5986382
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)
4021115
bootstrap
true
6902
class_weight
null
6902
criterion
"gini"
6902
max_depth
null
6902
max_features
0.6253824636308909
6902
max_leaf_nodes
null
6902
min_impurity_split
1e-07
6902
min_samples_leaf
12
6902
min_samples_split
8
6902
min_weight_fraction_leaf
0.0
6902
n_estimators
100
6902
n_jobs
1
6902
oob_score
false
6902
random_state
49297
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
1491
one-hundred-plants-margin
https://www.openml.org/data/download/1592283/phpCsX3fx
-1
12896059
description
https://api.openml.org/data/download/12896059/description.xml
-1
12896060
predictions
https://api.openml.org/data/download/12896060/predictions.arff
area_under_roc_curve
0.9945241477272724 [0.987098,0.999092,0.999921,1,0.999329,0.991911,0.999053,0.999211,0.996567,0.999921,0.997988,0.999684,0.998777,0.986821,0.999645,0.999408,0.999921,0.988636,0.986387,0.969973,0.998422,0.999763,0.994831,1,0.998422,0.970447,0.984651,0.998343,0.997277,0.999763,0.99925,0.999961,0.998067,0.989978,0.999171,0.996015,0.991517,0.987058,0.996962,0.999527,0.998461,0.999014,0.999132,0.997001,0.997159,0.999645,0.99637,0.997672,0.995186,0.995778,0.997633,0.991872,0.995147,0.981416,0.994594,0.981968,1,0.998737,0.990215,0.984138,0.999882,0.999014,0.989702,0.995502,0.996449,0.995068,0.985401,0.999171,0.977667,0.993411,0.992109,0.997869,0.99562,0.999961,0.970841,0.994437,0.999053,0.989938,0.998895,0.996686,0.990057,0.993726,0.997475,0.995896,0.993095,0.997001,0.999961,0.994831,0.99858,1,0.99925,0.998895,0.99712,0.990254,0.995226,0.998146,0.996094,0.992819,0.968158,0.99925]
average_cost
0
f_measure
0.7087541219516079 [0.444444,0.736842,1,1,0.909091,0.592593,0.9375,0.83871,0.6875,0.888889,0.777778,0.833333,0.722222,0.434783,0.941176,0.814815,0.820513,0.648649,0.5,0.24,0.722222,0.875,0.727273,1,0.733333,0.285714,0.214286,0.709677,0.823529,0.875,0.903226,0.903226,0.848485,0.5,0.882353,0.619048,0.588235,0.466667,0.8,0.914286,0.736842,0.833333,0.7,0.742857,0.666667,0.875,0.684211,0.785714,0.666667,0.75,0.866667,0.571429,0.787879,0.615385,0.666667,0.516129,0.969697,0.83871,0.181818,0.518519,0.941176,0.744186,0.5625,0.777778,0.717949,0.702703,0.516129,0.689655,0.285714,0.6,0.545455,0.764706,0.611111,0.967742,0.363636,0.666667,0.848485,0.608696,0.8,0.666667,0.380952,0.594595,0.727273,0.6,0.722222,0.774194,0.941176,0.628571,0.864865,0.969697,0.820513,0.75,0.758621,0.72,0.903226,0.833333,0.75,0.642857,0.2,0.777778]
kappa
0.7209595959595959
kb_relative_information_score
1040.4699185819597
mean_absolute_error
0.015379164182494364
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
0.7332730231441529 [0.545455,0.636364,1,1,0.882353,0.727273,0.9375,0.866667,0.6875,0.8,0.7,0.75,0.65,0.714286,0.888889,1,0.695652,0.571429,0.45,0.333333,0.65,0.875,0.705882,1,0.785714,0.6,0.25,0.733333,0.777778,0.875,0.933333,0.933333,0.823529,0.583333,0.833333,0.5,0.555556,0.5,0.857143,0.842105,0.636364,0.75,0.583333,0.684211,0.818182,0.875,0.590909,0.916667,0.647059,0.75,0.928571,0.526316,0.764706,0.8,0.647059,0.533333,0.941176,0.866667,0.333333,0.636364,0.888889,0.592593,0.5625,0.7,0.608696,0.619048,0.533333,0.769231,0.6,0.642857,1,0.722222,0.55,1,0.666667,1,0.823529,1,0.666667,1,0.8,0.52381,0.705882,0.5,0.65,0.8,0.888889,0.578947,0.761905,0.941176,0.695652,0.625,0.846154,1,0.933333,0.75,0.75,0.75,0.5,0.7]
predictive_accuracy
0.72375
prior_entropy
6.6438561897747395
recall
0.72375 [0.375,0.875,1,1,0.9375,0.5,0.9375,0.8125,0.6875,1,0.875,0.9375,0.8125,0.3125,1,0.6875,1,0.75,0.5625,0.1875,0.8125,0.875,0.75,1,0.6875,0.1875,0.1875,0.6875,0.875,0.875,0.875,0.875,0.875,0.4375,0.9375,0.8125,0.625,0.4375,0.75,1,0.875,0.9375,0.875,0.8125,0.5625,0.875,0.8125,0.6875,0.6875,0.75,0.8125,0.625,0.8125,0.5,0.6875,0.5,1,0.8125,0.125,0.4375,1,1,0.5625,0.875,0.875,0.8125,0.5,0.625,0.1875,0.5625,0.375,0.8125,0.6875,0.9375,0.25,0.5,0.875,0.4375,1,0.5,0.25,0.6875,0.75,0.75,0.8125,0.75,1,0.6875,1,1,1,0.9375,0.6875,0.5625,0.875,0.9375,0.75,0.5625,0.125,0.875]
relative_absolute_error
0.7767254637623402
root_mean_prior_squared_error
0.09949874371066209
root_mean_squared_error
0.08112955705184337
root_relative_squared_error
0.8153827277233219
total_cost
0
area_under_roc_curve
0.9934365297348936 [1,0.996835,1,1,1,1,1,1,0.993671,1,0.993671,0.996835,1,0.968354,1,0.993711,1,0.993671,0.962025,0.993711,1,1,0.993711,1,0.993711,0.990506,0.962025,1,1,1,0.990506,1,0.990506,0.993671,1,0.981132,1,0.993711,1,1,1,1,1,0.993671,1,1,1,1,1,0.962025,0.996835,1,1,0.984177,1,1,1,1,0.987421,0.990506,1,1,1,0.993671,1,1,0.990506,1,1,0.993711,0.984177,1,1,1,1,1,1,0.987342,1,1,0.993671,1,0.993711,1,0.974684,0.993671,1,1,0.996835,1,1,1,1,0.990506,1,0.993671,1,0.993671,0.860759,1]
area_under_roc_curve
0.9932434718573362 [0.981132,1,1,1,1,0.987421,0.996835,1,1,1,1,0.996835,0.996835,0.955696,1,1,1,0.962025,0.990506,0.981132,1,1,1,1,1,0.949367,0.987342,1,1,1,1,1,1,0.996835,1,0.974843,0.974843,1,0.993711,1,1,1,1,0.993671,1,1,1,1,0.993671,1,1,0.952532,1,1,0.993711,0.968553,1,1,1,0.943038,1,1,0.993671,0.987342,1,0.996835,0.990506,1,0.955975,1,1,1,1,1,1,1,1,0.993671,1,0.987342,0.96519,0.990506,1,0.993711,1,1,1,0.996835,1,1,0.996835,1,1,0.968354,1,1,1,0.981013,0.993671,1]
area_under_roc_curve
0.9953370054135817 [0.993671,1,1,1,1,0.993671,0.993711,1,0.996835,1,1,1,1,0.993671,1,1,1,0.993671,1,0.898734,1,0.993711,0.993671,1,1,0.990506,1,1,1,1,1,1,1,0.981013,1,1,0.993711,0.968553,1,1,0.996835,1,1,1,0.993671,1,0.993671,1,0.990506,1,0.996835,1,1,1,1,1,1,1,0.974843,0.984177,1,0.993711,1,1,0.990506,0.990506,0.981013,1,0.987421,0.984177,0.996835,1,1,1,1,1,1,0.987342,0.993671,0.996835,1,1,1,1,1,1,1,1,0.996835,1,1,1,1,0.984177,1,1,1,0.993671,0.974843,1]
area_under_roc_curve
0.9959308574158104 [0.990506,0.996835,1,1,1,0.984177,1,1,0.993671,1,1,1,1,0.993671,1,1,1,1,0.937107,0.996835,1,1,1,1,0.993711,0.981013,0.974684,1,1,1,1,1,1,0.990506,1,1,1,0.993711,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.936709,1,0.993671,1,1,1,0.990506,1,1,0.993671,1,0.993671,1,0.984177,0.993671,1,1,0.996835,0.996835,0.993711,1,0.987421,0.993671,1,0.990506,1,1,0.993711,1,1,0.993671,0.993711,1,1,1,1,1,1,1,0.987421,1,1,0.987421,0.987342,0.993671,1,1]
area_under_roc_curve
0.9933220882095377 [1,1,1,1,1,1,1,1,1,1,0.996835,1,0.993711,0.974843,1,1,1,0.996835,0.993711,0.987342,0.996835,1,1,1,1,0.987342,0.984177,1,1,1,1,1,1,0.974684,1,1,1,0.962025,0.996835,1,1,1,1,1,1,1,1,1,1,1,1,0.974843,0.996835,1,0.984177,0.987342,1,0.996835,0.993671,1,1,1,0.987421,1,0.993671,1,0.968553,1,0.962025,0.987342,0.996835,1,0.993711,1,0.857595,1,1,0.987342,1,1,1,1,0.993671,0.993671,0.968553,0.993711,1,1,1,1,1,0.990506,1,0.981132,0.958861,1,0.996835,1,0.987421,0.996835]
area_under_roc_curve
0.9954937405461346 [0.968354,1,1,1,1,0.984177,1,1,1,1,0.996835,1,1,1,1,1,1,1,1,0.943038,1,1,0.996835,1,1,0.996835,0.977848,1,1,1,1,1,0.993671,0.993671,0.987421,0.996835,0.981013,1,0.990506,1,0.996835,1,1,1,1,1,1,0.996835,1,0.993671,1,1,0.996835,1,0.993671,0.984177,1,1,0.987342,0.993711,1,1,0.987421,1,1,0.996835,1,1,0.984177,1,0.977848,0.990506,1,1,0.981013,0.987421,1,1,1,1,0.993711,0.993671,1,0.993671,1,1,1,1,0.993671,1,1,1,0.987421,1,1,1,1,0.981132,1,1]
area_under_roc_curve
0.996290601862909 [1,1,1,1,1,0.996835,1,1,0.993711,1,1,1,1,0.993711,1,0.996835,1,1,1,0.946203,0.990506,1,0.993671,1,0.996835,0.930818,0.987421,0.993671,1,1,1,1,1,0.968553,1,1,1,1,1,1,1,0.996835,1,1,0.974843,0.996835,0.990506,0.996835,1,1,1,1,1,1,0.990506,0.993671,1,1,0.993671,1,1,1,1,0.993671,1,1,0.974843,0.996835,0.990506,1,0.993711,1,0.996835,1,1,0.993711,1,0.993711,1,1,0.974684,1,1,0.996835,1,1,1,0.968553,1,1,1,1,0.993671,1,1,1,1,1,1,1]
area_under_roc_curve
0.9943538034392165 [1,1,1,1,1,0.996835,1,1,0.993711,1,0.993711,1,1,1,0.993711,1,1,0.987421,0.968354,0.993671,0.996835,1,1,1,1,0.993711,0.987421,1,0.949686,0.996835,1,1,1,1,1,1,0.990506,0.993671,1,1,1,1,1,1,1,0.993671,0.996835,1,0.987421,1,0.993711,0.996835,0.984177,1,0.996835,0.958861,1,1,0.977848,0.974843,1,0.996835,0.993711,1,1,0.949686,0.993711,1,0.955696,0.987342,1,1,1,1,0.996835,1,1,0.987421,1,1,0.984177,0.987421,0.981013,1,1,0.981013,1,0.981132,1,1,1,1,1,0.993711,1,0.993671,0.981013,0.993711,0.981013,1]
area_under_roc_curve
0.9952641111376485 [0.981132,1,1,1,1,0.993711,1,1,0.996835,1,0.993711,1,1,1,1,1,1,1,1,1,1,1,0.949686,1,1,0.91195,0.993711,1,1,1,1,1,1,0.993711,1,1,1,0.984177,1,1,0.993711,1,0.996835,0.993671,1,1,1,1,0.993711,1,1,0.993671,1,0.958861,0.993671,0.968553,1,1,1,0.987342,1,1,1,1,1,1,0.987342,1,0.990506,1,1,0.987421,0.993671,1,0.990506,0.974684,1,1,1,1,0.993671,0.974843,1,0.993711,1,1,1,0.996835,1,1,1,1,1,0.993671,1,0.996835,0.993711,0.993671,0.943038,1]
area_under_roc_curve
0.9958584607117269 [0.949686,1,0.993711,1,1,0.993711,1,0.981132,1,1,1,1,0.996835,0.993671,1,1,1,0.993711,0.993671,1,1,1,1,1,1,0.90566,0.993711,1,0.996835,1,1,0.996835,1,1,0.993671,0.993671,0.993671,1,1,1,1,1,1,1,1,1,1,0.990506,0.987421,1,1,1,1,0.984177,1,1,1,1,0.996835,0.993671,1,0.996835,0.974684,0.990506,0.987421,1,0.993671,1,0.993671,0.993711,0.974843,1,0.984177,1,0.984177,0.993671,1,1,1,0.990506,1,0.981132,1,0.968553,1,1,1,1,1,1,1,0.996835,0.996835,1,1,1,0.993711,1,1,1]
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
0.6842063711364623
kappa
0.7537198563365829
kappa
0.7410492243318991
kappa
0.6842313005723307
kappa
0.7410185550730359
kappa
0.7346914603813811
kappa
0.7599115463591849
kappa
0.7220467466835123
kappa
0.7157296272899558
kappa
0.6716264751154438
kb_relative_information_score
102.69733288396064
kb_relative_information_score
103.51052578961745
kb_relative_information_score
103.86241253032124
kb_relative_information_score
103.93085578937372
kb_relative_information_score
104.10184190596064
kb_relative_information_score
104.70026452367603
kb_relative_information_score
105.94510631616194
kb_relative_information_score
103.56130289520006
kb_relative_information_score
104.73323279468181
kb_relative_information_score
103.42704315300507
mean_absolute_error
0.015477426753797
mean_absolute_error
0.015373193205534092
mean_absolute_error
0.015410401019633016
mean_absolute_error
0.01544908508549869
mean_absolute_error
0.015297185958639086
mean_absolute_error
0.015369304423625446
mean_absolute_error
0.015180609871288372
mean_absolute_error
0.015396569461995654
mean_absolute_error
0.015358643008505484
mean_absolute_error
0.015479223036426907
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
0.6875
predictive_accuracy
0.75625
predictive_accuracy
0.74375
predictive_accuracy
0.6875
predictive_accuracy
0.74375
predictive_accuracy
0.7375
predictive_accuracy
0.7625
predictive_accuracy
0.725
predictive_accuracy
0.71875
predictive_accuracy
0.675
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
0.6875 [1,0.5,1,1,1,1,1,1,0,1,0.5,0.5,0.5,0,1,0,1,0,0.5,1,1,1,1,1,0,0,0,1,0.5,0,0.5,1,0.5,0,1,0,1,1,1,1,1,1,1,1,0,1,1,1,1,0.5,1,1,1,0,1,1,1,1,0,0.5,1,1,1,0.5,1,1,0.5,1,1,0,0.5,1,0.5,1,0,0.5,0.5,0.5,1,0.5,0,1,0,1,0.5,0.5,1,1,1,1,1,1,1,0.5,1,1,1,0.5,0,1]
recall
0.75625 [0,1,1,1,1,1,0.5,1,1,1,1,1,1,0.5,1,1,1,0.5,0.5,1,1,1,1,1,1,0.5,0,0.5,1,1,1,1,1,0.5,1,0,0,1,1,1,1,1,1,0.5,1,1,1,1,0.5,1,1,0,1,0.5,1,0,1,1,0,0.5,1,1,1,1,1,0,0.5,1,0,1,0.5,1,1,1,1,0,0.5,0.5,1,0,0,0.5,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,0.5,0,1]
recall
0.74375 [0,1,1,1,1,0.5,1,1,1,1,1,1,1,0.5,1,1,1,0.5,1,0,1,0,0,1,1,0.5,0.5,1,1,1,1,1,1,0,1,1,1,0,1,1,1,1,1,1,0.5,1,0.5,1,0.5,1,0.5,1,1,1,1,0,1,1,1,0,1,1,0.5,1,0.5,1,0.5,0.5,0,0.5,0,1,1,1,0,0.5,1,0.5,1,0.5,0,1,0.5,0.5,1,1,1,0.5,1,1,1,1,1,0.5,1,1,1,1,0,1]
recall
0.6875 [0,1,1,1,0.5,0,1,0.5,0.5,1,1,1,1,0.5,1,0.5,1,1,0,0,1,1,1,1,0,0,0,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,0,1,1,1,0.5,1,1,1,0.5,1,0.5,1,1,0.5,1,1,1,0.5,1,0,0.5,0,0.5,1,0.5,0,0.5,1,0.5,1,0.5,1,0.5,1,1,1,0,1,0,1,1,1,1,0,0.5,1,1,0,0.5,0,0]
recall
0.74375 [0.5,1,1,1,1,1,1,1,1,1,1,1,0,0,1,0.5,1,1,1,0.5,0.5,1,1,1,0.5,0.5,0.5,1,1,1,1,0,1,0.5,1,1,1,0,0.5,1,1,1,1,1,1,1,1,0.5,0.5,1,1,0,0.5,0,0.5,0,1,1,0,1,1,1,1,1,0.5,1,0,0,0,0.5,0.5,1,1,1,0,1,1,0,1,1,1,1,1,0.5,1,0,1,1,1,1,1,0.5,1,1,0.5,1,0.5,1,1,1]
recall
0.7375 [0.5,1,1,1,1,0,1,0.5,1,1,0.5,1,1,1,1,1,1,1,0,0,0.5,0.5,1,1,1,0,0,0,1,1,1,1,0.5,1,1,0.5,0.5,1,0.5,1,0.5,1,0,1,1,1,1,0,1,0.5,1,1,1,1,0.5,1,1,1,0,1,1,1,0,1,1,1,1,1,0,0.5,0.5,0.5,1,1,0.5,1,1,0.5,1,1,0,0.5,1,0.5,0,1,1,1,1,1,1,1,0,1,1,1,1,0,0,1]
recall
0.7625 [1,1,1,1,1,0,1,1,1,1,1,1,1,0,1,1,1,1,1,0,0.5,1,1,1,0.5,0,0,0.5,1,1,0.5,0,1,0,1,1,1,0.5,0.5,1,1,0.5,1,1,0,0.5,0.5,1,1,1,1,1,1,0,0.5,0.5,1,0.5,0,1,1,1,1,1,1,1,0,0.5,0.5,0.5,1,1,1,1,0,1,1,1,1,1,0,1,1,1,1,1,1,0,1,1,1,1,0,1,1,1,1,1,0,1]
recall
0.725 [0.5,1,1,1,1,0.5,1,1,1,1,1,1,1,0,1,0.5,1,1,0.5,0,1,1,0.5,1,0.5,0,1,1,0,1,1,1,1,1,1,1,0.5,0,1,1,1,1,1,0,0,1,1,1,1,1,0,0.5,0.5,1,1,0.5,1,1,0,0,1,1,0,1,1,0,1,0.5,0,1,0,1,1,1,0.5,1,1,0,1,1,0,0,0,1,0.5,0.5,1,0,1,1,1,1,1,1,1,0.5,0.5,1,0,1]
recall
0.71875 [0,1,1,1,1,1,1,1,0,1,1,1,1,0.5,1,0,1,1,1,0,1,1,0,1,1,0,0,1,1,1,1,1,1,1,1,1,0,0,1,1,0,1,0.5,1,0.5,1,1,0.5,0,1,1,0.5,0.5,0.5,0.5,0,1,0,0,0.5,1,1,0.5,1,1,1,0.5,1,0.5,1,1,0,0,1,0.5,0.5,1,0,1,0.5,0,1,1,1,1,1,1,1,1,1,1,1,0.5,0.5,1,1,1,0,0,1]
recall
0.675 [0,0.5,1,1,1,1,1,0,1,1,1,1,0.5,0,1,1,1,1,0,0,1,1,1,1,1,0,0,0.5,1,0,1,1,1,1,0.5,1,0.5,0.5,0.5,1,1,1,1,1,0.5,0.5,1,0.5,0,1,0.5,0.5,1,0.5,0.5,1,1,1,0,0,1,1,0,0.5,1,1,0.5,0,0,0,0,1,0,1,0,0,1,1,1,0,1,0,1,0,1,1,1,1,1,1,1,1,1,0.5,0,1,1,0.5,0.5,1]
relative_absolute_error
0.781688219888736
relative_absolute_error
0.7764238992693973
relative_absolute_error
0.7783030817996459
relative_absolute_error
0.7802568224999326
relative_absolute_error
0.7725851494262151
relative_absolute_error
0.7762274961426979
relative_absolute_error
0.7666974682468863
relative_absolute_error
0.7776045182826076
relative_absolute_error
0.775689040833609
relative_absolute_error
0.7817789412336809
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
0.08169112329925789
root_mean_squared_error
0.08101913467721653
root_mean_squared_error
0.08120183460745188
root_mean_squared_error
0.08149418650544649
root_mean_squared_error
0.08088538421609193
root_mean_squared_error
0.0809932922189253
root_mean_squared_error
0.0801107467871116
root_mean_squared_error
0.08119916157071608
root_mean_squared_error
0.08092713791450468
root_mean_squared_error
0.08176107925467281
root_relative_squared_error
0.82102668086757
root_relative_squared_error
0.8142729411018153
root_relative_squared_error
0.8161091444891327
root_relative_squared_error
0.8190473916176064
root_relative_squared_error
0.8129286983894295
root_relative_squared_error
0.8140132146235958
root_relative_squared_error
0.8051432992970252
root_relative_squared_error
0.816082279459122
root_relative_squared_error
0.8133483388477468
root_relative_squared_error
0.821729764673516
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
2010.9302459999299
usercpu_time_millis
1838.814887999888
usercpu_time_millis
1878.1612029999906
usercpu_time_millis
1839.501668999901
usercpu_time_millis
1843.2620759999736
usercpu_time_millis
1862.9800149999483
usercpu_time_millis
1818.0082650000031
usercpu_time_millis
1813.7087150000752
usercpu_time_millis
1823.4006080000427
usercpu_time_millis
1832.5175920000447
usercpu_time_millis_testing
32.410125999945194
usercpu_time_millis_testing
32.28032999993502
usercpu_time_millis_testing
31.878894999977092
usercpu_time_millis_testing
32.902489999969475
usercpu_time_millis_testing
32.347360000017034
usercpu_time_millis_testing
33.301149999942936
usercpu_time_millis_testing
32.33967799997117
usercpu_time_millis_testing
32.59914500006289
usercpu_time_millis_testing
32.15849100001833
usercpu_time_millis_testing
32.010684000056244
usercpu_time_millis_training
1978.5201199999847
usercpu_time_millis_training
1806.534557999953
usercpu_time_millis_training
1846.2823080000135
usercpu_time_millis_training
1806.5991789999316
usercpu_time_millis_training
1810.9147159999566
usercpu_time_millis_training
1829.6788650000053
usercpu_time_millis_training
1785.668587000032
usercpu_time_millis_training
1781.1095700000124
usercpu_time_millis_training
1791.2421170000243
usercpu_time_millis_training
1800.5069079999885