6000514
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)
4035246
bootstrap
false
6902
class_weight
null
6902
criterion
"gini"
6902
max_depth
null
6902
max_features
0.8458962901968512
6902
max_leaf_nodes
null
6902
min_impurity_split
1e-07
6902
min_samples_leaf
13
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
46186
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
12924145
description
https://api.openml.org/data/download/12924145/description.xml
-1
12924146
predictions
https://api.openml.org/data/download/12924146/predictions.arff
area_under_roc_curve
0.97959655145202 [0.951468,0.9927,0.995975,0.998106,0.997238,0.9884,0.992424,0.990096,0.992661,0.999329,0.987137,0.986585,0.991832,0.962437,0.99637,0.975971,0.997593,0.969342,0.96804,0.969263,0.995226,0.990215,0.988281,0.999171,0.994792,0.920257,0.921895,0.976484,0.979246,0.99783,0.992109,0.958767,0.992306,0.974156,0.993884,0.993924,0.98114,0.9622,0.990767,0.995857,0.994634,0.997199,0.990945,0.983073,0.988991,0.994437,0.99057,0.993845,0.982915,0.911754,0.982363,0.981968,0.980232,0.965791,0.980607,0.963226,0.999388,0.978042,0.98544,0.957781,0.998106,0.990925,0.919705,0.976326,0.996291,0.988557,0.974195,0.988045,0.932134,0.972143,0.955492,0.996113,0.945589,0.990412,0.936592,0.989781,0.996094,0.948114,0.995522,0.990372,0.975576,0.955788,0.985953,0.959557,0.979403,0.968691,0.995107,0.979403,0.989189,0.99566,0.998146,0.997277,0.987453,0.976997,0.972479,0.975813,0.980548,0.975852,0.931147,0.994437]
average_cost
0
f_measure
0.502834478804061 [0.4375,0.461538,0.722222,0.785714,0.705882,0.3125,0.6875,0.514286,0.516129,0.9375,0.4,0.606061,0.421053,0.363636,0.594595,0.529412,0.787879,0.387097,0.190476,0,0.510638,0.521739,0.352941,0.8,0.709677,0,0.083333,0.482759,0.8125,0.774194,0.648649,0.647059,0.6,0.3125,0.578947,0.702703,0.4,0.181818,0.413793,0.705882,0.705882,0.777778,0.634146,0.4,0.434783,0.541667,0.645161,0.6875,0.648649,0.571429,0.5,0.387097,0.457143,0.25,0.514286,0.25,0.9375,0.580645,0.342857,0.363636,0.727273,0.684211,0.333333,0.666667,0.666667,0.526316,0.1875,0.434783,0.210526,0.230769,0.117647,0.6875,0.512821,0.625,0.24,0.5,0.666667,0.344828,0.628571,0.384615,0.26087,0.606061,0.25,0.363636,0.487805,0.592593,0.75,0.5,0.594595,0.717949,0.8,0.648649,0.428571,0.333333,0.551724,0.484848,0.413793,0.307692,0,0.585366]
kappa
0.5176767676767676
kb_relative_information_score
1045.9600279409078
mean_absolute_error
0.0136489921049716
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
0.5210800725355653 [0.4375,0.391304,0.65,0.916667,0.666667,0.3125,0.6875,0.473684,0.533333,0.9375,0.368421,0.588235,0.363636,0.666667,0.52381,0.5,0.764706,0.4,0.4,0,0.387097,0.857143,0.333333,0.736842,0.733333,0,0.125,0.538462,0.8125,0.8,0.571429,0.611111,0.5,0.3125,0.5,0.619048,0.333333,0.176471,0.461538,0.666667,0.666667,0.7,0.52,0.428571,0.714286,0.40625,0.666667,0.6875,0.571429,0.526316,0.5,0.4,0.421053,0.375,0.473684,0.25,0.9375,0.6,0.315789,0.352941,0.705882,0.590909,0.357143,0.6,0.6,0.454545,0.1875,0.714286,0.666667,0.3,1,0.6875,0.434783,0.625,0.333333,0.75,0.6,0.384615,0.578947,0.5,0.428571,0.588235,0.25,0.352941,0.4,0.727273,0.75,0.5,0.52381,0.608696,0.736842,0.571429,0.5,0.5,0.615385,0.470588,0.461538,0.4,0,0.48]
predictive_accuracy
0.5225
prior_entropy
6.6438561897747395
recall
0.5225 [0.4375,0.5625,0.8125,0.6875,0.75,0.3125,0.6875,0.5625,0.5,0.9375,0.4375,0.625,0.5,0.25,0.6875,0.5625,0.8125,0.375,0.125,0,0.75,0.375,0.375,0.875,0.6875,0,0.0625,0.4375,0.8125,0.75,0.75,0.6875,0.75,0.3125,0.6875,0.8125,0.5,0.1875,0.375,0.75,0.75,0.875,0.8125,0.375,0.3125,0.8125,0.625,0.6875,0.75,0.625,0.5,0.375,0.5,0.1875,0.5625,0.25,0.9375,0.5625,0.375,0.375,0.75,0.8125,0.3125,0.75,0.75,0.625,0.1875,0.3125,0.125,0.1875,0.0625,0.6875,0.625,0.625,0.1875,0.375,0.75,0.3125,0.6875,0.3125,0.1875,0.625,0.25,0.375,0.625,0.5,0.75,0.5,0.6875,0.875,0.875,0.75,0.375,0.25,0.5,0.5,0.375,0.25,0,0.75]
relative_absolute_error
0.689343035604625
root_mean_prior_squared_error
0.09949874371066209
root_mean_squared_error
0.07984060720409358
root_relative_squared_error
0.8024282943337105
total_cost
0
area_under_roc_curve
0.9737053180479261 [1,0.984177,1,1,0.990506,1,1,1,0.968354,0.996855,0.974684,0.968354,0.977848,0.943038,0.993671,0.943396,0.993671,0.955696,0.990506,0.974843,0.981132,0.987421,0.981132,1,0.987421,0.990506,0.686709,1,0.955696,1,0.933544,0.996835,0.968354,0.920886,1,0.987421,1,0.993711,1,0.996835,1,1,1,0.984177,1,0.996835,1,1,1,0.691456,0.993671,1,0.987421,0.952532,1,1,1,1,0.977987,0.996835,1,1,1,0.968354,1,0.996835,0.993671,1,0.987421,1,0.974684,1,0.677215,1,1,1,0.996835,0.984177,1,1,0.974684,0.995253,0.987421,1,0.968354,0.952532,0.981013,1,0.981013,0.955975,1,1,0.996835,0.987342,0.971519,0.971519,1,1,0.85443,1]
area_under_roc_curve
0.980037044224186 [0.993711,1,1,1,1,0.987421,0.996835,1,1,1,0.996835,0.958861,1,0.96519,0.996835,1,0.993671,0.936709,0.955696,0.955975,1,0.993711,0.993711,1,1,0.901899,0.974684,0.898734,1,0.987421,1,1,0.993671,0.993671,1,0.993711,0.974843,1,0.987421,1,1,1,1,0.949367,0.993671,1,1,1,0.993671,1,1,0.955696,0.993711,0.971519,0.981132,0.874214,1,1,0.993711,0.827532,1,0.981132,1,0.955696,1,0.987342,0.984177,1,0.628931,0.974843,0.977848,1,0.996835,1,0.949686,1,0.993671,0.908228,1,0.981013,0.924051,0.977848,0.974843,1,0.96519,1,1,0.993671,1,1,0.993671,1,1,1,0.996835,1,0.943396,0.952532,0.977848,1]
area_under_roc_curve
0.9842542144335644 [0.990506,1,1,0.993711,1,1,0.993711,1,0.993671,1,0.993671,1,1,0.993671,1,1,1,0.939873,0.955975,0.908228,0.993711,1,0.996835,1,1,0.952532,0.987342,0.981132,1,1,0.993711,1,0.993671,0.987342,1,1,0.993711,0.918239,1,1,0.984177,1,1,1,0.974684,1,0.968354,1,0.943038,1,0.987342,1,1,1,1,0.974684,1,1,0.955975,0.927215,0.993711,0.987421,0.990506,1,0.984177,0.987342,0.990506,0.977848,1,0.96519,0.863924,1,1,0.984177,0.955975,1,1,0.838608,0.992089,0.981013,0.962264,1,0.984177,1,1,0.993711,1,0.987342,0.993671,1,1,1,0.974843,0.990506,1,1,0.981013,0.987342,0.90566,0.987342]
area_under_roc_curve
0.9803444192341377 [0.962025,1,1,1,1,0.984177,1,1,0.977848,1,0.968354,1,0.993711,0.990506,1,0.993671,1,1,0.899371,0.968354,1,1,1,1,0.974843,0.987342,0.886076,1,1,1,1,0.990506,1,0.981013,0.981132,1,1,0.987421,0.987421,1,0.996835,1,0.984277,1,0.990506,1,1,1,0.996835,0.631329,0.993671,0.993711,0.836478,0.89557,1,0.974684,1,0.890823,0.993711,0.990506,1,0.962264,0.993671,1,1,1,0.936709,0.981013,1,0.96519,0.943038,0.996835,0.987421,0.996835,0.987421,0.993671,1,0.968354,1,0.996835,0.968553,0.977848,0.996835,0.990506,0.968553,0.930818,1,1,0.996835,1,1,1,1,0.996835,1,0.993711,0.981013,0.996835,0.962264,0.971519]
area_under_roc_curve
0.9778218543507681 [0.876582,0.949686,1,1,1,0.993671,0.987421,0.990506,1,1,0.990506,0.987342,1,0.823899,1,1,1,0.996835,1,0.990506,0.996835,1,1,1,1,0.955696,0.968354,1,1,0.996835,1,0.393082,1,0.939873,1,0.996835,0.984177,0.898734,0.990506,0.996835,0.996835,1,1,0.993711,0.993711,1,1,0.996835,0.955696,1,0.987421,0.974843,1,0.987421,0.93038,0.955696,0.996855,0.987342,1,0.993711,0.996835,1,1,1,1,1,0.899371,0.974684,0.933544,0.981013,0.984177,0.996835,1,0.993711,0.879747,0.993711,0.996835,0.977848,1,1,1,1,0.981013,0.993671,0.937107,0.883648,1,1,1,0.990506,1,0.993671,0.949686,1,0.856013,0.968553,0.990506,0.981132,0.974843,0.993671]
area_under_roc_curve
0.987751522569859 [0.943038,1,0.996835,1,1,0.990506,1,0.968354,1,0.996835,0.990506,1,1,0.987421,1,1,1,0.96519,0.993711,0.968354,1,1,0.987342,1,0.996835,0.981013,0.981013,1,1,0.996835,1,1,0.990506,0.993671,1,0.996835,0.974684,0.993671,0.987342,1,1,1,0.949686,0.987421,0.981132,1,0.996835,0.981013,0.996835,0.984177,1,1,0.974684,1,0.993671,0.977848,1,1,0.988924,1,1,1,0.987421,1,1,0.987342,0.981132,1,0.936709,0.987342,0.943038,0.993671,1,1,0.882911,0.962264,0.996835,0.952532,0.996835,0.993711,0.981132,0.984177,1,0.992089,0.968553,1,1,0.993711,0.962025,1,1,0.993671,0.955975,1,1,1,1,0.955975,0.962264,0.996835]
area_under_roc_curve
0.9904058196003505 [1,0.987421,0.981132,1,1,1,0.993671,0.981013,1,1,1,1,1,1,0.993711,0.841772,1,1,0.981013,0.987342,0.990506,0.927215,0.974684,1,0.993671,0.968553,0.955975,0.990506,1,1,1,0.993711,1,0.955975,1,1,1,1,1,1,0.996835,1,1,1,1,0.996835,0.990506,0.996835,1,1,0.924528,1,1,1,0.987342,1,1,1,0.990506,0.987421,1,1,1,0.996835,0.996835,1,0.987421,0.984177,0.993671,0.987342,0.993711,1,1,1,1,0.987421,1,1,1,1,0.987342,1,0.977848,0.990506,1,1,1,0.962264,1,1,1,1,0.981013,0.91195,0.949686,0.981013,1,1,0.96519,1]
area_under_roc_curve
0.9826913412546775 [1,1,1,0.996835,1,0.981013,1,1,0.993711,1,0.968553,1,0.993671,1,0.981132,1,1,0.974843,0.96519,0.977848,0.993671,1,0.987342,1,1,0.981132,0.993711,1,0.823899,0.996835,1,1,1,1,0.993671,1,0.96519,0.958861,0.996835,1,1,1,1,0.984177,0.974843,0.993671,1,1,0.987421,1,0.987421,0.984177,0.990506,1,0.996835,0.924051,1,1,0.974684,0.955975,1,0.993671,0.987421,0.996835,1,0.918239,0.993711,0.990506,0.898734,0.96519,0.918239,0.998418,0.987342,1,0.977848,1,1,0.993711,1,1,0.977848,0.955975,0.990506,0.984177,0.981013,0.89557,1,0.90566,1,1,0.993711,0.996835,1,0.90566,1,0.917722,0.984177,0.867925,0.89557,0.996835]
area_under_roc_curve
0.979674936310803 [0.974843,0.996835,1,0.996835,0.993671,0.987421,0.968354,0.987421,1,1,0.968553,1,1,1,0.993671,0.993711,1,1,0.96519,0.987421,1,1,0.955975,1,1,0.396226,0.924528,0.990506,1,1,0.996835,1,0.993711,0.987421,0.996835,1,0.996835,0.936709,1,0.981132,1,0.984177,0.993671,0.981013,0.990506,0.993671,1,1,0.981132,1,1,0.968354,0.993671,0.946203,0.974684,0.962264,1,0.974843,1,0.977848,0.996835,1,0.993671,0.977848,1,1,0.971519,1,0.955696,1,1,0.974843,0.981013,0.955696,0.939873,0.962025,1,0.949686,1,0.993671,0.993671,0.481132,0.993711,0.981132,1,1,1,0.952532,0.981132,1,1,1,1,0.974684,0.943396,0.993671,0.968553,0.996835,0.939873,0.987421]
area_under_roc_curve
0.9755672319082874 [0.792453,1,0.955975,1,1,0.981132,1,0.974843,1,1,1,0.993711,0.984177,0.939873,1,0.974843,1,0.968553,0.981013,1,0.990506,0.990506,1,1,1,0.918239,0.987421,0.96519,0.993671,1,1,1,1,0.981132,0.993671,0.993671,0.971519,0.96519,0.984177,1,0.993711,0.996835,0.984177,0.981013,0.996835,0.996835,1,0.977848,1,0.987421,0.943038,0.996835,1,0.977848,1,0.955975,1,0.987421,0.990506,0.993671,1,1,0.484177,0.939873,0.993711,0.993711,0.984177,0.993711,0.974684,0.937107,0.962264,1,0.949367,1,0.914557,0.987342,1,0.974843,1,0.993671,0.987342,0.987421,1,0.484277,0.996835,0.990506,0.996835,0.987342,1,0.993671,1,1,0.984177,0.993671,1,1,0.880503,0.993671,0.974684,1]
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
0.46963418965313125
kappa
0.5264030310206015
kappa
0.5391050430116012
kappa
0.5075563271909402
kappa
0.5514845230574859
kappa
0.526328254519618
kappa
0.5831524099001303
kappa
0.5765356507999211
kappa
0.44431288973083904
kappa
0.4506708760852407
kb_relative_information_score
101.2562392081664
kb_relative_information_score
104.21440744545687
kb_relative_information_score
104.79399456561521
kb_relative_information_score
104.26565872802377
kb_relative_information_score
104.99252161306995
kb_relative_information_score
105.74392544646713
kb_relative_information_score
110.63987822909645
kb_relative_information_score
104.33310083014281
kb_relative_information_score
103.51565992523598
kb_relative_information_score
102.20464194963377
mean_absolute_error
0.013885519174980834
mean_absolute_error
0.01324604879637233
mean_absolute_error
0.013753548585849807
mean_absolute_error
0.01371414124516652
mean_absolute_error
0.013468976000687107
mean_absolute_error
0.013851426348488804
mean_absolute_error
0.013161954854149375
mean_absolute_error
0.013718498482575881
mean_absolute_error
0.013758807837861483
mean_absolute_error
0.013930999723584012
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
0.475
predictive_accuracy
0.53125
predictive_accuracy
0.54375
predictive_accuracy
0.5125
predictive_accuracy
0.55625
predictive_accuracy
0.53125
predictive_accuracy
0.5875
predictive_accuracy
0.58125
predictive_accuracy
0.45
predictive_accuracy
0.45625
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
0.475 [1,0,0.5,1,0,1,1,1,0,1,0,0.5,0.5,0,0.5,0,0,0,0,0,0,0,0,1,0,0,0.5,0.5,0.5,0,0.5,0.5,0.5,0,0.5,0,1,1,1,0.5,1,1,1,0,0.5,1,1,1,1,0.5,0.5,0,0,0,1,1,1,1,0,1,1,1,0,0.5,1,0.5,0.5,1,0,0,0.5,1,0,1,0,1,0.5,0.5,1,0,0,1,0,1,0.5,0,0,1,0.5,0,1,1,0.5,0.5,0.5,0.5,1,0,0,1]
recall
0.53125 [0,1,1,1,1,0,0.5,1,0.5,1,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0,0,1,0,0,1,1,0,0,0,1,1,0.5,1,0.5,0.5,0,0,0,1,0,1,1,1,1,0.5,0.5,1,0,1,0.5,1,1,0.5,1,0,0,0,1,1,1,0,1,0,0.5,0.5,1,0,0,1,0,0,0,1,1,1,0,0.5,0.5,0.5,1,0,0.5,0.5,0,1,0.5,0.5,1,1,1,1,0.5,1,0,0.5,0.5,0,0,0,0,1]
recall
0.54375 [0.5,0.5,1,0,1,0.5,1,0.5,0.5,1,0.5,1,1,0.5,1,1,1,0,0,0,1,0,0,1,1,0,0,1,1,1,1,1,0.5,0.5,1,1,1,0,1,1,0.5,0,1,1,0,1,0.5,1,0.5,0.5,0.5,1,1,0,1,0,1,1,0,0.5,0,1,0.5,1,0.5,0.5,0.5,0.5,1,0,0,1,1,0,0,0,1,0.5,0,0,0,1,0,0,1,0,1,0.5,1,1,1,1,0,0,0.5,1,0,0.5,0,0.5]
recall
0.5125 [0,1,1,1,1,0.5,1,0.5,0.5,1,0.5,0,1,0,1,0.5,1,0.5,0,0,1,1,1,0,0,0,0,1,0.5,1,1,0,1,0.5,1,1,1,0,0,1,1,1,1,1,0.5,0,0,1,1,0,0,0,0,0,1,0.5,1,0,1,0.5,1,0,0.5,1,1,1,0,0,0,0,0,0.5,1,0.5,0,0.5,0.5,0,1,0.5,0,0.5,0,0.5,1,0,1,0.5,0.5,1,1,1,1,0,1,0,0,0.5,0,0.5]
recall
0.55625 [0.5,0,1,0.5,1,0,0,0.5,0,1,0.5,0,0,0,1,1,1,0.5,0,0,1,1,1,1,1,0,0,0,1,0.5,1,0,1,0,1,1,0.5,0,0.5,1,1,1,1,1,1,1,1,0.5,0.5,1,1,0,0.5,0,0.5,0,1,0,1,0,0,1,1,1,0.5,1,0,0,0,0.5,0,0.5,1,1,0.5,0,1,0.5,1,1,0,1,0,0.5,0,0,1,1,1,1,1,0,0,1,0,0,0.5,0,0,1]
recall
0.53125 [0,1,1,1,1,0.5,1,0,1,0.5,0.5,1,0,1,1,1,1,0.5,0,0,1,1,0.5,1,1,0,0,0,1,0.5,0,1,0.5,0.5,1,0.5,0.5,0,0,0,1,1,0,0,0,1,0.5,0,1,0.5,1,0,0.5,1,0.5,0.5,1,1,0.5,1,1,1,0,1,1,1,1,0,0,0,0,0,1,1,0.5,0,0.5,0,0.5,0,0,0.5,0.5,0.5,0,1,1,0,0,1,1,0,0,1,0.5,1,1,0,0,0.5]
recall
0.5875 [1,0,0,0.5,1,0,0.5,0.5,1,1,1,1,0,1,1,0,1,1,0.5,0,0.5,0,0.5,1,0.5,0,0,1,1,1,0.5,0,1,0,1,1,0.5,0.5,0,1,0,1,1,1,0,1,0.5,0.5,1,1,0,0.5,1,0,0.5,0,0.5,0.5,0,0,1,1,1,1,0.5,1,0,0.5,0.5,0,0,1,1,1,0.5,0,1,1,0,1,0.5,1,0.5,0.5,1,1,1,0,1,1,1,1,0,0,0,0,1,1,0,1]
recall
0.58125 [1,1,1,0.5,1,0.5,1,1,0,1,0,1,0.5,0,0,0.5,1,0,0.5,0,0.5,0,0,1,1,0,0,0.5,0,0.5,1,1,1,1,1,1,0,0,0.5,1,1,1,1,0,0,1,1,1,1,1,0,0.5,0.5,1,1,0.5,1,1,0,0,1,1,0,1,1,0,0,0.5,0,0.5,0,1,1,1,0,1,1,0,0,1,0,0,0.5,0,0,0.5,1,0,1,1,0,1,1,0,1,0.5,0,0,0,1]
recall
0.45 [0,1,1,1,0,0,0,1,0.5,1,0,1,1,0,0.5,0,1,1,0,0,1,0,0,0.5,0.5,0,0,0,1,1,1,1,1,0,0.5,1,0.5,0,1,0,1,0.5,0.5,0,0,0.5,1,1,0,1,0.5,0.5,0.5,0.5,0,0,1,0,0,0,0.5,0.5,0,0.5,0,1,0,0,0,1,0,0,0,0,0,0,1,0,1,0.5,0.5,0,0,0,1,1,1,0.5,0,1,1,1,1,0,0,1,0,0,0,0]
recall
0.45625 [0,0,0,0.5,1,0,1,0,1,1,1,1,0.5,0,0.5,0,1,0,0,0,0.5,0.5,0,1,0.5,0,0,0.5,1,1,1,1,1,0,0.5,1,0.5,0,0,1,0,1,0.5,0,0.5,0.5,1,0.5,1,0,0.5,0.5,0,0,0.5,0,1,0,0.5,0.5,1,1,0,0.5,1,0,0,0,0,0,0,1,0,0.5,0,0.5,1,0,1,0,0,0,1,0,1,0.5,0,0,1,0.5,1,1,0,0,1,1,0,0.5,0,1]
relative_absolute_error
0.7012888472212531
relative_absolute_error
0.6689923634531469
relative_absolute_error
0.6946236659520093
relative_absolute_error
0.6926333962205301
relative_absolute_error
0.6802513131660145
relative_absolute_error
0.6995669872974132
relative_absolute_error
0.6647451946540076
relative_absolute_error
0.6928534587159524
relative_absolute_error
0.6948892847404777
relative_absolute_error
0.7035858446254539
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
0.08169330877383292
root_mean_squared_error
0.07869366082968351
root_mean_squared_error
0.07919489931410018
root_mean_squared_error
0.08020575797263828
root_mean_squared_error
0.07915394118643201
root_mean_squared_error
0.0800033409513874
root_mean_squared_error
0.07690002562949678
root_mean_squared_error
0.07919279738052111
root_mean_squared_error
0.0812288397042899
root_mean_squared_error
0.08200501495304983
root_relative_squared_error
0.8210486457134921
root_relative_squared_error
0.7909010495501451
root_relative_squared_error
0.7959386858631647
root_relative_squared_error
0.8060981976402946
root_relative_squared_error
0.7955270411916774
root_relative_squared_error
0.8040638300322019
root_relative_squared_error
0.7728743375204682
root_relative_squared_error
0.7959175606358434
root_relative_squared_error
0.8163805559244021
root_relative_squared_error
0.8241814106871217
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
4021.949687000415
usercpu_time_millis
3718.8226270000087
usercpu_time_millis
3892.6042540001617
usercpu_time_millis
3722.722861999955
usercpu_time_millis
3838.233795999713
usercpu_time_millis
3748.846154000148
usercpu_time_millis
3774.725935999868
usercpu_time_millis
3745.637686000009
usercpu_time_millis
3704.117042999769
usercpu_time_millis
3715.4775540002447
usercpu_time_millis_testing
38.603335000061634
usercpu_time_millis_testing
34.71394300004249
usercpu_time_millis_testing
34.7709229999964
usercpu_time_millis_testing
34.54128399971523
usercpu_time_millis_testing
34.880089000125736
usercpu_time_millis_testing
34.512037000240525
usercpu_time_millis_testing
34.56379499994
usercpu_time_millis_testing
34.72156499992707
usercpu_time_millis_testing
34.535879000031855
usercpu_time_millis_testing
34.52336100008324
usercpu_time_millis_training
3983.3463520003534
usercpu_time_millis_training
3684.108683999966
usercpu_time_millis_training
3857.8333310001653
usercpu_time_millis_training
3688.18157800024
usercpu_time_millis_training
3803.3537069995873
usercpu_time_millis_training
3714.3341169999076
usercpu_time_millis_training
3740.162140999928
usercpu_time_millis_training
3710.916121000082
usercpu_time_millis_training
3669.5811639997373
usercpu_time_millis_training
3680.9541930001615