10090038
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)
8015126
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
"gini"
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
20
8783
min_samples_split
13
8783
min_weight_fraction_leaf
0.0
8783
presort
false
8783
random_state
58729
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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
21100613
description
https://api.openml.org/data/download/21100613/description.xml
-1
21100614
predictions
https://api.openml.org/data/download/21100614/predictions.arff
area_under_roc_curve
0.8765133759469692 [0.77906,0.882457,0.929569,0.899582,0.894393,0.824909,0.887133,0.977687,0.892184,0.997633,0.82704,0.927004,0.886285,0.817294,0.958235,0.73114,0.964725,0.844263,0.90915,0.868134,0.988518,0.878117,0.9084,0.961095,0.883306,0.805003,0.865195,0.844894,0.927577,0.987788,0.895577,0.895537,0.85468,0.823094,0.91933,0.893604,0.890664,0.866596,0.887212,0.958748,0.862729,0.782098,0.959872,0.846828,0.917988,0.88808,0.833491,0.958905,0.950067,0.895478,0.936592,0.888139,0.892775,0.783854,0.922506,0.873935,0.994772,0.891848,0.920573,0.752071,0.960799,0.799282,0.925623,0.819247,0.893466,0.890743,0.781664,0.954171,0.695964,0.804017,0.796776,0.93093,0.81319,0.822522,0.816465,0.877249,0.926472,0.76381,0.900055,0.885535,0.799045,0.924164,0.718553,0.961983,0.918699,0.953756,0.953125,0.859691,0.917278,0.831992,0.862689,0.929253,0.763672,0.7965,0.854798,0.793363,0.786932,0.921165,0.767578,0.893703]
average_cost
0
kappa
0.32323232323232326
kb_relative_information_score
840.2221075197842
mean_absolute_error
0.01534429492829332
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]
predictive_accuracy
0.33
prior_entropy
6.6438561897747395
recall
0.33 [0.0625,0.25,0.8125,0.6875,0.625,0.1875,0.375,0.25,0.3125,0.875,0.5,0.6875,0.375,0.0625,0.1875,0.4375,0.875,0.1875,0.125,0.1875,0.6875,0.375,0.3125,0.5,0.375,0,0.125,0.0625,0.6875,0.5,0.5625,0.5625,0.25,0.3125,0.375,0.25,0.4375,0.125,0.1875,0.5625,0.6875,0.3125,0.6875,0.1875,0,0.5,0.3125,0.4375,0.3125,0.5,0.375,0.25,0.4375,0.25,0.375,0.125,0.5,0.3125,0,0.25,0.6875,0.5,0.4375,0.25,0.375,0.375,0.0625,0.0625,0.125,0.125,0,0.1875,0.1875,0.1875,0.0625,0,0.375,0,0.8125,0,0,0.5625,0.1875,0.875,0.375,0.4375,0.5,0.375,0.3125,0.5,0.5,0.3125,0,0,0.1875,0.4375,0.0625,0.0625,0,0.375]
relative_absolute_error
0.774964390317843
root_mean_prior_squared_error
0.09949874371066209
root_mean_squared_error
0.0912995245043117
root_relative_squared_error
0.9175947464201824
total_cost
0
area_under_roc_curve
0.8653458621925006 [0.987421,0.727848,0.996835,1,0.726266,0.990566,0.996835,0.987421,0.477848,0.993711,0.484177,0.746835,0.731013,0.724684,0.974684,0.959119,0.992089,0.702532,0.713608,0.959119,1,0.921384,0.943396,0.996855,0.971698,0.985759,0.71519,0.982595,0.987342,0.974843,0.718354,0.737342,0.724684,0.710443,0.988924,0.487421,0.996855,0.95283,0.987421,0.996835,1,0.996855,0.990506,0.691456,0.990506,0.987342,0.987421,0.993711,0.996835,0.72943,0.920886,0.992089,0.962264,0.707278,0.984277,0.993711,0.988924,0.996855,0.474843,0.408228,0.996855,0.449686,0.981013,0.977848,0.990566,0.984177,1,0.924528,0.946541,0.987421,0.471519,1,0.474684,0.990506,0.858491,0.96519,0.977848,0.718354,0.993671,0.993671,0.990506,0.993671,0.943396,0.996855,0.955696,0.960443,0.993671,0.996835,0.735759,0.484277,0.734177,0.993711,0.984177,0.719937,0.990506,0.726266,0.990566,0.968354,0.474684,0.993711]
area_under_roc_curve
0.87875181613725 [0.959119,0.96519,0.987342,1,1,0.937107,0.960443,0.990566,0.993671,1,0.97943,0.977848,0.988924,0.705696,0.987342,0.993711,0.743671,0.72943,0.981013,0.462264,0.990566,0.996855,0.971698,0.993711,0.996855,0.734177,0.963608,0.471519,0.996835,0.965409,0.992089,0.952532,0.990506,0.734177,0.962025,0.487421,0.977987,0.993711,0.959119,0.993671,0.990566,0.987421,0.993671,0.734177,0.993671,0.723101,0.990566,0.984277,0.982595,0.996835,0.993671,0.72943,0.984277,0.966772,0.955975,0.971698,0.996835,0.959119,0.993711,0.446203,0.996855,0.477987,0.990506,0.731013,0.996855,0.737342,0.719937,0.990566,0.41195,0.433962,0.960443,1,0.993671,0.984177,0.430818,0.988924,0.746835,0.458861,1,0.958861,0.414557,0.974684,0.962264,0.993711,0.947785,1,0.949367,0.990506,0.993671,0.987421,0.993671,0.996855,0.446203,0.458861,0.984177,1,0.487421,0.735759,0.96519,0.993711]
area_under_roc_curve
0.8762190510309686 [0.949367,0.958861,1,0.990566,0.732595,0.72943,0.974843,0.955696,0.981013,0.996835,0.993671,0.966772,0.984277,0.72943,0.993671,1,0.996835,0.984177,0.990566,0.96519,0.962264,0.455975,0.993671,0.996855,0.990566,0.981013,0.93038,0.943396,0.732595,1,0.996855,1,0.963608,0.72943,0.990566,0.484277,0.996855,0.95283,1,0.72943,0.743671,0.977987,0.990566,0.990566,0.977848,0.462264,0.746835,1,0.737342,0.990506,0.993671,0.981132,0.987421,0.993671,0.984277,0.985759,0.996855,0.996835,0.968553,0.981013,0.462264,0.987421,0.990506,0.45283,0.723101,0.731013,0.712025,0.958861,0.399371,0.716772,0.689873,0.990506,0.993711,0.94462,0.996855,0.719937,0.726266,0.669304,0.496835,0.726266,0.946541,1,0.46519,1,0.996855,0.993711,0.990566,0.474684,0.987342,0.996855,0.993671,0.987421,0.455975,0.962025,0.988924,0.984277,0.727848,0.981013,0.987421,0.738924]
area_under_roc_curve
0.8791477589363902 [0.996835,0.981013,0.990506,0.446541,0.988924,0.723101,0.987421,1,0.974684,0.993671,0.731013,1,0.481132,0.710443,0.990506,0.732595,1,0.721519,0.45283,0.707278,1,0.990566,0.963608,0.959119,0.477987,0.656646,0.993671,0.990566,1,0.998418,1,0.743671,0.990506,0.988924,0.993711,0.996855,0.990566,0.987421,0.943396,0.987342,0.738924,0.95283,0.996855,0.996855,0.982595,0.987421,0.740506,0.984277,0.941456,0.982595,0.933544,0.981132,0.496855,0.689873,0.984277,0.990506,1,0.988924,0.987421,0.993671,0.996855,0.474843,0.981013,1,0.988924,0.949367,0.719937,0.969937,0.968553,0.723101,0.971519,0.75,0.940252,0.727848,0.981132,0.731013,0.987342,0.697785,0.737342,0.726266,0.462264,0.981013,0.708861,0.990506,0.955975,0.996855,0.949686,0.996835,0.982595,0.477987,0.487342,0.996855,0.959119,0.968354,0.963608,0.477987,0.737342,0.996835,0.940252,0.987342]
area_under_roc_curve
0.8576711895947774 [0.462025,0.927673,0.996835,0.990506,0.996855,0.713608,0.477987,0.954114,1,0.996835,0.993671,0.688291,0.996855,0.455975,0.996855,0.493671,0.993671,0.993671,0.915094,0.954114,0.987342,0.984177,0.984177,0.996835,0.713608,0.96519,0.670886,0.965409,0.993711,0.995253,0.971698,0.968553,0.474684,0.474684,0.987421,0.987342,0.984177,0.487342,0.737342,0.990506,0.990506,0.996835,0.993711,0.465409,0.984277,0.990566,0.740506,0.995253,0.963608,0.996835,0.91195,0.45283,0.974684,0.459119,0.734177,0.707278,0.993711,0.946203,0.977848,0.455975,0.984177,0.993671,0.990566,0.993711,0.740506,0.996835,0.471698,0.890823,0.712025,0.946203,0.905063,0.993671,0.990566,0.996855,0.678797,0.930818,0.985759,0.960443,0.996835,0.993711,1,0.990506,0.462025,1,0.481132,0.477987,0.993711,1,1,0.987342,0.990566,0.746835,0.471698,0.984277,0.458861,0.477987,0.969937,0.990566,0.974843,0.738924]
area_under_roc_curve
0.8862163890215744 [0.449367,0.993711,0.993671,0.984177,0.990566,0.985759,0.446541,0.941456,0.993711,1,0.737342,0.993671,0.487421,0.993711,0.990566,0.993671,0.990506,0.947785,0.937107,0.936709,0.962025,0.990506,0.962025,0.990506,0.950949,0.936709,0.987342,0.993711,1,0.96519,0.462264,0.990566,0.743671,0.969937,0.477987,0.993671,0.996835,0.957278,0.985759,0.990506,0.996835,0.697785,0.487421,0.443396,0.968553,0.937107,0.731013,0.996835,0.984177,0.735759,0.987421,0.984277,0.734177,0.993711,0.993671,0.691456,1,0.712025,0.984177,0.440252,0.993671,0.990506,0.993711,0.993711,0.996835,0.985759,0.990566,0.990506,0.71519,0.976266,0.462025,0.740506,0.930818,0.965409,0.693038,0.977987,0.993671,0.976266,0.996835,0.95283,0.918239,0.740506,0.974684,0.993671,0.933962,0.993711,0.955975,0.474843,0.68038,0.740506,0.974843,0.738924,0.446541,0.990566,0.72943,0.984277,0.987342,0.987421,0.984277,0.981013]
area_under_roc_curve
0.8854784899689513 [0.988924,0.484277,0.449686,0.738924,0.996855,0.996835,0.984177,0.990506,0.993711,1,1,0.996855,0.981013,0.996855,0.996855,0.474684,0.996855,0.996855,0.984177,0.987342,0.97943,0.908228,0.719937,0.990506,0.946203,0.446541,0.940252,0.974684,0.927673,0.996835,0.732595,0.496855,0.993711,0.955975,0.721519,0.990506,0.723101,0.990506,0.996835,0.993711,0.708861,0.697785,0.993671,0.987342,0.977987,0.990506,0.743671,0.990506,0.996855,1,0.459119,0.993671,1,0.430818,0.976266,0.960443,0.990506,1,0.988924,0.984277,0.993671,0.996835,0.993711,0.704114,0.72943,0.990566,0.465409,0.950949,0.981013,0.719937,0.996855,0.996835,0.996835,0.993711,0.962025,0.455975,0.990566,0.91195,0.990566,0.990566,0.731013,0.996855,0.727848,0.996835,0.982595,0.952532,0.996835,0.984277,0.940252,0.996835,0.993711,0.990506,0.674051,0.437107,0.468553,0.487342,0.981013,0.990566,0.443038,0.974684]
area_under_roc_curve
0.8829864013613568 [0.716772,0.990566,0.996855,0.75,0.990566,0.743671,0.990506,0.984177,0.984277,0.987342,0.977987,1,0.936709,0.993711,0.493711,0.727848,1,0.433962,0.973101,0.697785,0.993671,0.691456,0.723101,0.990506,0.987342,0.993711,0.893082,0.449367,0.471698,1,0.993671,0.990566,0.996855,0.993711,0.987342,0.985759,0.955696,0.89557,0.993671,0.996855,0.996835,0.727848,0.993671,0.974684,0.974843,0.966772,0.984177,0.971519,0.990566,0.990566,0.996855,0.984177,0.990506,0.993711,0.726266,0.710443,0.990506,0.996835,0.732595,0.471698,0.995253,0.474684,0.990566,0.718354,0.993671,0.462264,0.949686,0.963608,0.420886,0.947785,0.924528,0.993671,0.952532,0.996855,0.884494,0.990566,0.993711,0.962264,0.996855,0.996855,0.946203,0.965409,0.721519,0.996835,0.743671,0.993671,0.981013,0.968553,0.95283,0.726266,0.493711,0.988924,0.905063,0.867925,0.996855,0.976266,0.452532,0.977987,0.920886,0.987342]
area_under_roc_curve
0.8743669642146322 [0.940252,0.974684,0.990566,0.996835,0.723101,0.993711,0.726266,0.933962,0.735759,1,0.474843,1,0.993671,0.988924,0.977848,0.424528,1,0.990566,1,0.996855,0.993671,0.651899,0.927673,0.746835,0.737342,0.468553,0.921384,0.993671,0.996835,0.993711,0.966772,0.993671,0.955975,0.993711,0.988924,0.985759,0.727848,0.727848,0.971519,0.968553,0.993711,0.732595,0.987342,0.958861,0.735759,0.996835,0.993711,0.990506,0.971698,0.990566,0.982595,0.735759,0.993671,0.724684,0.993671,0.965409,0.992089,0.490566,0.996835,0.963608,1,0.748418,0.996835,0.724684,0.993711,0.993711,0.683544,0.990566,0.677215,0.424528,0.974843,0.974843,0.462025,0.481013,0.696203,0.962025,0.990566,0.971698,0.996855,0.735759,0.943038,0.993711,0.474843,0.968553,0.993671,0.987342,0.996835,0.726266,0.962264,0.990506,0.984177,0.990506,0.958861,0.704114,0.940252,0.727848,0.984277,0.732595,0.65981,0.987421]
area_under_roc_curve
0.8699563629488092 [0.45283,0.726266,0.477987,0.993671,0.993671,0.468553,0.966772,0.977987,0.993671,1,0.990566,0.996855,0.977848,0.987342,0.996835,0.481132,0.993711,0.943396,0.960443,0.984277,0.984177,0.97943,0.993711,0.993671,0.996835,0.45283,0.465409,0.974684,0.993671,0.949686,0.993671,0.996835,0.987421,1,0.982595,0.996835,0.742089,0.976266,0.481013,0.996855,0.471698,0.424051,0.990506,0.973101,0.735759,0.731013,0.993711,0.735759,0.971698,0.474843,0.947785,0.990506,0.735759,0.719937,1,0.943396,0.993671,0.481132,0.988924,0.993671,0.996835,0.990506,0.493671,0.968354,0.984277,0.965409,0.977848,0.937107,0.716772,0.930818,0.927673,0.996855,0.712025,0.458861,0.950949,0.987342,1,0.427673,0.993711,0.985759,0.713608,0.487421,0.990566,0.490566,0.993671,0.977848,0.734177,0.974684,0.996855,0.740506,0.993671,0.990506,0.971519,0.938291,0.996855,0.977848,0.455975,0.993671,0.707278,0.471698]
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
0.2737319913163607
kappa
0.34969615657801284
kappa
0.33714736634444664
kappa
0.34325295023088764
kappa
0.33051750680930014
kappa
0.29902115566782445
kappa
0.38067777865550206
kappa
0.3052540165002171
kappa
0.3116785728381418
kappa
0.29927007299270075
kb_relative_information_score
79.86003521219408
kb_relative_information_score
85.47794107278237
kb_relative_information_score
84.15993920575639
kb_relative_information_score
85.76632446174945
kb_relative_information_score
81.04689385788691
kb_relative_information_score
84.83571829851175
kb_relative_information_score
89.05315257333345
kb_relative_information_score
84.45649932756571
kb_relative_information_score
82.96036220704394
kb_relative_information_score
82.60524130296668
mean_absolute_error
0.015817634594886668
mean_absolute_error
0.015201921369779978
mean_absolute_error
0.015284175952897184
mean_absolute_error
0.015117343284236842
mean_absolute_error
0.015316915252945599
mean_absolute_error
0.01539970555411906
mean_absolute_error
0.014895460992074089
mean_absolute_error
0.015462345767905247
mean_absolute_error
0.015490552453688486
mean_absolute_error
0.015456894060400688
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
0.28125
predictive_accuracy
0.35625
predictive_accuracy
0.34375
predictive_accuracy
0.35
predictive_accuracy
0.3375
predictive_accuracy
0.30625
predictive_accuracy
0.3875
predictive_accuracy
0.3125
predictive_accuracy
0.31875
predictive_accuracy
0.30625
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
0.28125 [0,0,1,1,0,0,1,0,0,1,0,0.5,0,0,0,0,0.5,0,0,0,1,0,0,1,0,0,0,0,0,0,0.5,0.5,0.5,0,0.5,0,1,0,1,0,1,1,1,0,0,0,0,1,1,0.5,0,0,0,0,0,0,0,1,0,0,1,0,0.5,0.5,0,1,0,0,0,1,0,1,0,1,0,0,0,0,1,0,0,0,0,1,0,0.5,1,1,0,0,0.5,0,0,0,0,0.5,0,0,0,1]
recall
0.35625 [0,0,1,1,1,0,0,0,1,1,0.5,0.5,0,0,0,1,0.5,0,0,0,1,1,0,0,1,0,0,0,1,0,0.5,0,0,0,0,0,0,1,0,1,1,1,1,0,0,0.5,1,0,0,1,1,0.5,0,0,0,0,1,0,0,0,1,0,0,0.5,1,0.5,0.5,0,0,0,0,1,0,0,0,0,0.5,0,1,0,0,0.5,0,1,0,1,0,1,0,1,1,1,0,0,0.5,1,0,0.5,0,0]
recall
0.34375 [0,0,1,1,0.5,0,0,0,0.5,1,1,0.5,0,0,1,1,1,0,0,0.5,0,0,1,0,1,0,0,0,0.5,1,1,1,0,0,0,0,0,0,0,0.5,0.5,0,1,1,0,0,0.5,1,0.5,0.5,0.5,0,1,0,0,0.5,1,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0.5,0,0,0,0,1,0,1,1,1,0,0,1,1,1,0,0,0,0,1,0,0,0,0.5]
recall
0.35 [0,1,1,0,0.5,0,0,1,0,1,0.5,1,0,0,0,0.5,1,0,0,0,1,1,0.5,0,0,0,1,0,1,0,1,0.5,1,0.5,1,0,1,1,0,1,0.5,0,1,1,0,0,0.5,0,0,0,0,0,0,0,1,0,1,0,0,1,1,0,0,1,0.5,0,0,0.5,0,0.5,0,0.5,0,0,0,0,0,0,0.5,0,0,0.5,0,1,0,1,0,1,0,0,0,1,0,0,0,0,0,0,0,1]
recall
0.3375 [0,0,1,1,1,0,0,0,1,1,1,0,0,0,1,0,1,0.5,0,0,1,1,0,0,0,0,0,0,1,0.5,0,0,0,0,1,0,0.5,0,0.5,1,1,0.5,1,0,0,1,0.5,0,0,0,0,0,0.5,0,0,0,1,0,0,0,0.5,1,1,0,0.5,1,0,0,0,0,0,0,0,0,0,0,0.5,0,1,0,0,1,0,1,0,0,0,0,1,1,1,0.5,0,0,0,0,0.5,0,0,0]
recall
0.30625 [0,0,1,0,1,0,0,0,1,1,0,1,0,0,0,1,1,0.5,0,0,0,1,0,1,0,0,0,0,1,0.5,0,0,0.5,0.5,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0.5,0.5,1,0,0.5,1,1,0,1,0,0,0,1,0,1,0,1,0.5,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0.5,0,1,0,1,0,0,0,0.5,0,0.5,0,0,0.5,1,0,0,0,0]
recall
0.3875 [0.5,0,0,0.5,1,1,0,0,0,1,1,1,1,0,0,0,1,1,0,0.5,0.5,0,0,1,0,0,0,0.5,0,1,0.5,0,0,0,0.5,1,0,0,0,1,0,0,1,0,0,1,0.5,1,1,1,0,1,1,0,0,0.5,0,1,0,0,1,1,1,0,0.5,0,0,0,1,0,0,0,1,0,0.5,0,1,0,1,0,0,1,0.5,1,0,0,1,0,0,1,0,0,0,0,0,0,0,0,0,0]
recall
0.3125 [0,1,0,0.5,1,0,1,1,0,0,0,1,0,0,0,0.5,1,0,0,0,1,0,0.5,0,0.5,0,0,0,0,1,1,1,0,1,0,0,0.5,0,0,0,1,0.5,0,0.5,0,0.5,0,0,0,1,1,0,1,1,0.5,0,1,1,0,0,0.5,0,1,0,0,0,0,0,0,0,0,0,0.5,1,0,0,0,0,1,0,0,0,0.5,1,0.5,0,0.5,0,0,0,0,0.5,0,0,0,0.5,0,0,0,1]
recall
0.31875 [0,0.5,1,1,0,1,0.5,0,0,1,0,1,1,0.5,0,0,1,0,1,1,1,0,0,0.5,0.5,0,0,0,1,0,0,1,0,1,0.5,0,0,0,0.5,0,1,0.5,0.5,0,0,1,0,1,0,1,0.5,0.5,0,0.5,0,0,0,0,0,0,1,0.5,0,0.5,0,0,0,0,0,0,0,0,0,0,0,0,1,0,1,0,0,1,0,0,1,0,1,0,0,0,1,0,0,0,0,0.5,0,0,0,0]
recall
0.30625 [0,0,0,1,1,0,0.5,0,0,1,1,1,1,0,0,0,1,0,0,0,0.5,0,1,1,1,0,0,0,1,0,1,1,0,1,0.5,1,0.5,0,0,1,0,0,0.5,0,0,0.5,0,0.5,0,0,0,0,0,0.5,1,0,0,0,0,1,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,1,0,0,0,1,0,1,0.5,0.5,0,1,0.5,0,0,0,0,1,0,0,0,0,0]
relative_absolute_error
0.798870434085184
relative_absolute_error
0.7677738065545431
relative_absolute_error
0.7719280784291495
relative_absolute_error
0.7635021860725665
relative_absolute_error
0.7735815784315946
relative_absolute_error
0.7777629067736885
relative_absolute_error
0.7522960097007102
relative_absolute_error
0.7809265539346072
relative_absolute_error
0.7823511340246698
relative_absolute_error
0.7806512151717506
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
0.09361076194594034
root_mean_squared_error
0.09034830315067796
root_mean_squared_error
0.09130695748125563
root_mean_squared_error
0.09016213073853928
root_mean_squared_error
0.09218367071566053
root_mean_squared_error
0.09115786633691737
root_mean_squared_error
0.0889341927813471
root_mean_squared_error
0.09082383815137672
root_mean_squared_error
0.09212905466428575
root_mean_squared_error
0.09225216600040236
root_relative_squared_error
0.9408235567089801
root_relative_squared_error
0.908034612109343
root_relative_squared_error
0.9176694506492687
root_relative_squared_error
0.906163508965769
root_relative_squared_error
0.9264807501864201
root_relative_squared_error
0.9161710282694665
root_relative_squared_error
0.8938222681480661
root_relative_squared_error
0.9128139186911587
root_relative_squared_error
0.9259318382169022
root_relative_squared_error
0.9271691536997448
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
51.92308899950149
usercpu_time_millis
44.57047599998987
usercpu_time_millis
48.817581000093924
usercpu_time_millis
46.17518699978973
usercpu_time_millis
44.29505300004166
usercpu_time_millis
42.868860000453424
usercpu_time_millis
41.17992000055892
usercpu_time_millis
37.67670100023679
usercpu_time_millis
36.80356599988954
usercpu_time_millis
35.878688999673614
usercpu_time_millis_testing
1.7501329998594883
usercpu_time_millis_testing
1.6768800001045747
usercpu_time_millis_testing
1.6773140000623243
usercpu_time_millis_testing
1.7417509998267633
usercpu_time_millis_testing
1.6529810000065481
usercpu_time_millis_testing
1.6352550001101918
usercpu_time_millis_testing
1.3207230003899895
usercpu_time_millis_testing
1.4045630000509846
usercpu_time_millis_testing
1.3121759998284688
usercpu_time_millis_testing
1.2457319999157335
usercpu_time_millis_training
50.172955999642
usercpu_time_millis_training
42.89359599988529
usercpu_time_millis_training
47.1402670000316
usercpu_time_millis_training
44.43343599996297
usercpu_time_millis_training
42.642072000035114
usercpu_time_millis_training
41.23360500034323
usercpu_time_millis_training
39.85919700016893
usercpu_time_millis_training
36.272138000185805
usercpu_time_millis_training
35.491390000061074
usercpu_time_millis_training
34.63295699975788