10110655
1
Jan van Rijn
9954
Supervised Classification
8815
sklearn.pipeline.Pipeline(columntransformer=sklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,standardscaler=sklearn.preprocessing.data.StandardScaler),nominal=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)),variancethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,decisiontreeclassifier=sklearn.tree.tree.DecisionTreeClassifier)(1)
8035922
axis
0
8778
copy
true
8778
missing_values
"NaN"
8778
strategy
"mean"
8778
verbose
0
8778
copy
true
8779
with_mean
true
8779
with_std
true
8779
memory
null
8780
copy
true
8781
fill_value
-1
8781
missing_values
NaN
8781
strategy
"constant"
8781
verbose
0
8781
categorical_features
null
8782
categories
null
8782
dtype
{"oml-python:serialized_object": "type", "value": "np.float64"}
8782
handle_unknown
"ignore"
8782
n_values
null
8782
sparse
true
8782
class_weight
null
8783
criterion
"entropy"
8783
max_depth
null
8783
max_features
1.0
8783
max_leaf_nodes
null
8783
min_impurity_decrease
0.0
8783
min_impurity_split
null
8783
min_samples_leaf
4
8783
min_samples_split
6
8783
min_weight_fraction_leaf
0.0
8783
presort
false
8783
random_state
63883
8783
splitter
"best"
8783
n_jobs
null
8812
remainder
"passthrough"
8812
sparse_threshold
0.3
8812
transformer_weights
null
8812
memory
null
8813
memory
null
8815
threshold
0.0
8816
openml-python
Sklearn_0.20.0.
1491
one-hundred-plants-margin
https://www.openml.org/data/download/1592283/phpCsX3fx
-1
21141848
description
https://api.openml.org/data/download/21141848/description.xml
-1
21141849
predictions
https://api.openml.org/data/download/21141849/predictions.arff
area_under_roc_curve
0.7839188762626261 [0.743549,0.871508,0.874487,0.81104,0.903922,0.746922,0.746212,0.808396,0.777758,0.841935,0.8721,0.777107,0.808081,0.71224,0.872396,0.709734,0.905125,0.648299,0.710938,0.708787,0.777206,0.839844,0.777403,0.999961,0.777521,0.611644,0.679569,0.77762,0.842113,0.873047,0.84083,0.90479,0.777068,0.614978,0.871035,0.871113,0.740609,0.680339,0.904356,0.935389,0.776199,0.808337,0.873974,0.777462,0.809679,0.71297,0.935152,0.715002,0.71149,0.841126,0.838048,0.680319,0.839646,0.736072,0.714015,0.580749,0.968079,0.903212,0.742543,0.741339,0.748086,0.773635,0.746252,0.620995,0.810271,0.777107,0.615215,0.935665,0.582071,0.585878,0.677498,0.902857,0.712989,0.871745,0.578697,0.935054,0.841619,0.610953,0.842902,0.84087,0.83941,0.64968,0.71222,0.775075,0.774207,0.810646,0.900588,0.774384,0.680319,0.745936,0.935054,0.93604,0.838463,0.740037,0.841974,0.841422,0.775055,0.774069,0.670632,0.713936]
average_cost
0
f_measure
0.46890828226856845 [0.410256,0.594595,0.8,0.62069,0.666667,0.516129,0.387097,0.666667,0.5,0.666667,0.545455,0.5,0.451613,0.30303,0.666667,0.258065,0.764706,0.235294,0.352941,0.292683,0.285714,0.625,0.545455,0.969697,0.4,0.121212,0.266667,0.529412,0.592593,0.666667,0.540541,0.787879,0.533333,0.137931,0.594595,0.62069,0.363636,0.222222,0.666667,0.709677,0.484848,0.45,0.709677,0.4,0.666667,0.388889,0.645161,0.424242,0.3125,0.571429,0.428571,0.363636,0.551724,0.142857,0.333333,0.15,0.909091,0.628571,0.242424,0.285714,0.551724,0.342857,0.4375,0.190476,0.555556,0.470588,0.133333,0.764706,0.222222,0.214286,0.322581,0.545455,0.4,0.533333,0.142857,0.714286,0.625,0.129032,0.608696,0.529412,0.6,0.258065,0.344828,0.333333,0.421053,0.64,0.514286,0.375,0.357143,0.4,0.666667,0.75,0.533333,0.25,0.666667,0.6,0.388889,0.342857,0.066667,0.48]
kappa
0.46464646464646464
kb_relative_information_score
845.2647513642554
mean_absolute_error
0.011153571428571334
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
0.48197446263298344 [0.347826,0.52381,0.857143,0.692308,0.565217,0.533333,0.4,0.818182,0.583333,0.647059,0.529412,0.5,0.466667,0.294118,0.647059,0.266667,0.722222,0.222222,0.333333,0.24,0.333333,0.625,0.529412,0.941176,0.428571,0.117647,0.285714,0.5,0.727273,0.6,0.47619,0.764706,0.571429,0.153846,0.52381,0.692308,0.352941,0.272727,0.6,0.733333,0.470588,0.375,0.733333,0.368421,0.714286,0.35,0.666667,0.411765,0.3125,0.666667,0.346154,0.352941,0.615385,0.166667,0.357143,0.125,0.882353,0.578947,0.235294,0.263158,0.615385,0.315789,0.4375,0.4,0.5,0.444444,0.142857,0.722222,0.272727,0.25,0.333333,0.529412,0.428571,0.571429,0.166667,0.833333,0.625,0.133333,1,0.5,0.642857,0.266667,0.384615,0.3,0.363636,0.888889,0.473684,0.375,0.416667,0.368421,0.647059,0.75,0.571429,0.25,0.818182,0.642857,0.35,0.315789,0.071429,0.666667]
predictive_accuracy
0.47
prior_entropy
6.6438561897747395
recall
0.47 [0.5,0.6875,0.75,0.5625,0.8125,0.5,0.375,0.5625,0.4375,0.6875,0.5625,0.5,0.4375,0.3125,0.6875,0.25,0.8125,0.25,0.375,0.375,0.25,0.625,0.5625,1,0.375,0.125,0.25,0.5625,0.5,0.75,0.625,0.8125,0.5,0.125,0.6875,0.5625,0.375,0.1875,0.75,0.6875,0.5,0.5625,0.6875,0.4375,0.625,0.4375,0.625,0.4375,0.3125,0.5,0.5625,0.375,0.5,0.125,0.3125,0.1875,0.9375,0.6875,0.25,0.3125,0.5,0.375,0.4375,0.125,0.625,0.5,0.125,0.8125,0.1875,0.1875,0.3125,0.5625,0.375,0.5,0.125,0.625,0.625,0.125,0.4375,0.5625,0.5625,0.25,0.3125,0.375,0.5,0.5,0.5625,0.375,0.3125,0.4375,0.6875,0.75,0.5,0.25,0.5625,0.5625,0.4375,0.375,0.0625,0.375]
relative_absolute_error
0.5633116883116824
root_mean_prior_squared_error
0.09949874371066209
root_mean_squared_error
0.09174488777641261
root_relative_squared_error
0.9220708157200724
total_cost
0
area_under_roc_curve
0.7737615436669054 [1,0.990506,1,0.496855,1,0.996855,0.746835,1,0.75,1,0.995253,0.748418,0.742089,0.75,1,0.474843,1,0.496835,0.490506,0.490566,0.993711,0.490566,0.487421,1,0.496855,0.493671,0.746835,0.745253,0.75,0.5,0.996835,1,0.746835,0.490506,1,0.487421,1,0.490566,1,1,0.493711,0.5,1,1,1,0.746835,1,1,0.490506,0.748418,0.75,0.493671,0.993711,0.738924,0.996855,0.487421,0.746835,0.996855,1,0.735759,0.496855,0.996855,0.75,0.496835,1,0.748418,0.5,1,0.490566,0.493711,0.740506,1,0.746835,0.742089,0.477987,1,0.75,0.742089,0.746835,0.748418,1,0.496835,0.484277,1,0.745253,0.748418,0.993671,0.743671,0.742089,0.496855,0.735759,1,0.996835,0.988924,1,0.490506,0.996855,0.490506,0.481013,1]
area_under_roc_curve
0.7603125497571848 [1,1,0.75,1,1,1,0.496835,1,0.748418,1,0.75,0.743671,0.493671,0.746835,1,0.996855,1,0.490506,0.487342,0.993711,1,0.493711,0.996855,1,1,0.732595,0.487342,0.496835,1,1,0.743671,1,0.745253,0.742089,0.745253,1,0.484277,0.496855,1,1,0.493711,0.490566,1,0.748418,0.745253,0.740506,0.996855,0.987421,0.493671,1,0.484177,0.477848,0.996855,0.988924,1,0.490566,1,0.490566,0.493711,0.490506,1,0.993711,0.995253,0.496835,1,0.735759,0.490506,0.987421,0.484277,0.496855,0.738924,1,0.746835,1,0.474843,1,0.746835,0.477848,1,0.75,0.746835,0.496835,0.481132,0.490566,0.743671,0.748418,0.738924,0.481013,0.746835,0.490566,0.746835,1,1,0.496835,0.745253,1,1,0.496835,0.738924,0.496855]
area_under_roc_curve
0.7663051807180957 [0.496835,0.746835,0.742089,1,0.746835,0.487342,0.496855,1,0.988924,0.745253,0.745253,0.75,1,0.746835,0.5,0.487342,0.996835,0.477848,0.487421,0.490506,0.5,1,0.481013,1,0.493711,0.996835,0.75,1,1,0.996835,1,0.993671,1,0.484177,0.496855,0.996855,0.981132,0.493711,1,1,0.496835,1,1,0.996855,0.493671,0.481132,0.746835,0.993711,0.743671,0.75,0.993671,0.996855,0.493711,0.484177,0.496855,0.742089,1,0.993671,0.990566,0.484177,0.496855,0.496855,0.748418,0.996855,0.746835,0.745253,0.5,1,0.493711,0.5,0.735759,0.990506,0.484277,0.746835,0.490566,1,0.996835,0.487342,0.75,1,0.490566,0.743671,0.987342,0.996835,0.484277,0.496855,1,0.996835,0.75,0.996855,0.992089,0.996855,0.490566,0.740506,1,1,0.487342,0.982595,0.493711,0.746835]
area_under_roc_curve
0.7919582437704002 [0.743671,0.996835,1,1,0.748418,0.5,0.996855,0.490506,0.75,0.75,0.75,0.992089,0.496855,0.75,0.998418,0.995253,0.746835,0.738924,0.490566,0.490506,0.987421,1,0.75,1,0.496855,0.487342,0.743671,1,1,0.746835,1,1,0.746835,0.490506,0.996855,0.496855,0.996855,1,0.996855,1,0.746835,0.990566,1,0.993711,1,1,0.988924,0.996855,0.993671,0.988924,1,1,0.977987,0.493671,1,0.740506,1,1,1,0.746835,0.5,0.996855,0.737342,0.5,0.746835,0.993671,0.742089,1,0.484277,0.745253,0.496835,0.487342,0.493711,0.996835,0.481132,0.748418,0.75,0.484177,1,0.748418,0.496855,0.493671,1,0.742089,0.981132,0.5,1,0.996835,0.481013,0.990566,1,0.496855,0.484277,0.490506,1,0.5,0.493671,0.996835,0.974843,0.481013]
area_under_roc_curve
0.7510962751771356 [0.745253,0.996855,0.75,1,0.493711,0.75,0.493711,0.493671,0.5,0.746835,0.996835,0.745253,1,0.481132,0.990566,0.5,0.75,0.746835,1,0.993671,0.493671,0.743671,1,1,0.748418,0.490506,0.727848,1,1,0.745253,0.496855,0.493711,0.493671,0.493671,0.987421,1,0.734177,0.496835,0.745253,0.990506,1,0.75,0.5,1,0.996855,0.487421,0.998418,0.5,0.75,1,0.987421,0.490566,1,0.990566,0.496835,0.468354,0.996855,0.742089,0.742089,0.493711,0.748418,0.746835,1,0.5,0.748418,0.493671,0.490566,0.998418,0.490506,0.474684,0.743671,0.996835,1,0.5,0.737342,1,0.746835,0.484177,0.5,0.990566,0.487421,0.996835,0.493671,0.737342,0.496855,0.996855,0.496855,1,1,0.748418,0.996855,1,0.981132,0.987421,0.75,1,0.742089,0.996855,0.487421,0.496835]
area_under_roc_curve
0.7753643469867046 [0.743671,1,1,1,0.993711,0.748418,0.996855,0.746835,1,0.746835,0.992089,0.742089,0.990566,0.990566,1,0.75,1,0.735759,0.487421,0.493671,0.75,0.743671,0.75,1,0.731013,0.735759,0.742089,1,1,1,1,1,0.737342,0.490506,0.496855,0.996835,0.493671,0.738924,0.993671,1,0.998418,0.746835,1,1,0.493711,0.993711,1,0.5,0.477848,0.746835,0.993711,0.987421,0.734177,0.981132,0.740506,0.487342,1,1,0.987342,0.984277,0.746835,0.490506,0.496855,1,0.746835,0.75,0.490566,1,0.481013,0.746835,0.484177,0.988924,0.484277,1,0.493671,0.987421,0.746835,0.735759,0.996835,0.493711,0.993711,0.490506,0.748418,0.490506,0.496855,1,1,0.5,0.493671,0.493671,1,1,0.496855,0.481132,0.746835,0.996855,0.743671,0.490566,0.490566,0.746835]
area_under_roc_curve
0.7979126860918717 [0.742089,0.493711,1,0.496835,1,0.996835,1,1,0.987421,0.745253,1,1,0.743671,0.481132,0.496855,0.748418,0.5,0.493711,0.484177,0.984177,0.743671,0.996835,1,1,0.742089,0.490566,0.487421,0.745253,0.496855,1,1,0.496855,1,0.493711,1,0.75,0.990506,0.748418,0.745253,0.493711,0.746835,1,0.745253,0.743671,0.987421,0.746835,0.746835,0.75,1,1,0.996855,0.745253,0.75,0.968553,0.496835,0.737342,1,0.745253,0.743671,0.977987,1,0.724684,1,0.496835,0.745253,0.996855,0.496855,0.996835,0.738924,0.484177,0.993711,1,0.740506,1,0.481013,1,1,0.996855,1,0.996855,0.745253,0.996855,0.748418,0.996835,1,0.743671,0.743671,0.484277,0.487421,0.5,1,0.996835,0.743671,0.481132,0.496855,0.746835,1,0.496855,0.732595,0.992089]
area_under_roc_curve
0.7822109356341056 [1,0.990566,1,0.490506,0.996855,0.5,0.996835,1,0.5,0.998418,1,0.496855,0.745253,0.496855,0.496855,0.481013,1,0.490566,0.993671,0.493671,0.743671,0.748418,0.75,1,0.987342,0.477987,0.477987,0.75,1,0.746835,0.748418,1,1,1,0.746835,1,0.740506,0.743671,0.746835,0.996855,1,0.740506,1,0.5,1,0.745253,1,1,0.977987,0.496855,0.984277,0.490506,0.493671,1,0.748418,0.481013,1,0.998418,0.740506,1,0.5,0.748418,0.996855,0.746835,0.75,0.990566,0.474843,0.75,0.490506,0.490506,0.487421,0.75,0.998418,0.481132,0.742089,1,1,0.943396,1,0.490566,0.995253,0.487421,0.493671,0.75,0.481013,0.745253,0.996835,0.493711,1,0.746835,1,0.996835,0.746835,0.993711,0.496855,0.996835,0.992089,0.990566,0.726266,0.748418]
area_under_roc_curve
0.8203205855425519 [0.487421,1,1,1,0.996835,0.996855,0.490506,0.977987,0.745253,1,0.496855,1,0.996835,0.748418,0.996835,0.981132,0.996855,0.987421,1,1,0.748418,0.990506,0.996855,1,0.75,0.484277,0.493711,0.746835,0.746835,1,1,1,0.487421,0.993711,0.993671,1,0.745253,0.743671,1,0.5,0.496855,0.748418,0.75,0.493671,0.5,0.496835,1,0.487342,0.496855,1,0.746835,0.742089,1,0.732595,0.746835,0.493711,1,0.993711,0.496835,0.742089,0.745253,0.998418,0.487342,0.496835,1,1,0.996835,0.5,0.735759,0.996855,1,0.990566,0.743671,1,0.481013,0.737342,0.996855,0.493711,1,1,1,0.996855,0.496855,0.990566,1,1,0.971519,0.743671,0.493711,0.996835,1,0.75,1,0.742089,0.993711,0.745253,0.487421,0.995253,0.737342,0.996855]
area_under_roc_curve
0.820479932927315 [0.487421,0.496835,0.5,0.746835,1,0.996855,0.743671,0.493711,0.740506,1,1,0.496855,1,0.75,0.996835,1,1,1,1,1,0.996835,0.996835,0.496855,1,1,0.474843,0.987421,0.745253,0.490506,0.990566,0.5,0.75,1,0.968553,0.995253,0.740506,0.490506,0.740506,1,1,0.981132,0.990506,0.748418,0.746835,1,0.748418,1,0.490506,0.996855,0.496855,0.748418,0.745253,0.996835,0.487342,0.748418,0.490566,1,1,0.5,1,1,0.742089,0.493671,0.75,0.996855,0.5,0.732595,0.996855,0.740506,0.487421,0.481132,0.996855,0.496835,0.998418,0.734177,0.998418,1,0.490566,0.496855,0.998418,0.992089,0.490566,1,0.493711,0.998418,1,0.998418,0.990506,0.481132,0.995253,1,0.998418,1,1,1,1,1,0.743671,0.731013,0.496855]
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
0.4759273875295975
kappa
0.4191002367797948
kappa
0.4442032132001737
kappa
0.4759687475337385
kappa
0.4378429592199281
kappa
0.4251421351863551
kappa
0.4820371101460718
kappa
0.46961325966850825
kappa
0.513677811550152
kappa
0.5011248371946165
kb_relative_information_score
82.62365876536992
kb_relative_information_score
78.75628507602167
kb_relative_information_score
79.57868644772671
kb_relative_information_score
87.00126061527837
kb_relative_information_score
75.9612370215662
kb_relative_information_score
80.06428941032726
kb_relative_information_score
87.75459977923016
kb_relative_information_score
83.81308701773129
kb_relative_information_score
94.65470535967786
kb_relative_information_score
95.05694187133095
mean_absolute_error
0.011060714285714288
mean_absolute_error
0.011550595238095243
mean_absolute_error
0.01157291666666667
mean_absolute_error
0.010910714285714286
mean_absolute_error
0.011833630952380955
mean_absolute_error
0.012098511904761907
mean_absolute_error
0.010983035714285716
mean_absolute_error
0.011307142857142861
mean_absolute_error
0.010117559523809525
mean_absolute_error
0.01010089285714286
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
0.48125
predictive_accuracy
0.425
predictive_accuracy
0.45
predictive_accuracy
0.48125
predictive_accuracy
0.44375
predictive_accuracy
0.43125
predictive_accuracy
0.4875
predictive_accuracy
0.475
predictive_accuracy
0.51875
predictive_accuracy
0.50625
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
0.48125 [1,0.5,1,0,1,1,0,1,0.5,1,0.5,0.5,0,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0.5,0.5,0,1,1,0.5,0,1,0,0,0,1,1,0,0,1,1,1,0.5,1,1,0,0.5,0.5,0,1,0.5,1,0,0.5,1,1,0.5,0,1,0.5,0,1,0.5,0,1,0,0,0,1,0.5,0.5,0,1,0.5,0.5,0.5,0.5,1,0,0,1,0.5,0.5,1,0.5,0.5,0,0.5,1,1,0,0.5,0,1,0,0,1]
recall
0.425 [1,1,0.5,1,1,1,0,1,0.5,1,0,0.5,0,0.5,1,1,1,0,0,1,1,0,1,1,1,0,0,0,0.5,1,0.5,1,0.5,0.5,0.5,1,0,0,1,0.5,0,0,1,0.5,0.5,0.5,1,1,0,1,0,0,1,0,1,0,1,0,0,0,1,1,0.5,0,1,0,0,0,0,0,0.5,1,0.5,0.5,0,1,0,0,0,0.5,0.5,0,0,0,0.5,0,0.5,0,0,0,0.5,1,1,0,0.5,0.5,1,0,0,0]
recall
0.45 [0,0.5,0.5,1,0.5,0,0,1,1,0.5,0.5,0.5,1,0.5,0,0,1,0,0,0,0,1,0,1,0,0.5,0.5,1,0.5,1,1,1,1,0,0,1,1,0,1,1,0,1,1,1,0,0,0.5,1,0.5,0.5,1,1,0,0,0,0.5,1,0.5,0,0,0,0,0.5,0,0.5,0.5,0,1,0,0,0.5,1,0,0.5,0,0,1,0,0,1,0,0,0,1,0,0,1,1,0.5,1,0.5,1,0,0,0.5,1,0,0.5,0,0.5]
recall
0.48125 [0.5,1,1,1,0.5,0,1,0,0,0.5,0.5,0.5,0,0,1,0.5,0.5,0.5,0,0,0,1,0.5,1,0,0,0.5,1,0.5,0.5,1,1,0.5,0,1,0,1,0,1,1,0.5,1,1,0,1,1,0.5,1,1,0.5,1,1,0,0,1,0.5,1,1,1,0.5,0,0,0.5,0,0.5,1,0.5,1,0,0.5,0,0,0,0.5,0,0.5,0.5,0,1,0.5,0,0,1,0,1,0,1,0,0,1,0.5,0,0,0,1,0,0,1,0,0]
recall
0.44375 [0.5,1,0.5,1,0,0.5,0,0,0,0.5,1,0.5,1,0,0,0,0.5,0.5,1,1,0,0.5,1,1,0.5,0,0,1,1,0.5,0,0,0,0,1,1,0.5,0,0.5,1,1,0.5,0,1,1,0,0.5,0,0.5,0.5,0,0,0.5,0,0,0,1,0.5,0.5,0,0.5,0.5,1,0,0.5,0,0,1,0,0,0.5,0.5,1,0,0.5,1,0.5,0,0,0,0,1,0,0,0,1,0,1,1,0.5,1,1,0,1,0.5,1,0.5,1,0,0]
recall
0.43125 [0.5,1,1,1,1,0.5,1,0.5,1,0.5,1,0.5,0,1,1,0.5,1,0.5,0,0,0,0.5,0.5,1,0,0.5,0.5,1,1,1,1,1,0.5,0,0,0,0,0.5,0.5,0,1,0.5,1,1,0,1,1,0,0,0.5,1,1,0,0,0,0,1,1,0,0,0.5,0,0,0,0.5,0.5,0,1,0,0.5,0,0.5,0,1,0,0,0.5,0,0.5,0,1,0,0.5,0,0,1,0,0,0,0,1,1,0,0,0.5,0,0.5,0,0,0.5]
recall
0.4875 [0.5,0,1,0,1,1,1,1,0,0.5,1,1,0.5,0,0,0,0,0,0,0.5,0.5,1,1,1,0,0,0,0.5,0,1,1,0,1,0,1,0.5,1,0.5,0.5,0,0.5,1,0.5,0,1,0.5,0,0.5,0,0,1,0.5,0.5,0,0,0.5,1,0.5,0,0,1,0,1,0,0.5,1,0,1,0.5,0,1,1,0,0,0,1,1,1,1,1,0.5,1,0.5,0.5,1,0,0,0,0,0,1,1,0.5,0,0,0.5,0.5,0,0.5,0.5]
recall
0.475 [1,1,1,0,1,0,1,1,0,1,0,0,0,0,0,0,1,0,1,0,0,0.5,0.5,1,0.5,0,0,0.5,1,0.5,0,1,1,1,0.5,1,0,0,0.5,1,1,0.5,1,0,1,0.5,1,1,0,0,1,0,0,1,0.5,0,1,1,0.5,1,0,0.5,1,0.5,0.5,1,0,0.5,0,0,0,0.5,1,0,0.5,1,1,0,1,0,0.5,0,0,0.5,0,0.5,1,0,1,0.5,0,1,0,0,0,1,0.5,0,0,0.5]
recall
0.51875 [0,1,1,1,1,1,0,0,0.5,1,0,1,1,0.5,1,0,1,0,1,1,0.5,0.5,1,1,0.5,0,0,0.5,0.5,1,1,1,0,0,1,1,0.5,0,1,0,0,0.5,0,0,0,0,1,0,0,1,0,0.5,1,0,0,0,1,0,0,0,0.5,1,0,0,1,1,0,0,0.5,1,1,0,0.5,1,0,0,1,0,1,0.5,1,1,0,1,0.5,1,1,0.5,0,1,1,0,0.5,0.5,1,0.5,0,1,0,1]
recall
0.50625 [0,0,0,0,1,1,0,0,0.5,1,1,0,1,0.5,1,1,1,1,0.5,1,0.5,1,0,1,1,0,1,0.5,0,1,0,0.5,0,0,0.5,0,0,0.5,1,1,0,0.5,0.5,0.5,1,0.5,0,0,1,0,0.5,0.5,1,0,0.5,0,1,1,0,1,1,0,0,0.5,1,0,0.5,1,0.5,0,0,0,0,0.5,0,1,1,0,0,1,0.5,0,1,0,1,1,0,0.5,0,0.5,1,0.5,1,1,1,1,1,0,0,0]
relative_absolute_error
0.5586219336219328
relative_absolute_error
0.5833633958633951
relative_absolute_error
0.58449074074074
relative_absolute_error
0.5510461760461751
relative_absolute_error
0.5976581289081281
relative_absolute_error
0.6110359547859538
relative_absolute_error
0.5546987734487726
relative_absolute_error
0.5710678210678203
relative_absolute_error
0.510987854737854
relative_absolute_error
0.5101461038961032
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
0.09334422008906755
root_mean_squared_error
0.09361147361940884
root_mean_squared_error
0.09425974043991665
root_mean_squared_error
0.0905353111978754
root_mean_squared_error
0.09565304692213171
root_mean_squared_error
0.09503995012720391
root_mean_squared_error
0.09083389502416359
root_mean_squared_error
0.0916343403111685
root_mean_squared_error
0.08620757525731733
root_mean_squared_error
0.08574356725374115
root_relative_squared_error
0.9381447102539144
root_relative_squared_error
0.9408307092964598
root_relative_squared_error
0.9473460359863418
root_relative_squared_error
0.9099141137012552
root_relative_squared_error
0.961349293015061
root_relative_squared_error
0.9551874383818943
root_relative_squared_error
0.9129149940656993
root_relative_squared_error
0.9209597718905589
root_relative_squared_error
0.8664187309540826
root_relative_squared_error
0.8617552750523125
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
209.9241460000485
usercpu_time_millis
198.32761799989385
usercpu_time_millis
164.70149300039338
usercpu_time_millis
141.02483700116863
usercpu_time_millis
140.77541200094856
usercpu_time_millis
150.5330829986633
usercpu_time_millis
145.4488979979942
usercpu_time_millis
145.59673000076145
usercpu_time_millis
142.0644949994312
usercpu_time_millis
140.76629200098978
usercpu_time_millis_testing
1.7350540001643822
usercpu_time_millis_testing
1.73444699976244
usercpu_time_millis_testing
1.2998000001971377
usercpu_time_millis_testing
1.2501000001066132
usercpu_time_millis_testing
1.2474129998736316
usercpu_time_millis_testing
1.4082489997235825
usercpu_time_millis_testing
1.2454489988158457
usercpu_time_millis_testing
1.2659800013352651
usercpu_time_millis_testing
1.260839999304153
usercpu_time_millis_testing
1.253082000403083
usercpu_time_millis_training
208.1890919998841
usercpu_time_millis_training
196.5931710001314
usercpu_time_millis_training
163.40169300019625
usercpu_time_millis_training
139.77473700106202
usercpu_time_millis_training
139.52799900107493
usercpu_time_millis_training
149.12483399893972
usercpu_time_millis_training
144.20344899917836
usercpu_time_millis_training
144.3307499994262
usercpu_time_millis_training
140.80365500012704
usercpu_time_millis_training
139.5132100005867