6131087
1
Jan van Rijn
9954
Supervised Classification
7096
sklearn.model_selection._search.RandomizedSearchCV(estimator=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)
4162437
bootstrap
true
6902
class_weight
null
6902
criterion
"entropy"
6902
max_depth
null
6902
max_features
"auto"
6902
max_leaf_nodes
null
6902
min_impurity_split
1e-07
6902
min_samples_leaf
1
6902
min_samples_split
15
6902
min_weight_fraction_leaf
0.0
6902
n_estimators
10
6902
n_jobs
1
6902
oob_score
false
6902
random_state
1
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
"median"
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
true
6948
threshold
0.0
6949
cv
null
7096
error_score
"raise"
7096
fit_params
{}
7096
iid
true
7096
n_iter
50
7096
n_jobs
1
7096
param_distributions
{"classifier__min_samples_leaf": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20], "classifier__max_features": [0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9], "classifier__bootstrap": [true, false], "classifier__criterion": ["gini", "entropy"], "imputation__strategy": ["mean", "median", "most_frequent"]}
7096
pre_dispatch
"2*n_jobs"
7096
random_state
1
7096
refit
true
7096
return_train_score
true
7096
scoring
null
7096
verbose
0
7096
openml-python
Sklearn_0.18.1.
1491
one-hundred-plants-margin
https://www.openml.org/data/download/1592283/phpCsX3fx
-1
13192760
description
https://api.openml.org/data/download/13192760/description.xml
-1
13192761
predictions
https://api.openml.org/data/download/13192761/predictions.arff
-1
13192762
trace
https://api.openml.org/data/download/13192762/trace.arff
area_under_roc_curve
0.9899992108585864 [0.984612,0.998935,1,1,0.997317,0.989741,0.999211,0.998106,0.992898,0.995758,0.993253,0.999211,0.997159,0.949811,0.995896,0.987847,0.999645,0.974096,0.982816,0.931976,0.997988,0.999408,0.984474,1,0.994752,0.967073,0.978871,0.997317,0.996883,0.999961,0.999605,1,0.997317,0.990254,0.997554,0.996804,0.982816,0.974708,0.997396,0.999053,0.995936,0.999053,0.997869,0.994081,0.998619,0.996804,0.997396,0.996843,0.954309,0.995285,0.995305,0.992109,0.961569,0.936336,0.989978,0.979186,1,0.997869,0.99203,0.985026,0.999961,0.997869,0.995778,0.989366,0.998856,0.98761,0.972498,0.999408,0.979897,0.974826,0.987946,0.996528,0.983823,0.997021,0.982146,0.997613,0.998698,0.971019,0.999053,0.999408,0.985815,0.99633,0.985736,0.996804,0.99053,0.994871,0.999803,0.992898,0.996843,0.997554,0.998382,0.999053,0.993647,0.977746,0.995936,0.997593,0.991122,0.99272,0.933377,0.997711]
average_cost
0
f_measure
0.6898202167813196 [0.580645,0.764706,1,0.967742,0.8125,0.545455,0.882353,0.8125,0.551724,0.933333,0.689655,0.857143,0.787879,0.516129,0.8125,0.714286,0.820513,0.384615,0.486486,0.230769,0.764706,0.896552,0.545455,0.941176,0.666667,0.24,0.344828,0.736842,0.827586,0.969697,0.882353,1,0.764706,0.333333,0.758621,0.702703,0.536585,0.421053,0.823529,0.864865,0.705882,0.875,0.8,0.709677,0.733333,0.774194,0.774194,0.75,0.645161,0.810811,0.774194,0.689655,0.702703,0.615385,0.571429,0.230769,0.969697,0.8125,0.6,0.516129,0.969697,0.764706,0.6875,0.516129,0.777778,0.4,0.181818,0.857143,0.384615,0.444444,0.625,0.764706,0.315789,0.777778,0.580645,0.848485,0.882353,0.347826,0.909091,0.827586,0.615385,0.75,0.827586,0.727273,0.588235,0.823529,0.941176,0.606061,0.625,0.8,0.705882,0.8,0.827586,0.615385,0.742857,0.722222,0.666667,0.6,0.173913,0.727273]
kappa
0.6950757575757576
kb_relative_information_score
1130.189658306701
mean_absolute_error
0.013227631721321586
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
0.6956428021511846 [0.6,0.722222,1,1,0.8125,0.529412,0.833333,0.8125,0.615385,1,0.769231,0.789474,0.764706,0.533333,0.8125,0.833333,0.695652,0.5,0.428571,0.3,0.722222,1,0.529412,0.888889,0.647059,0.333333,0.384615,0.636364,0.923077,0.941176,0.833333,1,0.722222,0.357143,0.846154,0.619048,0.44,0.363636,0.777778,0.761905,0.666667,0.875,0.736842,0.733333,0.785714,0.8,0.8,0.75,0.666667,0.714286,0.8,0.769231,0.619048,0.8,0.666667,0.3,0.941176,0.8125,0.642857,0.533333,0.941176,0.722222,0.6875,0.533333,0.7,0.428571,0.176471,0.789474,0.5,0.545455,0.625,0.722222,0.272727,0.7,0.6,0.823529,0.833333,0.571429,0.882353,0.923077,0.8,0.75,0.923077,0.705882,0.555556,0.777778,0.888889,0.588235,0.625,0.736842,0.666667,0.736842,0.923077,0.8,0.684211,0.65,0.647059,0.642857,0.285714,0.705882]
predictive_accuracy
0.698125
prior_entropy
6.6438561897747395
recall
0.698125 [0.5625,0.8125,1,0.9375,0.8125,0.5625,0.9375,0.8125,0.5,0.875,0.625,0.9375,0.8125,0.5,0.8125,0.625,1,0.3125,0.5625,0.1875,0.8125,0.8125,0.5625,1,0.6875,0.1875,0.3125,0.875,0.75,1,0.9375,1,0.8125,0.3125,0.6875,0.8125,0.6875,0.5,0.875,1,0.75,0.875,0.875,0.6875,0.6875,0.75,0.75,0.75,0.625,0.9375,0.75,0.625,0.8125,0.5,0.5,0.1875,1,0.8125,0.5625,0.5,1,0.8125,0.6875,0.5,0.875,0.375,0.1875,0.9375,0.3125,0.375,0.625,0.8125,0.375,0.875,0.5625,0.875,0.9375,0.25,0.9375,0.75,0.5,0.75,0.75,0.75,0.625,0.875,1,0.625,0.625,0.875,0.75,0.875,0.75,0.5,0.8125,0.8125,0.6875,0.5625,0.125,0.75]
relative_absolute_error
0.6680622081475537
root_mean_prior_squared_error
0.09949874371066209
root_mean_squared_error
0.07452690078652034
root_relative_squared_error
0.7490235354452439
total_cost
0
area_under_roc_curve
0.9916035994347588 [0.955975,1,1,1,0.993671,1,1,1,0.993671,1,0.981013,1,0.996835,0.993671,1,1,1,0.990506,1,0.987421,1,1,0.993711,1,0.993711,0.987342,0.955696,0.996835,0.977848,1,1,1,1,1,1,0.993711,0.993711,0.993711,0.993711,1,1,0.993711,0.996835,0.996835,1,0.974684,1,1,1,0.973101,0.990506,1,1,1,1,1,1,1,0.968553,1,1,1,0.996835,0.993671,1,1,0.96519,1,1,0.91195,0.993671,1,0.987342,1,1,1,1,0.974684,1,1,0.987342,1,0.987421,1,0.968354,0.981013,1,1,0.996835,1,0.990506,1,1,0.971519,1,0.996835,0.993711,0.996835,0.848101,1]
area_under_roc_curve
0.9888120969668017 [0.987421,1,1,1,1,1,1,1,1,1,0.996835,0.993671,0.996835,0.693038,1,1,1,0.974684,0.990506,1,1,0.987421,1,1,1,0.958861,0.987342,0.990506,1,1,1,1,1,0.987342,0.993671,0.987421,0.924528,1,1,1,0.987421,1,1,0.971519,1,1,1,1,0.981013,0.996835,1,0.96519,1,1,1,0.974843,1,1,1,0.968354,1,0.981132,1,0.977848,1,0.96519,0.993671,1,1,1,0.981013,1,0.974684,1,1,1,0.993671,0.968354,1,0.993671,0.993671,1,1,1,1,1,1,1,1,1,1,1,1,0.946203,1,1,1,0.993671,0.962025,1]
area_under_roc_curve
0.9892474723350052 [0.977848,1,1,1,0.996835,0.990506,1,1,0.990506,1,0.981013,1,1,1,0.996835,0.974684,1,0.96519,1,0.89557,1,1,0.976266,1,0.987421,0.993671,1,0.993711,1,1,1,1,1,0.981013,1,0.993711,0.993711,0.930818,1,1,1,1,1,1,1,1,1,1,0.704114,1,0.993671,1,1,0.974684,1,1,1,1,0.981132,0.971519,1,1,1,1,1,0.990506,0.990506,1,0.987421,0.974684,0.996835,0.993671,0.993711,0.996835,1,1,1,0.990506,1,1,1,1,1,0.993671,0.987421,1,1,0.996835,0.984177,1,1,1,1,0.990506,1,1,0.996835,0.987342,0.974843,0.981013]
area_under_roc_curve
0.9909556364939102 [0.962025,1,1,1,1,0.987342,1,1,0.993671,1,0.993671,1,1,1,1,1,1,0.996835,0.874214,0.993671,1,1,0.990506,1,0.974843,0.971519,0.97943,1,1,1,1,1,1,0.984177,1,0.993711,1,1,1,1,1,1,1,1,1,1,0.993671,1,1,1,0.990506,1,1,0.974684,1,0.990506,1,1,1,0.987342,1,1,0.996835,0.987421,1,0.984177,0.952532,1,0.993711,0.958861,0.949367,0.990506,0.962264,1,0.987421,0.985759,1,0.914557,1,1,1,1,1,0.987342,0.993711,1,1,0.996835,1,1,0.996835,1,0.893082,0.96519,1,0.993711,0.996835,0.996835,0.987421,0.993671]
area_under_roc_curve
0.9883479868242974 [0.987342,1,1,1,1,0.984177,1,0.996835,0.974843,1,1,1,1,0.858491,1,1,1,0.996835,0.943396,0.993671,0.987342,1,1,1,1,0.996835,0.987342,1,0.987421,1,1,1,0.990506,0.993671,1,1,0.990506,0.931962,1,1,1,1,1,1,1,1,1,1,1,1,1,0.981132,1,0.427673,0.96519,0.971519,1,0.981013,1,0.987421,1,1,1,1,0.996835,1,0.968553,1,0.987342,0.993671,1,1,1,0.996855,0.93038,1,1,0.981013,1,1,1,1,0.914557,1,0.981132,1,1,1,1,1,1,1,1,0.987421,0.981013,1,0.996835,0.993711,0.974843,1]
area_under_roc_curve
0.9898079870233264 [0.996835,1,1,1,1,0.987342,1,1,1,0.987342,0.993671,0.996835,1,1,1,0.996835,1,0.939873,1,0.686709,1,1,0.993671,1,0.996835,0.996835,0.96519,0.987421,1,1,1,1,0.987342,0.987342,1,0.987342,0.990506,0.993671,1,1,0.996835,1,1,1,0.987421,1,1,1,0.990506,1,1,1,1,1,1,0.977848,1,1,0.984177,0.993711,1,1,0.987421,1,1,0.990506,0.981132,1,1,0.987342,0.987342,0.993671,1,1,0.993671,1,1,0.987342,1,1,0.949686,0.993671,1,0.990506,1,1,1,1,1,1,1,1,1,1,1,1,1,0.993711,0.773585,1]
area_under_roc_curve
0.9909231699307377 [0.990506,1,1,1,1,1,1,1,0.993711,1,1,1,1,0.993711,0.949686,0.958861,1,0.91195,0.974684,0.949367,0.996835,1,0.990506,1,0.993671,0.86478,0.968553,0.987342,0.993711,1,0.990506,1,1,0.993711,1,1,0.996835,1,1,1,0.993671,1,1,1,1,0.993671,0.996835,0.993671,1,1,1,1,1,0.974843,0.981013,0.971519,1,0.996835,0.996835,0.987421,1,1,1,0.962025,1,0.993711,0.937107,1,0.984177,0.962025,1,1,1,1,0.993671,1,1,0.981132,1,1,0.963608,1,0.987342,1,1,1,1,0.962264,1,1,1,1,0.996835,1,0.987421,1,1,0.968553,0.939873,1]
area_under_roc_curve
0.9894282153092904 [1,1,1,1,1,0.993671,1,1,0.993711,1,1,1,0.993671,0.993711,0.993711,0.981013,1,1,0.987342,0.987342,0.993671,1,1,1,1,0.962264,0.974843,1,1,1,1,1,1,1,1,1,0.984177,0.981013,1,1,1,1,1,1,1,1,1,1,1,1,0.993711,0.996835,0.713608,1,0.990506,0.985759,1,1,0.987342,1,1,0.990506,0.993711,0.996835,1,0.974843,0.949686,1,0.927215,0.990506,1,1,1,0.974843,0.996835,1,1,0.993711,1,1,0.993671,1,0.990506,1,0.977848,0.987342,1,1,0.993711,1,1,1,1,0.962264,1,1,0.971519,1,0.878165,1]
area_under_roc_curve
0.9909983032799936 [0.993711,0.996835,1,1,0.996835,0.993711,0.996835,0.993711,0.981013,1,1,1,0.981013,0.996835,1,0.974843,1,1,1,1,1,1,0.937107,1,1,0.883648,0.962264,1,1,1,1,1,1,1,1,1,0.974684,0.971519,1,1,1,1,0.984177,0.996835,1,1,1,0.993671,0.930818,0.987421,1,0.990506,1,0.931962,0.974684,0.930818,1,1,1,0.981013,1,1,0.990506,1,1,1,0.990506,1,0.946203,1,1,1,0.955696,1,0.968354,1,1,1,1,1,0.996835,0.993711,1,1,0.996835,1,1,0.987342,1,0.987342,1,0.990506,1,0.987342,1,0.993671,0.981132,1,0.958861,1]
area_under_roc_curve
0.9947516121327921 [0.974843,1,1,1,1,1,1,0.974843,1,1,1,1,1,0.996835,0.996835,1,1,0.981132,0.993671,0.937107,0.996835,1,0.993711,1,1,1,0.993711,1,1,1,1,1,1,0.993711,1,1,0.996835,0.971519,0.993671,1,0.987421,1,1,1,1,1,1,0.993671,1,1,0.993671,0.996835,1,0.946203,1,0.987421,1,1,0.990506,0.987342,1,0.996835,0.993671,0.993671,1,0.987421,0.981013,1,1,1,0.955975,1,0.981013,0.996835,0.993671,0.990506,1,1,1,1,1,0.974843,1,0.993711,0.993671,1,0.996835,0.990506,1,0.993671,1,0.996835,1,0.996835,1,0.993671,0.943396,0.996835,1,1]
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
0.7347124077217639
kappa
0.6906077348066298
kappa
0.7157857340228161
kappa
0.6400236826524571
kappa
0.7030719418779121
kappa
0.6842562260725421
kappa
0.7094583925469762
kappa
0.6714060031595577
kappa
0.6778141903897027
kappa
0.7220247966516623
kb_relative_information_score
107.4790369606146
kb_relative_information_score
113.71235027144725
kb_relative_information_score
115.88244381412935
kb_relative_information_score
113.75898278998383
kb_relative_information_score
115.4927925220164
kb_relative_information_score
112.9466202159691
kb_relative_information_score
115.0101437152909
kb_relative_information_score
116.83932193997288
kb_relative_information_score
112.56194909274517
kb_relative_information_score
106.50601698453328
mean_absolute_error
0.014414874142401593
mean_absolute_error
0.012859900377399675
mean_absolute_error
0.012742475441225264
mean_absolute_error
0.012982173382172404
mean_absolute_error
0.012658815386002845
mean_absolute_error
0.0133101703851698
mean_absolute_error
0.012757152534964724
mean_absolute_error
0.01262077880452854
mean_absolute_error
0.013096821789321592
mean_absolute_error
0.014833154970029582
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
0.7375
predictive_accuracy
0.69375
predictive_accuracy
0.71875
predictive_accuracy
0.64375
predictive_accuracy
0.70625
predictive_accuracy
0.6875
predictive_accuracy
0.7125
predictive_accuracy
0.675
predictive_accuracy
0.68125
predictive_accuracy
0.725
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
0.7375 [0,1,1,1,0.5,1,1,1,0,1,0.5,1,1,0.5,1,1,1,0,1,0,1,1,0,1,0,0.5,0,1,0.5,1,1,1,1,0,0,1,0,1,1,1,1,1,1,0.5,0.5,0.5,1,1,1,0.5,1,1,1,1,1,1,1,1,0,1,1,1,0.5,0.5,1,0.5,0.5,1,0,0,1,1,0.5,1,1,1,1,0,1,1,0.5,1,0,1,0.5,0.5,1,1,1,1,0.5,1,1,0.5,1,1,1,1,0,1]
recall
0.69375 [1,1,1,1,1,1,0.5,1,1,1,1,0.5,1,0.5,1,1,1,0,0,1,1,0,1,1,1,0,0.5,1,1,1,1,1,1,0,0.5,0,0,1,1,1,1,1,1,0.5,1,1,1,1,0,1,0.5,0,1,1,1,0,1,1,1,0.5,1,0,1,0.5,1,0,0,1,1,1,0.5,1,0,1,1,1,0.5,0.5,1,0,0.5,1,1,1,1,1,1,1,0,1,0,1,1,0.5,0.5,0.5,1,0,0,1]
recall
0.71875 [0.5,0.5,1,1,0.5,0.5,1,1,0,1,0.5,1,1,1,0.5,0.5,1,0.5,1,0,1,1,0.5,1,1,0,0.5,1,1,1,1,1,1,0.5,1,0,1,0,1,1,0,1,1,1,1,1,0.5,1,0.5,1,1,1,1,0.5,1,1,1,1,0,0,1,1,0.5,1,1,0.5,0,1,0,0.5,0.5,1,0,1,1,1,1,0,1,1,0,1,1,0.5,0,1,1,0.5,1,1,1,1,1,0.5,1,1,1,0.5,0,0.5]
recall
0.64375 [0.5,1,1,1,0.5,0,1,1,0.5,0.5,0,1,1,0.5,1,0.5,1,0.5,0,0,1,1,0.5,1,0,0,0.5,1,1,1,1,1,1,0,1,1,1,1,1,1,1,0,1,1,1,1,0.5,1,1,1,0.5,0,1,0,1,0,1,1,1,0.5,1,1,0.5,0,0.5,0,0,1,1,0.5,0.5,0.5,0,1,0,0.5,1,0,1,0.5,1,0.5,1,0.5,1,1,1,0.5,1,1,1,1,0,0.5,1,0,0.5,0.5,0,0]
recall
0.70625 [0,1,1,1,1,0.5,1,1,0,1,1,1,1,0,1,1,1,0.5,0,0,0.5,1,1,1,1,0.5,1,1,0,1,1,1,0,0.5,1,1,1,0,0.5,1,1,1,1,1,1,0,1,0.5,1,1,1,0,0.5,0,0,0,1,0.5,0.5,1,1,1,1,1,0.5,0,0,1,0,0.5,1,1,0,1,0.5,1,1,0,1,1,1,1,0.5,1,0,1,1,1,0.5,1,1,1,1,0,0.5,1,1,1,0,0.5]
recall
0.6875 [1,1,1,1,1,0.5,1,0.5,1,0.5,0,1,0,1,1,1,1,0.5,1,0,0.5,0.5,0.5,1,1,0,0,0,1,1,1,1,0.5,0,0,0.5,0.5,1,1,1,1,0.5,1,1,1,1,0.5,0.5,0,1,1,1,1,1,1,0,1,1,0,1,1,1,1,1,1,0.5,1,1,0.5,0,0.5,0.5,1,1,0,1,1,0.5,1,1,0,0.5,1,0.5,0,1,1,1,0.5,1,1,0.5,0,1,1,1,0.5,1,0,1]
recall
0.7125 [0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,0,0,0.5,1,1,0,1,1,0,0,0.5,1,1,0.5,1,1,1,1,1,1,1,1,1,0,1,1,1,0,0.5,0.5,0.5,1,1,0,1,1,0,0.5,0,1,0.5,0.5,0,1,0.5,1,0,1,1,0,1,0.5,0,1,1,1,1,1,1,1,0,1,1,0.5,1,0.5,0.5,1,1,1,0,0,1,1,1,0,1,1,1,1,0,0,1]
recall
0.675 [1,1,1,0.5,1,0.5,1,1,0,1,1,1,1,0,0,0.5,1,1,1,0.5,0.5,0.5,1,1,0.5,0,0,1,0,1,1,1,1,1,1,1,0.5,0,1,1,1,1,1,0,0,1,1,1,1,1,1,1,0,1,0.5,0,1,1,0.5,1,1,0.5,1,0,1,0,0,1,0,0.5,0,1,1,0,0.5,1,1,0,1,1,0,0,0.5,1,0.5,0.5,1,0,0,1,0,1,1,0,0,1,0.5,0,0,1]
recall
0.68125 [1,0.5,1,1,1,1,1,0,0.5,1,1,1,0.5,0.5,1,0,1,0,1,0,1,1,0,1,0.5,0,0,1,0.5,1,1,1,1,1,1,1,0.5,0,1,1,1,1,0,1,0,1,1,0.5,0,1,1,0.5,1,0.5,0,0,1,0,1,0,1,1,0.5,1,1,1,0.5,0,0,0,1,1,0,0.5,0.5,1,1,1,1,0.5,0.5,1,1,1,0.5,1,1,0.5,1,0.5,1,0.5,1,0.5,1,0.5,0,0.5,0.5,1]
recall
0.725 [0,0.5,1,1,1,0,1,0,1,1,1,1,0.5,0,1,1,1,0,0.5,0,1,1,1,1,0.5,1,0,1,1,1,1,1,1,0,0.5,1,1,0.5,0.5,1,1,1,1,0.5,1,0.5,1,1,1,1,0.5,0.5,1,0,0,0,1,1,1,0.5,1,1,0.5,0.5,1,1,0,1,0.5,1,0,0,0,1,0.5,0.5,1,1,0,1,1,0,1,1,1,1,1,0.5,1,0.5,1,1,1,0.5,1,1,0,1,0.5,1]
relative_absolute_error
0.7280239465859378
relative_absolute_error
0.6494899180504876
relative_absolute_error
0.6435593657184466
relative_absolute_error
0.6556653223319385
relative_absolute_error
0.639334110404183
relative_absolute_error
0.6722308275338271
relative_absolute_error
0.6443006330790254
relative_absolute_error
0.6374130709357838
relative_absolute_error
0.6614556459253319
relative_absolute_error
0.7491492409105838
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
0.07805923487772606
root_mean_squared_error
0.07341600937453242
root_mean_squared_error
0.07283696562041105
root_mean_squared_error
0.0742190936521689
root_mean_squared_error
0.07233204171319466
root_mean_squared_error
0.07530360235529684
root_mean_squared_error
0.07267552419713524
root_mean_squared_error
0.07189795706625754
root_mean_squared_error
0.07450667321318293
root_mean_squared_error
0.07962969431005533
root_relative_squared_error
0.7845248288231543
root_relative_squared_error
0.7378586566682986
root_relative_squared_error
0.7320390479724821
root_relative_squared_error
0.7459299573469464
root_relative_squared_error
0.7269643717666732
root_relative_squared_error
0.7568296799231595
root_relative_squared_error
0.7304165006190676
root_relative_squared_error
0.7226016569147206
root_relative_squared_error
0.7488202406840938
root_relative_squared_error
0.8003085399913686
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
47414.83813599916
usercpu_time_millis
47506.53817700004
usercpu_time_millis
48299.85212900101
usercpu_time_millis
47776.04468999925
usercpu_time_millis
47602.817289000086
usercpu_time_millis
47101.339050001116
usercpu_time_millis
47470.40525599914
usercpu_time_millis
47760.939852001684
usercpu_time_millis
47074.12381500217
usercpu_time_millis
47255.020711001634
usercpu_time_millis_testing
4.212124000332551
usercpu_time_millis_testing
4.081281998878694
usercpu_time_millis_testing
4.046100000778097
usercpu_time_millis_testing
4.083960999196279
usercpu_time_millis_testing
4.527652999968268
usercpu_time_millis_testing
4.151000001002103
usercpu_time_millis_testing
4.046474999995553
usercpu_time_millis_testing
4.1407260014239
usercpu_time_millis_testing
4.134251001232769
usercpu_time_millis_testing
4.058858001371846
usercpu_time_millis_training
47410.62601199883
usercpu_time_millis_training
47502.45689500116
usercpu_time_millis_training
48295.80602900023
usercpu_time_millis_training
47771.96072900006
usercpu_time_millis_training
47598.28963600012
usercpu_time_millis_training
47097.18805000011
usercpu_time_millis_training
47466.358780999144
usercpu_time_millis_training
47756.79912600026
usercpu_time_millis_training
47069.989564000934
usercpu_time_millis_training
47250.96185300026