10091902
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)
8017009
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
4
8783
min_samples_split
15
8783
min_weight_fraction_leaf
0.0
8783
presort
false
8783
random_state
58200
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
21104341
description
https://api.openml.org/data/download/21104341/description.xml
-1
21104342
predictions
https://api.openml.org/data/download/21104342/predictions.arff
area_under_roc_curve
0.8102600220959596 [0.891098,0.867444,0.840475,0.901653,0.872179,0.868963,0.837851,0.899128,0.774562,0.968434,0.743115,0.899641,0.713404,0.799183,0.963542,0.806877,0.842132,0.700541,0.764639,0.764323,0.867069,0.66933,0.859572,0.936099,0.867562,0.606258,0.669882,0.830019,0.868391,0.871982,0.810152,0.902659,0.77614,0.676768,0.805516,0.839055,0.799992,0.702553,0.837101,0.931088,0.738025,0.838009,0.841442,0.7718,0.710444,0.837378,0.841185,0.902127,0.833925,0.806937,0.771208,0.742128,0.80449,0.673946,0.772451,0.733665,0.999625,0.839311,0.831696,0.637843,0.901417,0.903804,0.807134,0.801393,0.872179,0.674992,0.732915,0.931404,0.666469,0.699751,0.663569,0.872672,0.743687,0.839489,0.795908,0.741596,0.903981,0.701448,0.934028,0.742977,0.795553,0.872534,0.801156,0.835405,0.836845,0.80013,0.903389,0.834576,0.899917,0.836194,0.903527,0.840238,0.770814,0.859454,0.806739,0.710306,0.708827,0.864268,0.665621,0.775687]
average_cost
0
f_measure
0.45690614701655535 [0.311111,0.44898,0.740741,0.785714,0.666667,0.529412,0.588235,0.444444,0.428571,0.9375,0.461538,0.516129,0.411765,0.357143,0.588235,0.5,0.689655,0.142857,0.228571,0.176471,0.424242,0.277778,0.243902,0.848485,0.444444,0.193548,0.0625,0.304348,0.466667,0.545455,0.666667,0.685714,0.470588,0.121212,0.5,0.545455,0.243902,0.242424,0.5,0.692308,0.413793,0.551724,0.733333,0.3125,0.090909,0.606061,0.709677,0.6875,0.444444,0.486486,0.375,0.388889,0.444444,0.296296,0.363636,0.222222,0.969697,0.580645,0.27027,0,0.647059,0.645161,0.484848,0.4,0.645161,0.142857,0.242424,0.466667,0.153846,0.171429,0.181818,0.733333,0.434783,0.666667,0.352941,0.37037,0.705882,0.214286,0.727273,0.518519,0.166667,0.592593,0.378378,0.285714,0.580645,0.357143,0.774194,0.461538,0.588235,0.551724,0.722222,0.666667,0.4375,0.368421,0.466667,0.461538,0.461538,0.45,0.148148,0.484848]
kappa
0.4501262626262626
kb_relative_information_score
853.6555405021089
mean_absolute_error
0.011902027000776886
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
0.47473854081016187 [0.241379,0.333333,0.909091,0.916667,0.6,0.5,0.555556,0.4,0.5,0.9375,0.6,0.533333,0.388889,0.416667,0.555556,0.5,0.769231,0.166667,0.210526,0.166667,0.411765,0.25,0.2,0.823529,0.4,0.2,0.0625,0.233333,0.5,0.529412,0.714286,0.631579,0.444444,0.117647,0.45,0.529412,0.2,0.235294,0.583333,0.9,0.461538,0.615385,0.785714,0.3125,0.166667,0.588235,0.733333,0.6875,0.4,0.428571,0.375,0.35,0.545455,0.363636,0.352941,0.2,0.941176,0.6,0.238095,0,0.611111,0.666667,0.470588,0.428571,0.666667,0.166667,0.235294,0.5,0.2,0.157895,0.333333,0.785714,0.714286,0.818182,0.333333,0.454545,0.666667,0.25,0.705882,0.636364,0.15,0.727273,0.333333,0.263158,0.6,0.416667,0.8,0.6,0.555556,0.615385,0.65,0.714286,0.4375,0.318182,0.5,0.6,0.6,0.375,0.181818,0.470588]
predictive_accuracy
0.455625
prior_entropy
6.6438561897747395
recall
0.455625 [0.4375,0.6875,0.625,0.6875,0.75,0.5625,0.625,0.5,0.375,0.9375,0.375,0.5,0.4375,0.3125,0.625,0.5,0.625,0.125,0.25,0.1875,0.4375,0.3125,0.3125,0.875,0.5,0.1875,0.0625,0.4375,0.4375,0.5625,0.625,0.75,0.5,0.125,0.5625,0.5625,0.3125,0.25,0.4375,0.5625,0.375,0.5,0.6875,0.3125,0.0625,0.625,0.6875,0.6875,0.5,0.5625,0.375,0.4375,0.375,0.25,0.375,0.25,1,0.5625,0.3125,0,0.6875,0.625,0.5,0.375,0.625,0.125,0.25,0.4375,0.125,0.1875,0.125,0.6875,0.3125,0.5625,0.375,0.3125,0.75,0.1875,0.75,0.4375,0.1875,0.5,0.4375,0.3125,0.5625,0.3125,0.75,0.375,0.625,0.5,0.8125,0.625,0.4375,0.4375,0.4375,0.375,0.375,0.5625,0.125,0.5]
relative_absolute_error
0.6011124747867104
root_mean_prior_squared_error
0.09949874371066209
root_mean_squared_error
0.09123417885753826
root_relative_squared_error
0.9169379979594836
total_cost
0
area_under_roc_curve
0.7955793229042274 [0.996855,0.735759,0.996835,1,0.496835,1,0.743671,1,0.493671,0.996855,0.490506,0.734177,0.746835,0.740506,1,0.490566,0.493671,0.493671,0.993671,0.981132,0.984277,0.471698,0.996855,1,0.987421,0.474684,0.487342,1,0.746835,1,0.746835,0.993671,0.737342,0.490506,0.493671,0.484277,0.493711,0.477987,0.996855,0.745253,1,0.996855,0.996835,0.738924,0.496835,0.993671,0.996855,1,1,0.740506,0.474684,0.745253,0.990566,0.72943,0.996855,0.993711,1,1,0.993711,0.977848,1,1,0.746835,0.987342,0.996855,0.490506,0.982595,1,0.996855,0.471698,0.477848,1,0.490506,1,1,1,0.746835,0.726266,1,1,0.742089,0.996835,0.993711,0.996855,0.490506,0.737342,0.493671,0.996835,0.990506,0.477987,1,1,0.742089,0.987342,0.748418,0.490506,1,1,0.484177,0.993711]
area_under_roc_curve
0.8145885578377516 [1,0.993671,0.745253,1,1,0.971698,0.995253,0.493711,0.748418,1,0.995253,0.745253,0.743671,0.742089,0.988924,0.996855,0.75,0.731013,0.969937,0.471698,0.996855,0.487421,0.968553,1,0.996855,0.487342,0.743671,0.484177,1,0.990566,1,1,0.746835,0.477848,0.990506,1,0.487421,0.996855,1,1,1,1,0.996835,0.746835,0.490506,1,1,1,0.743671,0.993671,1,0.746835,0.996855,0.992089,0.490566,0.477987,1,1,0.996855,0.477848,1,0.496855,0.996835,0.737342,0.5,0.737342,0.746835,1,0.474843,0.977987,0.734177,1,0.745253,0.746835,0.474843,0.740506,0.746835,0.72943,1,0.484177,0.72943,0.75,0.490566,1,0.740506,0.745253,0.996835,0.737342,0.996835,0.990566,0.748418,1,0.737342,0.993671,1,0.493671,0.477987,0.496835,0.987342,0.496855]
area_under_roc_curve
0.8093708950322425 [0.974684,0.742089,1,0.984277,1,0.985759,0.496855,0.996835,0.740506,1,0.743671,0.984177,0.993711,0.993671,1,0.992089,1,0.474684,0.987421,0.474684,0.993711,0.474843,0.740506,0.996855,0.990566,0.734177,0.993671,0.987421,0.737342,0.996835,0.993711,1,0.746835,0.72943,1,0.496855,0.996855,0.477987,1,0.985759,0.745253,0.474843,1,0.987421,0.743671,0.484277,0.748418,0.996855,0.743671,0.742089,0.992089,0.987421,0.977987,0.490506,0.993711,0.971519,1,0.996835,0.484277,0.481013,0.490566,0.996855,0.748418,0.484277,0.988924,0.487342,1,0.998418,0.481132,0.724684,0.477848,1,1,0.735759,0.468553,0.493671,1,0.477848,0.496835,0.75,0.981132,0.993671,0.487342,0.490506,0.996855,0.496855,1,0.748418,0.996835,1,0.746835,1,0.481132,0.977848,0.748418,1,0.738924,0.974684,0.468553,0.742089]
area_under_roc_curve
0.8069189853514847 [0.977848,0.987342,1,1,0.75,0.745253,0.996855,0.998418,0.745253,1,0.735759,0.745253,0.496855,0.481013,1,0.993671,1,0.990506,0.484277,0.735759,0.996855,0.474843,0.996835,0.490566,0.484277,0.732595,0.726266,0.487421,0.988924,0.996835,0.993711,0.740506,0.996835,0.735759,0.987421,0.490566,0.993711,0.474843,0.490566,0.996835,0.981013,0.987421,1,0.996855,0.740506,0.487421,0.746835,0.996855,0.740506,0.493671,0.496835,0.993711,0.477987,0.490506,0.996855,0.742089,1,0.75,1,0.487342,0.996855,0.5,0.742089,0.484277,0.746835,0.734177,0.732595,0.745253,0.962264,0.72943,0.458861,0.75,0.481132,1,0.968553,0.496835,1,0.740506,0.996835,0.748418,0.984277,0.75,0.996835,0.987342,0.996855,0.968553,1,1,1,1,1,1,0.468553,0.96519,0.996835,0.496855,0.487342,0.996835,1,0.490506]
area_under_roc_curve
0.8246432409839979 [0.734177,0.971698,0.75,0.988924,1,0.484177,0.490566,0.974684,0.487421,1,0.743671,0.976266,0.490566,0.471698,0.990566,0.993671,0.745253,0.740506,0.959119,0.737342,0.987342,1,0.993671,1,0.996835,0.732595,0.477848,0.990566,1,0.75,0.5,0.487421,0.5,0.742089,0.496855,0.998418,0.985759,0.732595,0.746835,1,0.740506,1,1,0.487421,0.990566,0.996855,1,1,0.987342,1,0.949686,0.484277,0.981013,0.484277,0.745253,0.705696,0.996855,0.981013,0.981013,0.493711,0.990506,1,0.993711,1,0.993671,0.993671,0.477987,0.992089,0.487342,0.484177,0.726266,0.987342,1,0.477987,0.734177,0.984277,0.75,0.996835,0.998418,0.996855,0.477987,1,0.995253,0.988924,0.490566,0.471698,1,1,0.993671,0.740506,0.990566,0.496835,0.493711,0.996855,0.487342,0.493711,0.743671,0.981132,0.471698,0.746835]
area_under_roc_curve
0.8154809529496058 [0.732595,0.996855,0.985759,1,0.996855,1,1,0.735759,1,0.75,0.743671,1,0.496855,0.974843,0.993711,0.748418,0.746835,0.974684,0.484277,0.973101,0.75,0.743671,0.969937,1,0.990506,0.742089,0.723101,0.971698,1,0.746835,1,1,0.745253,0.745253,0.493711,0.75,0.985759,0.981013,0.974684,0.987342,0.985759,1,0.493711,0.990566,0.965409,1,0.748418,0.746835,0.996835,0.745253,0.474843,0.996855,0.496835,0.481132,0.705696,0.735759,1,0.748418,0.727848,0.984277,0.993671,0.984177,0.993711,0.487421,1,0.471519,0.484277,1,0.738924,0.740506,0.740506,0.493671,1,0.996855,0.743671,0.996855,0.996835,0.484177,0.996835,0.487421,0.993711,0.743671,0.481013,0.993671,0.974843,1,1,1,0.493671,0.490506,1,0.496835,0.477987,0.984277,0.742089,1,0.735759,1,0.468553,0.742089]
area_under_roc_curve
0.8291263633468675 [0.996835,0.490566,0.496855,0.745253,1,1,0.985759,0.993671,1,1,1,1,0.996835,1,1,0.487342,1,0.987421,0.742089,0.987342,0.743671,0.471519,0.484177,0.996835,0.734177,0.487421,0.490566,0.738924,0.493711,0.5,0.745253,0.493711,1,0.490566,0.735759,0.998418,0.977848,0.996835,0.996835,1,0.484177,0.746835,1,0.745253,1,0.985759,0.5,0.745253,0.993711,0.993711,0.496855,0.487342,1,0.487421,0.982595,0.743671,1,0.745253,0.990506,0.484277,0.740506,1,1,0.954114,1,0.993711,0.477987,0.982595,0.738924,0.745253,0.971698,1,1,1,0.97943,0.471698,0.996855,0.477987,0.993711,0.471698,0.740506,1,0.990506,0.742089,1,0.738924,1,0.484277,0.981132,0.984177,1,0.996835,0.738924,0.484277,1,0.487342,0.993671,0.993711,0.721519,1]
area_under_roc_curve
0.803910665950163 [0.971519,1,0.481132,0.743671,0.490566,0.75,1,0.746835,0.490566,1,0.487421,1,0.745253,1,0.493711,0.746835,1,0.484277,0.731013,0.995253,0.740506,0.727848,0.742089,0.996835,0.993671,0.455975,0.996855,0.97943,0.496855,0.987342,0.75,0.993711,1,0.993711,0.743671,0.743671,0.487342,0.490506,0.743671,1,0.484177,0.993671,1,0.745253,0.496855,0.737342,0.996835,0.995253,0.993711,1,0.990566,0.743671,0.732595,0.993711,0.75,0.484177,1,0.996835,0.732595,0.487421,0.987342,1,1,0.993671,0.75,0.490566,0.481132,0.745253,0.700949,0.735759,0.443396,1,0.748418,1,0.738924,1,1,0.977987,0.987421,0.996855,0.477848,0.993711,0.746835,0.981013,0.75,0.734177,1,0.481132,1,0.996835,0.493711,0.990506,1,0.484277,1,0.745253,0.746835,0.481132,0.477848,0.746835]
area_under_roc_curve
0.8040687694053021 [0.996855,0.996835,1,0.996835,1,0.993711,0.487342,0.996855,0.987342,1,0.487421,1,0.490506,0.982595,0.995253,1,1,0.487421,0.496835,0.487421,1,0.995253,0.984277,0.75,0.995253,0.481132,0.477987,0.976266,0.995253,1,0.746835,0.996835,0.493711,0.487421,0.993671,0.995253,0.735759,0.474684,0.992089,0.487421,0.481132,0.496835,0.493671,0.727848,0.743671,0.745253,1,0.995253,0.477987,0.993711,0.988924,0.743671,0.742089,0.740506,0.496835,0.971698,1,0.487421,0.748418,0.732595,0.743671,0.75,0.743671,0.742089,0.490566,0.487421,0.726266,1,0.477848,0.949686,1,0.493711,0.738924,0.745253,0.740506,0.493671,0.996855,0.487421,1,0.746835,0.981013,1,1,0.493711,1,0.995253,0.996835,0.743671,0.487421,1,0.996835,0.743671,1,0.742089,0.490566,0.987342,0.490566,0.987342,0.955696,1]
area_under_roc_curve
0.8003715617785208 [0.484277,0.740506,0.493711,0.748418,1,0.996855,1,0.984277,0.996835,1,0.996855,1,0.738924,0.742089,0.996835,0.490566,0.996855,0.468553,0.727848,0.490566,0.737342,0.462025,0.990566,1,0.493671,0.487421,0.496855,0.726266,0.984177,1,0.746835,1,0.996855,0.993711,0.995253,0.990506,0.743671,0.734177,0.490506,0.996855,0.484277,0.732595,0.496835,0.745253,0.742089,0.748418,1,0.746835,0.471698,0.487421,0.748418,0.740506,0.746835,0.740506,0.746835,0.487421,1,0.490566,0.737342,0.738924,1,1,0.496835,0.742089,0.993711,0.987421,0.732595,0.981132,0.726266,0.487421,0.981132,1,0.493671,0.742089,0.977848,0.995253,1,0.971698,0.996855,0.743671,0.982595,0.496855,0.990566,0.493711,0.993671,0.990506,0.742089,0.976266,1,0.745253,1,0.996835,0.974684,0.731013,0.955975,0.993671,0.484277,0.745253,0.496835,1]
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
0.46969696969696967
kappa
0.46961325966850825
kappa
0.4062845412916469
kappa
0.45045400710619815
kappa
0.4377985708081646
kappa
0.43808697024702076
kappa
0.48827292110874204
kappa
0.46936197094125076
kappa
0.45041061276058114
kappa
0.4190314559734775
kb_relative_information_score
83.65272729246139
kb_relative_information_score
88.21442454841214
kb_relative_information_score
83.39247405634076
kb_relative_information_score
85.36146780352186
kb_relative_information_score
86.7863088157961
kb_relative_information_score
84.49462862687534
kb_relative_information_score
91.23798607878759
kb_relative_information_score
85.00394042510219
kb_relative_information_score
84.69599095976523
kb_relative_information_score
80.81559189505757
mean_absolute_error
0.011695018523143526
mean_absolute_error
0.011394473235098235
mean_absolute_error
0.012371085164835163
mean_absolute_error
0.011924138361638364
mean_absolute_error
0.01202818986568987
mean_absolute_error
0.01223025550838051
mean_absolute_error
0.011234278568653566
mean_absolute_error
0.01180158244533245
mean_absolute_error
0.011951020854145853
mean_absolute_error
0.012390227480852486
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
0.475
predictive_accuracy
0.4125
predictive_accuracy
0.45625
predictive_accuracy
0.44375
predictive_accuracy
0.44375
predictive_accuracy
0.49375
predictive_accuracy
0.475
predictive_accuracy
0.45625
predictive_accuracy
0.425
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 [1,0.5,1,1,0,1,0.5,1,0,1,0,0,0.5,0,0.5,0,0,0,0.5,0,0,0,1,1,0,0,0,1,0.5,1,0.5,0.5,0.5,0,0,0,0,0,1,0.5,1,1,1,0.5,0,1,1,1,1,0.5,0,0.5,0,0,1,1,1,1,0,0,1,1,0.5,0.5,1,0,0.5,1,0,0,0,1,0,1,0,1,0.5,0,1,1,0,1,1,1,0,0.5,0,1,0.5,0,1,1,0.5,0.5,0.5,0,1,1,0,1]
recall
0.475 [1,1,0.5,1,1,0,0.5,0,0.5,1,0.5,0.5,0.5,0,0.5,1,0.5,0,0.5,0,1,0,0,1,1,0,0,0,1,0,1,1,0.5,0,1,1,0,1,0,1,1,1,1,0,0,1,1,1,0,0.5,1,0.5,1,0.5,0,0,1,1,1,0,1,0,0.5,0.5,0,0,0.5,1,0,0,0.5,1,0,0.5,0,0.5,0,0,1,0,0,0,0,1,0.5,0.5,1,0,0.5,0,0.5,1,0.5,1,1,0,0,0,0.5,0]
recall
0.4125 [0.5,0.5,1,0,1,0.5,0,0.5,0,1,0.5,0.5,1,0.5,1,0.5,1,0,0,0,0,0,0.5,1,0,0.5,0,0,0.5,1,1,1,0,0,1,0,1,0,1,0,0.5,0,1,1,0,0,0.5,1,0.5,0.5,0.5,0,0,0,1,0,1,1,0,0,0,1,0.5,0,0.5,0,0.5,0.5,0,0,0,1,1,0,0,0,1,0,0,0.5,0,0.5,0,0,1,0,1,0.5,1,1,0.5,1,0,0,0.5,1,0,0.5,0,0]
recall
0.45625 [0,1,1,1,0.5,0.5,1,1,0.5,1,0,0,0,0,1,0.5,0.5,0.5,0,0,1,0,1,0,0,0.5,0,0,0.5,1,1,0.5,1,0,1,0,1,0,0,1,0.5,0,1,1,0,0,0.5,1,0.5,0,0,1,0,0,0,0.5,1,0.5,1,0,1,0,0.5,0,0.5,0,0.5,0,0,0,0,0.5,0,1,0,0,1,0.5,1,0.5,0,0.5,0.5,0,1,0,1,0.5,1,1,1,1,0,0.5,0.5,0,0,1,1,0]
recall
0.44375 [0.5,0,0.5,0.5,1,0,0,0,0,1,0.5,0.5,0,0,0,1,0.5,0.5,0,0.5,0.5,1,0,1,1,0,0,1,0,0.5,0,0,0,0,0,1,0.5,0,0.5,1,0.5,1,1,0,0,1,1,1,0.5,1,0,0,0.5,0,0.5,0,1,0,0.5,0,1,1,0,1,0.5,1,0,0,0,0,0,0.5,1,0,0.5,0,0.5,0.5,0.5,1,0,1,0,0.5,0,0,1,0,1,0.5,1,0,0,1,0,0,0.5,1,0,0.5]
recall
0.44375 [0,1,0.5,1,1,0.5,1,0,1,0.5,0.5,1,0,0,0,0.5,0.5,0,0,0,0.5,0.5,0.5,1,0.5,0.5,0,0,1,0.5,1,1,0.5,0.5,0,0.5,0,0,0,0,0.5,1,0,0,0,1,0.5,0.5,1,0.5,0,1,0,0,0,0.5,1,0.5,0,0,1,0.5,1,0,1,0,0,1,0.5,0.5,0,0,1,1,0.5,0,1,0,1,0,1,0.5,0,0.5,0,1,1,1,0,0,1,0,0,1,0.5,1,0.5,1,0,0.5]
recall
0.49375 [1,0,0,0.5,1,1,1,0.5,1,1,1,1,1,1,1,0,1,0,0.5,0,0.5,0,0,1,0,0,0,0.5,0,0,0.5,0,1,0,0.5,0.5,0.5,1,1,1,0,0,1,0,0,0.5,0,0.5,1,1,0,0,1,0,0.5,0.5,1,0.5,0,0,0,1,1,0,1,0,0,0.5,0.5,0.5,0,1,1,1,0.5,0,1,0,1,0,0.5,0,1,0.5,1,0,1,0,0,0.5,1,1,0,0,0,0,1,0,0,1]
recall
0.475 [0.5,1,0,0.5,0,0.5,1,0.5,0,1,0,1,0.5,1,0,0.5,1,0,0.5,1,0,0,0,1,1,0,1,0.5,0,0,0.5,1,1,1,0.5,0.5,0,0,0.5,1,0,1,1,0.5,0,0.5,1,0,0,1,1,0.5,0,1,0.5,0,1,1,0,0,0.5,0.5,1,1,0.5,0,0,0,0,0.5,0,1,0,1,0.5,1,1,1,0,1,0,0,0.5,0,0,0,1,0,1,1,0,0.5,1,0,1,0.5,0.5,0,0,0.5]
recall
0.45625 [0,1,1,1,1,1,0,1,0.5,1,0,0,0,0.5,0.5,1,1,0,0,0,1,1,0,0.5,1,0,0,0.5,0.5,1,0.5,1,0,0,1,1,0,0,0.5,0,0,0,0,0,0,0.5,1,1,0,1,0.5,0.5,0.5,0.5,0,0,1,0,0.5,0,0.5,0,0.5,0,0,0,0,1,0,0,1,0,0,0.5,0.5,0,1,0,1,0.5,0,1,1,0,1,0.5,1,0.5,0,1,1,0.5,1,0.5,0,0.5,0,0.5,0,1]
recall
0.425 [0,0.5,0,0.5,1,1,1,1,0.5,1,1,1,0.5,0.5,1,0,1,0,0,0,0,0,0,1,0,0,0,0.5,0,1,0.5,1,1,0,0.5,0.5,0.5,0.5,0,0,0,0,0,0.5,0.5,0.5,1,0.5,0,0,0.5,0.5,0.5,0.5,0.5,0,1,0,0.5,0,1,1,0,0.5,1,0,0,0,0,0,0,1,0,0,0.5,0.5,1,0,1,0,0.5,0,1,0,1,0.5,0,0,1,0,1,1,0.5,0,0,1,0,0.5,0,1]
relative_absolute_error
0.590657501168864
relative_absolute_error
0.5754784462170816
relative_absolute_error
0.62480228105228
relative_absolute_error
0.6022292101837547
relative_absolute_error
0.6074843366510025
relative_absolute_error
0.6176896721404287
relative_absolute_error
0.5673878064976539
relative_absolute_error
0.5960395174410319
relative_absolute_error
0.6035869118255471
relative_absolute_error
0.6257690646895185
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
0.09165774625466784
root_mean_squared_error
0.08911242419051243
root_mean_squared_error
0.09187285459687641
root_mean_squared_error
0.09015256099356123
root_mean_squared_error
0.0913736894602902
root_mean_squared_error
0.09182063465321705
root_mean_squared_error
0.08835727817978106
root_mean_squared_error
0.09016726096548602
root_mean_squared_error
0.0927992273591295
root_mean_squared_error
0.09485494942019562
root_relative_squared_error
0.9211950104737454
root_relative_squared_error
0.8956135612088473
root_relative_squared_error
0.9233569306567188
root_relative_squared_error
0.9060673294099157
root_relative_squared_error
0.918340132273437
root_relative_squared_error
0.922832100475835
root_relative_squared_error
0.8880240582405756
root_relative_squared_error
0.9062150696865925
root_relative_squared_error
0.9326673272276237
root_relative_squared_error
0.9533281113179641
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
101.77267600010964
usercpu_time_millis
77.18336200014164
usercpu_time_millis
80.7915749996937
usercpu_time_millis
79.6530139996321
usercpu_time_millis
60.142099000131566
usercpu_time_millis
56.97177899992312
usercpu_time_millis
56.829711999853316
usercpu_time_millis
54.95950900012758
usercpu_time_millis
53.96747499980847
usercpu_time_millis
55.460294000567956
usercpu_time_millis_testing
1.7554890000610612
usercpu_time_millis_testing
1.731514999846695
usercpu_time_millis_testing
1.7302609999205742
usercpu_time_millis_testing
1.724067999930412
usercpu_time_millis_testing
1.3282019999678596
usercpu_time_millis_testing
1.2701680002464855
usercpu_time_millis_testing
1.2511290001384623
usercpu_time_millis_testing
1.2512640000750253
usercpu_time_millis_testing
1.2486569999055064
usercpu_time_millis_testing
1.2522370002443495
usercpu_time_millis_training
100.01718700004858
usercpu_time_millis_training
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