolute_error
0.012755206968505593
mean_prior_absolute_error
0.01980002942907592
mean_prior_absolute_error
0.01980002942907592
mean_prior_absolute_error
0.019800029429075917
mean_prior_absolute_error
0.019800029429075917
mean_prior_absolute_error
0.01980002942907591
mean_prior_absolute_error
0.01979995585638609
mean_prior_absolute_error
0.01979995585638609
mean_prior_absolute_error
0.01979995585638609
mean_prior_absolute_error
0.019799955856386102
mean_prior_absolute_error
0.01979995631910742
number_of_instances
160 [2,1,1,2,2,2,2,1,2,2,1,2,2,2,2,2,2,1,2,2,1,2,2,2,2,1,1,2,2,1,2,2,1,1,1,2,1,1,2,2,2,1,1,2,1,1,2,1,2,2,1,2,1,2,1,2,2,1,1,1,1,2,1,1,2,2,2,1,1,2,2,2,1,1,2,2,2,2,1,1,1,2,2,2,1,2,2,2,2,2,2,2,1,2,2,2,1,1,2,1]
number_of_instances
160 [2,1,1,2,2,2,2,1,2,2,1,2,2,2,2,2,2,1,2,2,2,2,2,2,2,2,1,2,2,2,2,2,1,1,1,2,1,1,2,2,2,1,1,2,1,1,2,1,2,2,1,2,1,2,1,2,1,1,1,1,1,2,1,1,2,2,2,1,1,2,2,2,1,1,2,2,2,2,1,1,1,2,1,2,1,2,2,2,2,2,2,2,1,1,2,2,1,1,2,1]
number_of_instances
160 [2,1,2,2,2,1,2,1,1,2,2,1,2,2,2,2,2,2,2,1,2,2,2,1,1,2,1,2,2,2,2,1,2,2,2,1,1,2,1,1,2,1,1,2,2,2,2,2,2,1,1,2,2,2,1,2,1,1,1,1,2,1,1,1,2,2,2,1,1,2,2,2,2,1,2,2,2,1,2,2,1,2,1,2,1,2,2,1,2,1,1,2,2,1,2,1,1,2,2,1]
number_of_instances
160 [2,1,2,2,2,1,2,2,1,2,2,1,2,2,2,2,2,2,2,1,2,2,2,1,1,2,1,2,2,2,2,1,2,2,2,1,1,2,1,1,2,1,1,2,2,2,2,2,1,1,1,2,2,2,2,2,1,1,1,1,2,1,1,1,2,1,2,1,1,2,2,2,2,1,2,2,2,1,2,2,1,2,1,2,1,2,2,1,2,1,1,2,2,1,1,1,2,2,2,1]
number_of_instances
160 [2,2,2,1,1,1,1,2,1,1,2,1,1,2,1,1,2,2,2,1,2,1,2,1,1,2,2,1,2,2,1,1,2,2,2,1,2,2,1,1,2,2,2,2,2,2,2,2,1,1,2,2,2,1,2,2,1,2,2,2,2,1,2,2,1,1,2,2,2,2,1,1,2,2,2,1,1,1,2,2,2,2,1,1,2,2,2,1,2,1,1,2,2,1,1,1,2,2,2,2]
number_of_instances
160 [1,2,2,1,1,1,1,2,1,1,2,1,1,2,1,1,2,2,2,1,2,1,2,1,1,2,2,1,2,2,1,1,2,2,2,1,2,2,1,1,2,2,2,2,2,2,2,2,1,1,2,1,2,1,2,2,2,2,2,2,2,1,2,2,1,1,2,2,2,2,1,1,2,2,2,1,1,1,2,2,2,1,2,1,2,2,2,1,2,1,1,2,2,2,1,1,2,2,2,2]
number_of_instances
160 [1,2,2,1,1,2,1,2,2,1,2,2,1,1,1,1,1,2,1,2,2,1,1,2,2,2,2,1,1,2,1,2,2,2,2,2,2,2,2,2,1,2,2,1,2,2,1,2,1,2,2,1,2,1,2,1,2,2,2,2,2,2,2,2,1,1,1,2,2,1,1,1,2,2,1,1,1,2,2,2,2,1,2,1,2,1,1,2,1,2,2,1,2,2,1,2,2,2,1,2]
number_of_instances
160 [1,2,2,1,1,2,1,2,2,1,2,2,1,1,1,1,1,2,1,2,1,1,1,2,2,1,2,1,1,1,1,2,2,2,2,2,2,2,2,2,1,2,2,1,2,2,1,2,2,2,2,1,2,1,2,1,2,2,2,2,2,2,2,2,1,2,1,2,2,1,1,1,2,2,1,1,1,2,2,2,2,1,2,1,2,1,1,2,1,2,2,1,2,2,2,2,2,2,1,2]
number_of_instances
160 [1,2,1,2,2,2,2,2,2,2,1,2,2,1,2,2,1,1,1,2,1,2,1,2,2,1,2,2,1,1,2,2,1,1,1,2,2,1,2,2,1,2,2,1,1,1,1,1,2,2,2,1,1,2,2,1,2,2,2,2,1,2,2,2,2,2,1,2,2,1,2,2,1,2,1,2,2,2,1,1,2,1,2,2,2,1,1,2,1,2,2,1,1,2,2,2,2,1,1,2]
number_of_instances
159 [1,2,1,2,2,2,2,1,2,2,1,2,2,1,2,2,1,1,1,2,1,2,1,2,2,1,2,2,1,1,2,2,1,1,1,2,2,1,2,2,1,2,2,1,1,1,1,1,2,2,2,2,1,2,1,1,2,2,2,2,1,2,2,2,2,2,1,2,2,1,2,2,1,2,1,2,2,2,1,1,2,2,2,2,2,1,1,2,1,2,2,1,1,2,2,2,1,1,1,2]
predictive_accuracy
0.75
predictive_accuracy
0.7875
predictive_accuracy
0.80625
predictive_accuracy
0.78125
predictive_accuracy
0.7625
predictive_accuracy
0.79375
predictive_accuracy
0.81875
predictive_accuracy
0.775
predictive_accuracy
0.74375
predictive_accuracy
0.7924528301886792
prior_entropy
6.6438309601245775
prior_entropy
6.6438309601245775
prior_entropy
6.6438309601245775
prior_entropy
6.6438309601245775
prior_entropy
6.6438309601245775
prior_entropy
6.6438309601245775
prior_entropy
6.6438309601245775
prior_entropy
6.6438309601245775
prior_entropy
6.6438309601245775
prior_entropy
6.6438309601245775
recall
0.75 [1,1,0,1,0.5,0.5,0,1,1,1,1,0.5,1,1,0.5,1,1,1,1,1,1,0,1,1,0.5,1,1,0,1,0,1,1,1,1,0,0,1,1,0.5,0.5,1,1,0,0,1,1,0.5,1,0.5,0.5,1,1,1,1,0,0.5,1,1,1,1,1,1,1,1,0.5,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,0.5,0.5,0,0.5,0,1,0.5,1,0.5,0.5,1,1,0.5,0.5,1,1,0.5,1]
recall
0.7875 [1,1,0,0.5,1,0.5,1,1,1,0.5,1,1,1,1,1,1,0.5,1,1,0.5,1,0.5,1,1,0,0.5,0,0,1,1,0.5,1,1,1,1,0,1,1,1,1,0.5,1,0,0.5,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,0,1,0.5,1,0,1,1,1,1,0.5,1,1,1,1,1,0,0.5,1,1,0.5,1,1,1,1,0,1,1,1,0,1,1,1,1]
recall
0.80625 [1,1,0.5,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0.5,1,1,1,0,0.5,1,0,1,1,0.5,1,1,1,1,0,1,1,0,1,1,1,1,1,1,0,1,0.5,1,0.5,1,0.5,0,1,0.5,1,1,1,0.5,1,0,1,1,1,1,1,1,1,0.5,1,1,1,0.5,1,0.5,1,1,1,1,1,1,1,0.5,1,0.5,1,0,1,0.5,0,1,1,1,1,0,1,1,1,1,1,1,1,1]
recall
0.78125 [1,1,0.5,1,1,0,1,1,1,1,1,1,1,0.5,0,1,0.5,1,0.5,1,1,0,1,1,0,0.5,1,0,1,1,0.5,1,1,1,0.5,0,1,1,0,1,1,0,0,1,0.5,1,1,0.5,1,1,1,1,1,0.5,0.5,0.5,1,1,1,1,1,0,1,1,1,1,1,1,1,0.5,1,0.5,1,1,0.5,1,0.5,1,0.5,1,1,0,1,1,1,1,1,1,1,1,1,0,0.5,1,1,1,1,1,1,1]
recall
0.7625 [0.5,1,0.5,1,1,1,1,0.5,0,0,1,0,1,1,0,1,0,0.5,1,1,1,0,0,1,0,0.5,1,1,1,1,1,1,0.5,1,0.5,1,1,1,1,0,1,1,1,0,0.5,0.5,0.5,1,1,1,0.5,0.5,1,0,0.5,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,0,1,0.5,0,1,1,1,0.5,1,1,1,0,0.5,1,0,1,1,1,1,0.5,1]
recall
0.79375 [1,1,0.5,0,1,1,1,0.5,1,1,1,1,1,1,1,1,0.5,0.5,1,1,1,0,0.5,1,0,1,0.5,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,0,0.5,0.5,1,1,1,1,1,1,0,1,1,0.5,0.5,1,0.5,1,1,1,1,1,1,1,1,1,0.5,1,0.5,1,1,1,1,1,1,1,1,1,0.5,0,0,0,1,0,1,1,0,1,1,1,0,0.5,1,1,1,1,1,1,1]
recall
0.81875 [1,1,0,0,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0.5,0,1,1,1,1,0.5,1,1,1,0.5,1,0.5,1,1,0.5,0.5,0,0,1,1,1,1,1,1,1,1,1,0.5,1,1,0.5,1,1,0.5,1,1,1,1,1,1,0.5,0.5,0,1,1,1,0,1,1,0,1,0.5,1,1,1,0,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1]
recall
0.775 [0,1,0,1,0,1,1,1,0,0,0,1,1,1,1,1,0,0.5,1,0.5,1,1,1,1,0,1,0.5,0,1,1,0,1,0,1,1,0.5,1,1,0.5,1,0,0.5,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,0.5,1,1,1,1,1,1,1,1,0.5,1,1,1,0,1,1,1,1,1,0.5,1,0,1,1,0.5,0,0.5,1,0,1,1,1,1,1,1,1,1,0.5,1,1,1,1]
recall
0.74375 [0,1,0,1,0.5,1,1,1,0.5,1,1,1,1,1,0.5,1,1,1,1,1,1,0,1,1,0,1,1,0,1,1,0.5,0.5,0,1,1,0,0.5,1,0.5,0.5,0,0.5,0.5,0,0,1,1,1,0.5,0,0.5,1,1,0.5,0,1,1,1,1,1,1,1,0.5,1,0.5,1,1,1,0.5,0,0.5,0.5,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,0,1,1,1,0.5,1,1,1,0.5]
recall
0.7924528301886793 [1,0.5,0,0.5,0,1,0.5,1,1,1,0,1,0.5,1,0.5,1,0,1,1,1,1,0,1,1,0,1,1,0,1,1,1,1,1,1,1,0,1,1,0.5,1,1,0,1,0,1,1,0,1,1,0.5,0.5,1,1,1,0,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0,1,0.5,1,1,1,1,1,1,1,0,1,1,1,0.5,1,1,1,1,1,0.5,1,0,1,1,1,1,1,1,1,1]
relative_absolute_error
0.6642518380871577
relative_absolute_error
0.6647658323532883
relative_absolute_error
0.6583159662332969
relative_absolute_error
0.6655103527535415
relative_absolute_error
0.6529458571687421
relative_absolute_error
0.6345098207801902
relative_absolute_error
0.6542892225502495
relative_absolute_error
0.6604367295104595
relative_absolute_error
0.6656217573727965
relative_absolute_error
0.6442037933283983
root_mean_prior_squared_error
0.09949890883178135
root_mean_prior_squared_error
0.09949890883178135
root_mean_prior_squared_error
0.09949890883178135
root_mean_prior_squared_error
0.09949890883178135
root_mean_prior_squared_error
0.09949890883178135
root_mean_prior_squared_error
0.09949853911503082
root_mean_prior_squared_error
0.09949853911503082
root_mean_prior_squared_error
0.09949853911503082
root_mean_prior_squared_error
0.09949853911503082
root_mean_prior_squared_error
0.0994985414402977
root_mean_squared_error
0.07229308924437841
root_mean_squared_error
0.07226863429907288
root_mean_squared_error
0.07125733033983626
root_mean_squared_error
0.07198159529986863
root_mean_squared_error
0.07138533018831765
root_mean_squared_error
0.06972320451291633
root_mean_squared_error
0.07098452723512047
root_mean_squared_error
0.07147247672564153
root_mean_squared_error
0.07237311282512399
root_mean_squared_error
0.07030973524138732
root_relative_squared_error
0.7265716789578198
root_relative_squared_error
0.726325897917679
root_relative_squared_error
0.716161927567548
root_relative_squared_error
0.723441052218622
root_relative_squared_error
0.7174483723133673
root_relative_squared_error
0.7007460122837478
root_relative_squared_error
0.7134228086811893
root_relative_squared_error
0.7183268956643856
root_relative_squared_error
0.7273786476548467
root_relative_squared_error
0.7066408635103
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
7911.318482999945
usercpu_time_millis
7898.620698000059
usercpu_time_millis
7917.214736999995
usercpu_time_millis
7813.734791000002
usercpu_time_millis
7899.661352999942
usercpu_time_millis
7912.611698000092
usercpu_time_millis
7867.462034000027
usercpu_time_millis
7905.212797000104
usercpu_time_millis
7862.371722000034
usercpu_time_millis
7885.950928999932
usercpu_time_millis_testing
40.23856599997089
usercpu_time_millis_testing
39.936685000043326
usercpu_time_millis_testing
39.50618700002906
usercpu_time_millis_testing
39.44443599993974
usercpu_time_millis_testing
39.52671399997598
usercpu_time_millis_testing
39.34783900001548
usercpu_time_millis_testing
40.972968000005494
usercpu_time_millis_testing
39.51585900006194
usercpu_time_millis_testing
39.536197000074935
usercpu_time_millis_testing
39.74403999995957
usercpu_time_millis_training
7871.079916999975
usercpu_time_millis_training
7858.6840130000155
usercpu_time_millis_training
7877.708549999966
usercpu_time_millis_training
7774.290355000062
usercpu_time_millis_training
7860.134638999966
usercpu_time_millis_training
7873.263859000076
usercpu_time_millis_training
7826.489066000022
usercpu_time_millis_training
7865.696938000042
usercpu_time_millis_training
7822.8355249999595
usercpu_time_millis_training
7846.206888999973