10097845
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)
8022993
axis
0
8778
copy
true
8778
missing_values
"NaN"
8778
strategy
"most_frequent"
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
17
8783
min_samples_split
4
8783
min_weight_fraction_leaf
0.0
8783
presort
false
8783
random_state
3693
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
21116227
description
https://api.openml.org/data/download/21116227/description.xml
-1
21116228
predictions
https://api.openml.org/data/download/21116228/predictions.arff
area_under_roc_curve
0.8608749605429291 [0.852924,0.867622,0.871449,0.916785,0.896603,0.856061,0.825975,0.927281,0.893584,0.894117,0.926708,0.96005,0.885239,0.85247,0.866675,0.812322,0.901989,0.810073,0.78709,0.750276,0.889323,0.796125,0.923532,0.997258,0.861841,0.875335,0.879518,0.794468,0.895853,0.867207,0.951744,0.931542,0.827829,0.841757,0.892578,0.868766,0.755228,0.75509,0.986861,0.964035,0.757911,0.855153,0.958136,0.89175,0.868371,0.75144,0.962161,0.829072,0.711963,0.830552,0.950481,0.851207,0.952356,0.775706,0.886877,0.708767,0.998185,0.922684,0.888554,0.818182,0.799874,0.792831,0.893939,0.665167,0.8677,0.921579,0.850892,0.932884,0.647333,0.707643,0.77109,0.965653,0.861091,0.863439,0.75945,0.927912,0.899167,0.765724,0.863952,0.894768,0.922743,0.793304,0.78855,0.822266,0.882497,0.894906,0.876105,0.876263,0.787682,0.82996,0.964883,0.992543,0.879044,0.87139,0.891079,0.858744,0.888198,0.890152,0.793975,0.850438]
average_cost
0
kappa
0.3263888888888889
kb_relative_information_score
839.5946201023492
mean_absolute_error
0.015111129837254211
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
0.333125
prior_entropy
6.6438561897747395
recall
0.333125 [0.25,0.625,0.625,0.25,0.4375,0.125,0.3125,0.625,0.1875,0.3125,0.375,0.8125,0.375,0.0625,0.625,0.1875,0.8125,0.125,0.25,0.0625,0.1875,0.125,0.1875,1,0.125,0.0625,0.25,0.3125,0.5,0.6875,0.1875,0.5625,0.4375,0.125,0.4375,0.75,0.1875,0.3125,0,0.9375,0.1875,0.1875,0.75,0,0.6875,0.125,0.75,0.25,0.0625,0.5625,0.4375,0.3125,0.375,0,0.1875,0,0.8125,0.5625,0.25,0.1875,0.25,0.3125,0.5625,0.125,0.6875,0.125,0.25,0.6875,0.0625,0,0.0625,0.625,0.3125,0.5625,0.0625,0.625,0.5625,0,0.5625,0.1875,0,0.1875,0.3125,0.0625,0.375,0.625,0.25,0.125,0,0.0625,0.875,0.75,0.375,0,0.1875,0.375,0.25,0.1875,0,0.1875]
relative_absolute_error
0.7631883756188982
root_mean_prior_squared_error
0.09949874371066209
root_mean_squared_error
0.09099921221330556
root_relative_squared_error
0.9145764943316995
total_cost
0
area_under_roc_curve
0.8564533824934323 [0.981132,0.996835,0.75,0.949686,0.990506,0.993711,1,0.996855,0.996835,0.996855,0.996835,0.738924,0.969937,0.914557,0.993671,0.990566,1,0.481013,0.46519,0.471698,0.990566,0.468553,0.971698,1,0.990566,0.742089,0.740506,0.97943,0.985759,0.493711,0.726266,0.990506,0.734177,0.704114,1,0.477987,0.949686,0.490566,0.984277,1,0.993711,0.977987,0.990506,0.990506,0.996835,0.969937,1,0.996855,0.474684,0.718354,0.734177,0.996835,0.981132,0.696203,0.996855,0.455975,0.990506,0.993711,0.968553,0.71519,0.484277,0.987421,0.745253,0.474684,1,0.988924,0.996835,0.996855,0.965409,0.946541,0.672468,1,0.740506,0.72943,0.990566,0.987342,0.996835,0.969937,0.740506,0.990506,1,0.474684,0.971698,0.996855,0.731013,0.738924,0.914557,0.731013,0.992089,0.471698,0.987342,0.996855,0.981013,0.958861,0.963608,0.726266,0.993711,0.987342,0.446203,0.993711]
area_under_roc_curve
0.8780730037417396 [0.996855,0.996835,0.735759,1,0.996835,0.993711,0.735759,0.993711,0.966772,0.996855,0.995253,0.993671,0.996835,0.735759,0.993671,0.987421,0.996835,0.960443,0.731013,0.984277,0.993711,0.468553,0.965409,0.996855,0.996855,0.721519,0.974684,0.471519,0.993671,0.996855,0.988924,0.996835,0.974684,0.962025,0.981013,1,0.459119,0.955975,0.977987,0.996835,0.987421,0.996855,0.996835,0.976266,0.740506,0.72943,0.996855,0.949686,0.443038,0.990506,0.931962,0.719937,0.974843,0.950949,0.993711,0.468553,1,0.993711,0.987421,0.712025,1,0.987421,0.993671,0.496835,0.990566,0.987342,0.732595,0.974843,0.437107,0.955975,0.689873,0.990566,0.735759,0.996835,1,0.996835,0.977848,0.713608,0.988924,0.75,0.969937,0.731013,0.455975,0.443396,0.987342,0.988924,0.735759,0.962025,0.726266,0.487421,0.746835,0.990566,0.982595,0.721519,0.97943,0.987342,0.990566,0.707278,0.963608,0.996855]
area_under_roc_curve
0.8505185942600109 [0.724684,0.742089,0.957278,0.996855,0.72943,0.960443,0.490566,0.996835,0.962025,0.726266,0.713608,0.996835,1,0.743671,0.458861,0.718354,0.993671,0.691456,0.474843,0.688291,0.990566,0.946541,0.710443,0.996855,0.481132,0.996835,0.996835,0.996855,1,0.993671,0.943396,0.993671,0.996835,0.713608,0.468553,0.996855,0.996855,0.468553,0.996855,0.990506,0.481013,0.993711,0.993711,0.993711,0.740506,0.446541,0.993671,0.987421,0.718354,0.745253,0.993671,0.996855,0.990566,0.721519,0.990566,0.97943,1,0.987342,0.996855,0.443038,0.490566,0.490566,0.990506,0.987421,0.990506,0.726266,0.973101,0.993671,0.45283,0.468354,0.96519,0.990506,0.484277,0.738924,0.955975,0.974684,0.993671,0.449367,0.734177,0.996835,0.990566,0.993671,0.990506,0.992089,0.996855,0.977987,1,0.992089,0.743671,0.990566,0.990506,0.996855,0.965409,0.72943,0.993671,0.987421,0.727848,0.981013,0.987421,0.726266]
area_under_roc_curve
0.863425359246875 [0.990506,0.97943,0.996835,0.990566,0.742089,0.471519,0.990566,0.968354,0.977848,0.738924,0.990506,0.990506,0.481132,0.990506,1,0.957278,0.743671,0.960443,0.446541,0.723101,0.943396,0.996855,0.996835,0.996855,0.487421,0.974684,0.737342,0.990566,0.726266,0.746835,0.996855,0.996835,0.737342,0.981013,0.990566,0.496855,0.987421,0.993711,0.993711,0.993671,0.72943,0.990566,0.996855,0.959119,0.993671,0.996855,0.996835,1,0.93038,0.990506,0.981013,0.984277,0.908805,0.43038,0.996855,0.977848,1,0.992089,0.993711,0.97943,0.990566,0.987421,0.977848,0.462264,0.745253,0.974684,0.731013,1,0.971698,0.716772,0.699367,0.746835,0.993711,0.996835,0.41195,0.746835,0.737342,0.449367,0.996835,0.971519,0.487421,0.952532,1,0.436709,0.933962,0.487421,0.996855,0.968354,0.977848,0.959119,0.996835,0.981132,0.459119,0.696203,0.992089,0.496855,0.732595,0.977848,0.877358,0.685127]
area_under_roc_curve
0.844343727609267 [0.731013,1,1,0.993671,0.490566,0.737342,0.477987,0.992089,0.484277,0.990506,1,0.981013,0.996855,0.471698,0.996855,0.974684,0.75,0.996835,0.996855,0.987342,0.462025,0.719937,1,0.996835,0.990506,0.922468,0.962025,1,1,0.743671,0.990566,0.996855,0.487342,0.452532,0.971698,0.987342,0.69462,0.471519,0.992089,0.987342,0.993671,0.738924,0.490566,0.993711,0.990566,0.465409,0.987342,0.484177,0.737342,0.982595,0.996855,0.465409,0.981013,0.996855,0.735759,0.927215,0.996855,0.718354,0.990506,0.474843,0.737342,0.996835,0.993711,0.996855,0.735759,0.949367,0.471698,0.987342,0.474684,0.640823,0.987342,0.996835,0.990566,0.490566,0.954114,0.993711,0.740506,0.924051,0.987342,0.981132,0.993711,0.996835,0.481013,0.990506,0.977987,0.990566,0.465409,0.996855,1,0.737342,0.996855,0.987342,0.990566,0.990566,0.746835,0.984277,0.731013,0.993711,0.446541,0.737342]
area_under_roc_curve
0.8516126303638242 [0.723101,0.996855,1,0.949367,0.993711,0.97943,0.962264,0.738924,1,0.732595,0.97943,0.993671,0.987421,0.981132,0.996855,0.721519,0.996835,0.982595,0.955975,0.724684,0.988924,0.734177,0.981013,0.996835,0.990506,0.96519,0.954114,0.993711,0.993711,0.993671,0.984277,0.990566,0.72943,0.977848,0.474843,1,0.721519,0.724684,0.984177,0.996835,0.696203,0.723101,0.993711,0.993711,1,0.977987,0.993671,0.746835,0.713608,0.743671,0.993711,0.955975,0.971519,0.993711,0.710443,0.458861,0.990566,0.993671,0.993671,0.993711,0.738924,0.471519,0.965409,0.996855,0.745253,0.988924,0.984277,0.996835,0.439873,0.995253,0.458861,0.987342,0.990566,0.996855,0.667722,0.987421,0.743671,0.96519,0.746835,0.490566,0.990566,0.484177,0.727848,0.719937,0.468553,0.981132,0.933962,0.462264,0.471519,0.990506,0.996855,0.971519,0.474843,0.987421,0.988924,0.949686,0.966772,0.484277,0.886792,0.738924]
area_under_roc_curve
0.8616156904306977 [0.984177,0.474843,1,0.943038,1,0.993671,0.996835,0.996835,0.984277,0.993671,1,0.996855,0.726266,0.990566,0.484277,0.713608,0.493711,0.459119,0.685127,0.992089,0.737342,0.738924,0.982595,1,0.731013,0.946541,0.971698,0.734177,0.990566,0.993671,0.985759,0.493711,0.981132,0.990566,0.990506,0.740506,0.713608,0.734177,0.995253,0.493711,0.721519,0.981013,0.985759,0.996835,0.990566,0.700949,0.740506,0.72943,0.95283,1,0.987421,0.981013,0.988924,0.965409,0.981013,0.707278,1,0.737342,0.987342,0.971698,0.987342,0.938291,0.984277,0.468354,0.746835,0.990566,0.455975,0.996835,0.712025,0.455696,0.974843,1,0.971519,0.990566,0.643987,0.996855,0.996855,0.971698,0.993711,0.993711,0.982595,0.990566,0.97943,0.960443,0.993671,0.993671,0.708861,0.459119,0.977987,0.740506,0.996855,0.993671,0.723101,0.987421,0.487421,0.735759,0.984177,0.487421,0.705696,0.987342]
area_under_roc_curve
0.8456223628691978 [0.981013,0.993711,1,0.462025,0.996855,0.716772,0.985759,0.996835,0.493711,0.992089,0.987421,0.993711,0.712025,0.993711,0.474843,0.727848,1,0.455975,0.971519,0.471519,0.977848,0.72943,0.727848,0.993671,0.985759,0.977987,0.427673,0.734177,0.996855,0.734177,0.987342,0.990566,1,0.984277,0.981013,1,0.737342,0.974684,0.985759,0.996855,0.723101,0.723101,0.990506,0.726266,1,0.718354,0.996835,0.996835,0.930818,0.484277,0.962264,0.723101,0.731013,0.981132,0.990506,0.704114,0.993671,0.988924,0.723101,0.965409,0.490506,0.734177,0.987421,0.726266,0.996835,0.984277,0.965409,0.743671,0.46519,0.71519,0.987421,1,0.996835,0.462264,0.689873,1,0.955975,0.443396,1,0.468553,0.721519,1,0.71519,0.996835,0.696203,0.735759,0.993671,0.968553,0.968553,0.737342,1,0.996835,0.96519,0.937107,0.459119,0.993671,0.971519,0.990566,0.976266,0.962025]
area_under_roc_curve
0.8870995790542155 [0.468553,0.996835,0.5,1,0.993671,0.990566,0.72943,0.949686,0.974684,0.996855,0.481132,0.996855,0.939873,0.743671,0.993671,0.459119,0.993711,0.927673,0.996835,0.474843,0.987342,0.993671,0.984277,0.993671,0.745253,0.981132,0.946541,0.985759,0.726266,0.990566,0.990506,0.993671,0.930818,0.962264,0.737342,1,0.731013,0.704114,0.993671,0.996855,0.468553,0.718354,0.985759,0.735759,0.487342,0.737342,0.990566,0.974684,0.45283,0.993711,0.987342,0.990506,0.990506,0.696203,0.993671,0.459119,0.993671,0.949686,0.974684,0.973101,0.97943,0.996835,0.981013,0.731013,0.996855,0.987421,0.981013,0.5,0.724684,0.993711,0.974843,1,0.737342,0.990506,0.689873,0.731013,0.996855,0.996855,0.996855,0.981013,0.993671,0.987421,0.45283,0.981132,0.971519,0.996835,0.920886,0.957278,0.449686,0.993671,1,0.992089,0.996835,0.94462,0.990566,0.710443,0.974843,0.987342,0.977848,0.996855]
area_under_roc_curve
0.8668398216702491 [0.933962,0.477848,0.496855,0.960443,0.993671,0.990566,0.704114,0.490566,0.734177,0.981132,1,0.993711,0.990506,0.987342,1,0.993711,0.993711,1,0.993671,0.993711,0.984177,0.990506,0.996855,0.990506,1,0.440252,0.993711,0.484177,0.732595,0.990566,0.982595,0.75,0.996855,0.95283,0.971519,0.731013,0.71519,0.993671,0.984177,1,0.974843,0.974684,0.990506,0.740506,1,0.713608,0.993711,0.721519,0.990566,0.474843,0.990506,0.704114,0.993671,0.71519,0.734177,0.449686,1,0.987421,0.471519,1,0.987342,0.471519,0.484177,0.721519,0.990566,0.490566,0.958861,0.993711,0.981013,0.437107,0.455975,1,0.981013,0.990506,0.712025,0.996835,1,1,0.468553,0.996835,0.993671,0.477987,0.987421,0.474843,0.973101,0.996835,0.947785,0.935127,0.437107,0.988924,1,0.996835,0.996835,0.982595,0.990566,0.993671,0.996855,0.996835,0.716772,0.977987]
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
0.36197094125078966
kappa
0.3496191641343384
kappa
0.3305967792863909
kappa
0.32420163423202936
kappa
0.31785883467550924
kappa
0.3058020747051631
kappa
0.3117057384166074
kappa
0.31815491457207123
kappa
0.2804166009152596
kappa
0.36244920503412636
kb_relative_information_score
84.95043274396714
kb_relative_information_score
87.30799872894914
kb_relative_information_score
83.51548832154285
kb_relative_information_score
83.26375409605336
kb_relative_information_score
80.34437576277587
kb_relative_information_score
81.557880274159
kb_relative_information_score
82.48919173632584
kb_relative_information_score
80.43100713520955
kb_relative_information_score
87.66290465195704
kb_relative_information_score
88.07158665141574
mean_absolute_error
0.014887765381633342
mean_absolute_error
0.014938370302226181
mean_absolute_error
0.01497332445203348
mean_absolute_error
0.015205061197069155
mean_absolute_error
0.015218032402249717
mean_absolute_error
0.015370494889638573
mean_absolute_error
0.015362521217758256
mean_absolute_error
0.015312235141718308
mean_absolute_error
0.015150294664730956
mean_absolute_error
0.014693198723484518
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
0.36875
predictive_accuracy
0.35625
predictive_accuracy
0.3375
predictive_accuracy
0.33125
predictive_accuracy
0.325
predictive_accuracy
0.3125
predictive_accuracy
0.31875
predictive_accuracy
0.325
predictive_accuracy
0.2875
predictive_accuracy
0.36875
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
0.36875 [0,1,0.5,0,0.5,0,1,1,1,0,1,0.5,0,0,1,1,1,0,0,0,1,0,0,1,0,0.5,0,0,0.5,0,0,0,0.5,0,1,0,0,0,0,1,1,0,1,0,1,0.5,1,0,0,0,0.5,1,0,0,1,0,1,1,0,0,0,1,0,0,1,0.5,0,1,0,0,0,1,0.5,0.5,0,0.5,1,0,0.5,0,0,0,0,1,0,0.5,0,0.5,0,0,1,1,1,0,0,0,0,0,0,0]
recall
0.35625 [1,1,0.5,1,0,0,0.5,1,0,1,0,1,0,0.5,0,0,1,0,0.5,0,0,0,0,1,0,0,0.5,0,0.5,1,0.5,1,0,0,0,1,0,0,0,1,0,1,1,0,0.5,0,1,0,0,1,0,0.5,0,0,1,0,1,0,0,0,1,1,1,0,1,0,0.5,0,0,0,0,0,0,1,1,1,0,0,0.5,0.5,0,0,0,0,1,0.5,0.5,0,0,0,0.5,1,0,0,0.5,0.5,0,0,0,1]
recall
0.3375 [0,0.5,0,1,0,0,0,1,0,0,0,1,1,0,0,0,1,0,0,0,0,0,0,1,0,0,0,1,1,1,0,1,1,0,0,1,0,0,0,1,0,0,1,0,0.5,0,0.5,0,0,0.5,1,1,0,0,0,0,1,0.5,1,0,0,0,1,1,0.5,0,0,1,0,0,0,0,0,0.5,0,0,1,0,0,1,0,0.5,1,0,1,0,0,0,0,1,0.5,1,0,0,0.5,1,0,0.5,0,0.5]
recall
0.33125 [1,0,1,0,0.5,0,0,0,0,0,1,0.5,0,0,1,0,0.5,0,0,0,0,0,0,1,0,0,0.5,0,0,0.5,1,1,0.5,0.5,1,0,1,1,0,1,0,0,1,0,1,1,1,0,0,1,0,1,0,0,0,0,1,1,0,0,1,0,0,0,0.5,0,0.5,1,0,0,0,0.5,0,1,0,0.5,0,0,1,0,0,0,1,0,0,0,1,0,0,0,1,0,0,0,0,0,0.5,0,0,0]
recall
0.325 [0,1,1,1,0,0,0,0.5,0,1,0,0.5,1,0,1,0.5,0.5,1,1,0,0,0,1,1,0,0,0.5,0,1,0.5,0,0,0,0,0,1,0,0,0,1,1,0.5,0,0,1,0,0,0,0,0.5,0,0,0,0,0,0,1,0,1,0,0,1,1,1,0.5,0,0,0,0,0,0,0,0,0,0,1,0.5,0,0.5,0,0,1,0,0,0,0,0,1,0,0,1,1,0,0,0.5,0,0.5,1,0,0]
recall
0.3125 [0,1,1,0,1,0,0,0.5,1,0.5,0,1,1,0,1,0,1,0,0,0,0,0.5,0,1,0,0,0.5,1,0,1,0,1,0,0,0,1,0,0.5,0,1,0,0,1,0,1,0,1,0.5,0,0.5,1,0,0,0,0,0,0,1,0,1,0.5,0,0,0,0.5,0,1,1,0,0,0,1,1,1,0,0,0.5,0,0.5,0,0,0,0,0,0,1,0,0,0,0,1,0,0,0,0,0,0,0,0,0.5]
recall
0.31875 [0.5,0,1,0,1,0,0,1,0,0,1,1,0.5,0,0,0,0,0,0,0,0.5,0.5,0,1,0.5,0,0,0.5,0,1,0.5,0,1,0,1,0.5,0,0.5,0,0,0,0,0.5,0,0,0,0.5,0,0,1,1,0,0.5,0,0,0,1,0.5,0.5,0,0,0,1,0,0.5,1,0,1,0,0,0,1,0,0,0,1,1,0,1,0,0,0,0,0,1,1,0,0,0,0,1,1,0.5,0,0,0.5,0.5,0,0,0]
recall
0.325 [0,1,1,0,1,0,0.5,1,0,0.5,0,1,0,0,0,0.5,1,0,0,0,0,0,0,1,0,0,0,0.5,1,0,0,1,1,1,0,1,0.5,0,0,1,0,0.5,1,0,1,0,1,1,0,0,0,0,0.5,0,0,0,0,0.5,0,0,0,0.5,1,0,1,0,0,0.5,0,0,1,1,1,0,0,1,0,0,1,0,0,0,0,0,0,0.5,1,0,0,0,1,1,0,0,0,1,0,1,0,0]
recall
0.2875 [0,1,0,0,0,1,0.5,0,0,0,0,1,0,0,1,0,1,0,0,0,0.5,0,1,1,0.5,0,0,0.5,0.5,1,0,0,0,0,0.5,1,0.5,0,0,1,0,0,0.5,0,0,0,1,0,0,1,0.5,0,1,0,0,0,1,0,0,0,0.5,0,1,0,1,0,0,0,0,0,0,1,0.5,0,0,0.5,1,0,1,0,0,0,0,0,0.5,1,0,0,0,0,1,0.5,0.5,0,0,0.5,0,0,0,0]
recall
0.36875 [0,0,0,0,1,1,0,0,0,0,1,1,1,0,1,0,1,0,1,1,0,0,0,1,0,0,0,0,0.5,1,0,0.5,1,0,0.5,0.5,0,1,0,1,0,0,0.5,0,1,0,1,0.5,1,0,0.5,0,1,0,0.5,0,1,1,0,1,0,0,0,0,1,0,0.5,1,0.5,0,0,1,0,1,0,1,1,0,0,0,0,0,1,0,0,1,0,0,0,0,1,1,1,0,0,0,1,0,0,0]
relative_absolute_error
0.7519073425067332
relative_absolute_error
0.7544631465770786
relative_absolute_error
0.7562285076784573
relative_absolute_error
0.76793238369036
relative_absolute_error
0.7685874950631156
relative_absolute_error
0.7762876206888155
relative_absolute_error
0.7758849099877894
relative_absolute_error
0.773345209177691
relative_absolute_error
0.765166397208633
relative_absolute_error
0.742080743610328
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
0.0900739645071972
root_mean_squared_error
0.08942413568645338
root_mean_squared_error
0.0910700658755826
root_mean_squared_error
0.09076961101982445
root_mean_squared_error
0.09312120799595706
root_mean_squared_error
0.09157752595993644
root_mean_squared_error
0.09237625371835217
root_mean_squared_error
0.09193125543649958
root_mean_squared_error
0.0907395110071181
root_mean_squared_error
0.088821745374023
root_relative_squared_error
0.9052774050004921
root_relative_squared_error
0.8987463796175641
root_relative_squared_error
0.91528860043108
root_relative_squared_error
0.9122689155129281
root_relative_squared_error
0.935903354385553
root_relative_squared_error
0.9203887661761825
root_relative_squared_error
0.9284162821892329
root_relative_squared_error
0.9239438811793603
root_relative_squared_error
0.9119663990028316
root_relative_squared_error
0.8926921291821804
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
197.12713900025847
usercpu_time_millis
184.23334099952626
usercpu_time_millis
170.16399899966927
usercpu_time_millis
138.71835300051316
usercpu_time_millis
142.22135900035937
usercpu_time_millis
139.4073239998761
usercpu_time_millis
139.76541600004566
usercpu_time_millis
141.5304379997906
usercpu_time_millis
141.6989139997895
usercpu_time_millis
141.66636500067398
usercpu_time_millis_testing
1.719876000606746
usercpu_time_millis_testing
1.724828999613237
usercpu_time_millis_testing
1.330471000073885
usercpu_time_millis_testing
1.3431530005618697
usercpu_time_millis_testing
1.4969519997976022
usercpu_time_millis_testing
1.3409459998001694
usercpu_time_millis_testing
1.3628110000354354
usercpu_time_millis_testing
1.3823700001012185
usercpu_time_millis_testing
1.335656000264862
usercpu_time_millis_testing
1.3308640000104788
usercpu_time_millis_training
195.40726299965172
usercpu_time_millis_training
182.50851199991303
usercpu_time_millis_training
168.8335279995954
usercpu_time_millis_training
137.3751999999513
usercpu_time_millis_training
140.72440700056177
usercpu_time_millis_training
138.06637800007593
usercpu_time_millis_training
138.40260500001023
usercpu_time_millis_training
140.14806799968937
usercpu_time_millis_training
140.36325799952465
usercpu_time_millis_training
140.3355010006635