10104409
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)
8029621
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
1
8783
min_samples_split
6
8783
min_weight_fraction_leaf
0.0
8783
presort
false
8783
random_state
45406
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
21129356
description
https://api.openml.org/data/download/21129356/description.xml
-1
21129357
predictions
https://api.openml.org/data/download/21129357/predictions.arff
area_under_roc_curve
0.7520132970328279 [0.746232,0.841166,0.874428,0.843316,0.841264,0.65337,0.747199,0.810626,0.653291,0.842862,0.810271,0.809935,0.714193,0.681601,0.8416,0.680674,0.905934,0.588995,0.651219,0.648615,0.747139,0.841797,0.684403,0.999684,0.747633,0.584931,0.587279,0.80962,0.842981,0.810922,0.747593,0.936395,0.746528,0.55451,0.840199,0.778468,0.713206,0.682607,0.905185,0.935527,0.683811,0.809304,0.8416,0.746922,0.780204,0.716106,0.874033,0.685409,0.651278,0.842369,0.682331,0.681739,0.808594,0.645163,0.745896,0.554253,0.999684,0.935054,0.651259,0.744279,0.748895,0.71437,0.68387,0.622435,0.810764,0.747001,0.587812,0.842704,0.587121,0.589153,0.682232,0.841501,0.714469,0.841481,0.488952,0.873422,0.841876,0.613262,0.812263,0.779297,0.778212,0.620423,0.713739,0.683791,0.805674,0.811316,0.810567,0.743746,0.715495,0.778153,0.810211,0.967113,0.777423,0.71293,0.779908,0.716757,0.776495,0.682173,0.584734,0.746903]
average_cost
0
f_measure
0.47104398987643087 [0.484848,0.564103,0.774194,0.709677,0.594595,0.344828,0.516129,0.580645,0.322581,0.758621,0.580645,0.580645,0.30303,0.315789,0.647059,0.228571,0.866667,0.181818,0.294118,0.190476,0.484848,0.647059,0.387097,0.969697,0.451613,0.153846,0.117647,0.555556,0.666667,0.645161,0.451613,0.777778,0.533333,0.064516,0.594595,0.516129,0.424242,0.222222,0.764706,0.727273,0.461538,0.512821,0.564103,0.470588,0.62069,0.411765,0.709677,0.428571,0.3125,0.645161,0.285714,0.333333,0.470588,0.15,0.484848,0.125,0.969697,0.702703,0.285714,0.368421,0.592593,0.375,0.375,0.272727,0.645161,0.5,0.2,0.733333,0.222222,0.25,0.375,0.580645,0.387097,0.645161,0,0.62069,0.645161,0.0625,0.769231,0.6,0.5625,0.235294,0.4375,0.285714,0.444444,0.692308,0.645161,0.4,0.413793,0.486486,0.580645,0.810811,0.5,0.222222,0.538462,0.444444,0.424242,0.363636,0,0.457143]
kappa
0.4659090909090909
kb_relative_information_score
791.9343479644814
mean_absolute_error
0.010659999999999841
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
0.48319930593254745 [0.470588,0.478261,0.8,0.733333,0.52381,0.384615,0.533333,0.6,0.333333,0.846154,0.6,0.6,0.294118,0.272727,0.611111,0.210526,0.928571,0.176471,0.277778,0.153846,0.470588,0.611111,0.4,0.941176,0.466667,0.130435,0.111111,0.5,0.818182,0.666667,0.466667,0.7,0.571429,0.066667,0.52381,0.533333,0.411765,0.272727,0.722222,0.705882,0.6,0.434783,0.478261,0.444444,0.692308,0.388889,0.733333,0.5,0.3125,0.666667,0.263158,0.3,0.444444,0.125,0.470588,0.125,0.941176,0.619048,0.263158,0.318182,0.727273,0.375,0.375,0.5,0.666667,0.5,0.214286,0.785714,0.272727,0.375,0.375,0.6,0.4,0.666667,0,0.692308,0.666667,0.0625,1,0.642857,0.5625,0.222222,0.4375,0.333333,0.4,0.9,0.666667,0.368421,0.461538,0.428571,0.6,0.714286,0.583333,0.272727,0.7,0.545455,0.411765,0.352941,0,0.421053]
predictive_accuracy
0.47125
prior_entropy
6.6438561897747395
recall
0.47125 [0.5,0.6875,0.75,0.6875,0.6875,0.3125,0.5,0.5625,0.3125,0.6875,0.5625,0.5625,0.3125,0.375,0.6875,0.25,0.8125,0.1875,0.3125,0.25,0.5,0.6875,0.375,1,0.4375,0.1875,0.125,0.625,0.5625,0.625,0.4375,0.875,0.5,0.0625,0.6875,0.5,0.4375,0.1875,0.8125,0.75,0.375,0.625,0.6875,0.5,0.5625,0.4375,0.6875,0.375,0.3125,0.625,0.3125,0.375,0.5,0.1875,0.5,0.125,1,0.8125,0.3125,0.4375,0.5,0.375,0.375,0.1875,0.625,0.5,0.1875,0.6875,0.1875,0.1875,0.375,0.5625,0.375,0.625,0,0.5625,0.625,0.0625,0.625,0.5625,0.5625,0.25,0.4375,0.25,0.5,0.5625,0.625,0.4375,0.375,0.5625,0.5625,0.9375,0.4375,0.1875,0.4375,0.375,0.4375,0.375,0,0.5]
relative_absolute_error
0.5383838383838294
root_mean_prior_squared_error
0.09949874371066209
root_mean_squared_error
0.09641933156789631
root_relative_squared_error
0.9690507434775201
total_cost
0
area_under_roc_curve
0.7532100847862433 [0.996855,0.745253,1,0.5,0.75,0.996855,0.5,1,0.75,1,0.746835,0.748418,0.493671,0.5,1,0.484277,1,0.496835,0.5,0.496855,0.996855,0.493711,0.5,1,0.496855,0.493671,0.493671,1,0.75,0.5,0.996835,1,0.746835,0.493671,1,0.490566,0.487421,0.496855,1,1,0.484277,0.5,0.75,0.996835,1,0.75,1,1,0.493671,0.75,0.75,0.493671,0.990566,0.493671,1,0.484277,0.996835,0.996855,0.984277,0.743671,0.496855,0.996855,0.75,0.5,1,0.748418,0.5,1,0.496855,0.496855,0.746835,1,0.746835,0.745253,0.490566,1,0.75,0.985759,0.75,0.745253,1,0.5,0.996855,1,0.746835,0.75,0.993671,0.742089,0.75,0.496855,0.740506,1,0.996835,0.748418,0.996835,0.490506,1,0.490506,0.493671,1]
area_under_roc_curve
0.7271014947058351 [1,1,0.75,1,0.742089,0.496855,0.748418,0.996855,0.75,1,0.5,0.75,0.496835,0.745253,1,0.996855,1,0.5,0.490506,0.993711,1,0.493711,0.490566,1,0.5,0.735759,0.496835,0.496835,0.998418,0.5,0.493671,1,0.748418,0.490506,0.745253,0.996855,0.490566,0.496855,1,0.996835,0.496855,1,1,0.745253,0.748418,0.745253,0.996855,0.493711,0.481013,1,0.742089,0.484177,0.996855,0.995253,1,0.493711,1,1,0.990566,0.746835,1,0.993711,0.75,0.496835,1,0.496835,0.493671,0.5,0.490566,0.496855,0.734177,1,0.748418,1,0.487421,0.746835,0.740506,0.481013,0.75,0.75,0.746835,0.493671,0.484277,0.5,0.738924,0.75,0.496835,0.477848,0.746835,0.5,0.496835,1,0.745253,0.75,0.75,0.746835,1,0.496835,0.742089,0.5]
area_under_roc_curve
0.7241939336040125 [0.496835,0.746835,0.740506,1,0.75,0.493671,0.5,1,0.743671,0.745253,0.748418,0.75,1,0.5,0.5,0.490506,1,0.490506,0.493711,0.493671,0.5,1,0.737342,1,0.496855,0.748418,0.748418,0.996855,1,0.996835,0.493711,0.993671,0.746835,0.484177,0.496855,0.493711,0.996855,0.493711,1,1,0.5,1,1,0.996855,0.496835,0.493711,0.746835,0.993711,0.745253,0.75,0.487342,0.996855,0.496855,0.487342,0.496855,0.745253,1,0.993671,0.996855,0.496835,0.5,0.496855,0.493671,1,0.746835,0.748418,0.5,0.746835,0.493711,0.5,0.735759,0.995253,0.496855,0.745253,0.496855,1,0.996835,0.490506,0.75,1,0.496855,0.496835,0.748418,1,0.484277,0.493711,1,0.745253,0.748418,0.996855,1,0.996855,0.496855,0.740506,0.75,1,0.487342,0.740506,0.493711,0.745253]
area_under_roc_curve
0.7714260657989014 [0.742089,0.996835,1,1,0.75,0.493671,0.996855,0.745253,0.5,0.75,0.746835,0.998418,0.493711,1,0.996835,0.995253,0.746835,0.740506,0.493711,0.487342,0.496855,1,0.5,1,0.496855,0.748418,0.748418,1,1,0.746835,0.996855,1,0.746835,0.493671,0.996855,0.496855,1,0.993711,0.496855,1,0.748418,0.993711,1,0.5,1,1,0.745253,0.996855,0.745253,0.996835,0.996835,1,0.996855,0.493671,0.996855,0.5,1,1,0.487421,0.998418,1,0.496855,0.740506,0.5,0.746835,0.996835,0.737342,1,0.487421,0.743671,0.5,0.490506,0.496855,0.746835,0.484277,0.748418,0.75,0.484177,1,0.75,0.496855,0.5,1,0.737342,0.993711,0.5,1,1,0.493671,0.984277,0.746835,1,0.5,0.490506,1,0.5,0.5,0.75,0.977987,0.487342]
area_under_roc_curve
0.7306815241620888 [0.745253,1,0.75,0.75,0.496855,0.75,0.490566,0.496835,0.5,0.75,0.996835,0.995253,1,0.481132,0.996855,0.496835,0.75,0.75,0.996855,0.996835,0.493671,0.746835,0.5,0.996835,1,0.493671,0.484177,1,1,0.746835,0.496855,1,0.5,0.5,0.987421,0.996835,0.746835,0.496835,0.75,0.990506,0.746835,0.75,0.5,0.996855,1,0.493711,1,0.5,0.75,0.998418,0.490566,0.496855,0.75,0.993711,0.496835,0.477848,1,0.745253,0.746835,0.493711,0.748418,0.748418,1,0.5,0.75,0.493671,0.490566,0.748418,0.493671,0.484177,0.746835,0.996835,1,0.5,0.484177,1,0.746835,0.735759,0.75,0.496855,0.493711,0.996835,0.487342,0.737342,0.5,0.996855,0.5,1,1,0.746835,0.496855,1,0.996855,0.996855,0.748418,0.5,0.745253,0.996855,0.493711,0.496835]
area_under_roc_curve
0.739878517832975 [0.75,1,1,1,0.996855,0.5,1,0.75,0.996855,0.75,0.993671,0.742089,0.993711,0.993711,1,0.748418,1,0.740506,0.490566,0.487342,0.75,0.743671,0.75,1,0.742089,0.481013,0.493671,0.996855,1,0.75,1,1,0.745253,0.496835,0.496855,0.75,0.5,0.740506,1,1,0.745253,0.745253,1,0.996855,0.5,1,1,0.5,0.487342,0.746835,0.993711,0.993711,0.740506,0.484277,0.738924,0.493671,1,1,0.496835,0.996855,0.746835,0.496835,0.496855,1,0.748418,0.75,0.490566,1,0.496835,0.748418,0.493671,0.740506,0.493711,0.996855,0.490506,0.996855,0.75,0.484177,0.75,0.5,0.490566,0.490506,0.746835,0.493671,0.496855,1,0.5,0.5,0.5,0.996835,1,0.996835,0.496855,0.493711,0.496835,1,0.987342,0.493711,0.493711,0.75]
area_under_roc_curve
0.771682812873179 [0.748418,0.496855,1,1,1,0.996835,0.75,1,0.496855,0.745253,1,0.996855,0.743671,0.484277,0.5,0.748418,0.5,0.496855,0.493671,0.742089,0.745253,1,0.998418,1,0.745253,0.490566,0.487421,0.745253,0.496855,1,0.75,0.5,1,0.493711,1,0.5,0.990506,0.75,0.746835,0.5,0.493671,0.993671,0.746835,0.75,0.496855,0.745253,0.5,0.75,1,1,0.496855,0.746835,1,0.484277,0.745253,0.742089,1,0.745253,0.746835,0.984277,1,0.740506,1,0.496835,0.746835,0.996855,0.496855,0.996835,0.743671,0.493671,1,1,0.740506,1,0.487342,0.996855,1,0.5,1,1,0.995253,0.996855,0.742089,0.5,1,0.746835,0.748418,0.487421,1,0.5,0.996855,0.996835,0.493671,0.487421,0.5,0.748418,1,0.496855,0.493671,0.998418]
area_under_roc_curve
0.7561573272430535 [1,0.993711,1,0.5,0.996855,0.5,0.996835,1,0.5,0.998418,1,0.5,0.745253,0.496855,0.496855,0.487342,1,0.490566,0.993671,0.493671,0.496835,0.75,0.75,1,0.748418,0.493711,0.493711,0.75,0.996855,0.746835,0.745253,0.996855,1,0.996855,0.746835,1,0.746835,1,1,0.996855,1,0.740506,0.993671,0.5,1,0.745253,1,1,0.493711,0.5,0.487421,0.496835,0.493671,0.996855,0.746835,0.5,1,0.998418,0.496835,0.996855,0.5,0.745253,0.996855,0.748418,0.75,0.993711,0.496855,0.75,0.493671,0.493671,0.496855,0.75,0.996835,0.493711,0.490506,1,1,0.981132,1,0.493711,0.496835,0.487421,0.493671,0.75,0.727848,0.748418,1,0.493711,0.993711,0.745253,0.5,0.996835,0.746835,0.993711,0.5,0.75,0.993671,0.496855,0.496835,0.748418]
area_under_roc_curve
0.7844196570734816 [0.496855,1,1,1,0.996835,0.996855,0.746835,0.5,0.743671,1,0.496855,1,0.993671,0.746835,0.996835,0.496855,1,0.496855,1,0.496855,0.998418,1,0.993711,1,0.75,0.484277,0.493711,0.746835,0.75,1,1,1,0.487421,0.987421,0.993671,1,0.746835,0.75,0.996835,0.5,0.5,0.75,0.75,0.496835,0.493671,0.75,1,0.496835,0.5,1,0.75,0.737342,0.75,0.732595,0.748418,0.496855,1,0.996855,0.496835,0.490506,0.5,0.748418,0.490506,0.490506,1,0.993711,0.746835,0.5,0.484177,0.993711,0.993711,1,0.746835,1,0.490506,0.745253,0.996855,0.5,1,0.748418,1,0.996855,0.5,0.493711,0.996835,1,0.75,0.748418,0.496855,0.75,1,0.75,1,0.745253,0.996855,0.746835,0.487421,0.995253,0.493671,1]
area_under_roc_curve
0.7618730594697873 [0.493711,0.496835,0.496855,0.75,1,0.493711,0.745253,0.493711,0.487342,1,0.996855,0.5,0.496835,0.746835,0.746835,1,1,0.5,0.493671,1,1,0.996835,0.5,1,1,0.484277,0.987421,0.746835,0.5,0.996855,0.5,0.75,1,0.481132,0.746835,0.748418,0.487342,0.487342,1,1,0.993711,0.748418,0.75,0.746835,1,0.5,1,0.5,1,0.496855,0.5,0.748418,0.996835,0.490506,0.748418,0.487421,1,0.996855,0.496835,0.743671,1,0.746835,0.490506,0.75,0.996855,0.5,0.742089,0.996855,0.996835,0.5,0.490566,0.496855,0.496835,0.996835,0.487342,0.75,1,0.493711,0.5,0.993671,0.996835,0.496855,1,0.496855,0.988924,1,0.996835,0.984177,0.487421,0.996835,1,0.996835,0.996835,0.738924,1,0.75,0.496855,0.746835,0.734177,0.996855]
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
0.49486977111286506
kappa
0.40008682953783004
kappa
0.4063782759709504
kappa
0.48845470692717585
kappa
0.4253236501420903
kappa
0.4314592545799116
kappa
0.5073230429118472
kappa
0.4633414884381659
kappa
0.5452033162258193
kappa
0.49463044851547694
kb_relative_information_score
80.55162133892087
kb_relative_information_score
71.11064584741534
kb_relative_information_score
70.89547907857798
kb_relative_information_score
84.24080701418383
kb_relative_information_score
72.79778389265249
kb_relative_information_score
74.93466486925114
kb_relative_information_score
84.75482137598405
kb_relative_information_score
80.45174375029414
kb_relative_information_score
89.62705035075706
kb_relative_information_score
82.56973044644809
mean_absolute_error
0.01021458333333334
mean_absolute_error
0.011702083333333339
mean_absolute_error
0.011589583333333342
mean_absolute_error
0.010275000000000003
mean_absolute_error
0.011325000000000005
mean_absolute_error
0.011279166666666673
mean_absolute_error
0.01018541666666667
mean_absolute_error
0.010489583333333339
mean_absolute_error
0.009312500000000005
mean_absolute_error
0.010227083333333338
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
0.5
predictive_accuracy
0.40625
predictive_accuracy
0.4125
predictive_accuracy
0.49375
predictive_accuracy
0.43125
predictive_accuracy
0.4375
predictive_accuracy
0.5125
predictive_accuracy
0.46875
predictive_accuracy
0.55
predictive_accuracy
0.5
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
0.5 [1,0.5,1,0,0.5,1,0,1,0.5,1,0.5,0.5,0,0,1,0,1,0,0,0,1,0,0,1,0,0,0,1,0.5,0,1,1,0.5,0,1,0,0,0,1,1,0,0,0.5,1,1,0.5,1,1,0,0.5,0.5,0,1,0,1,0,1,1,1,0.5,0,1,0.5,0,1,0.5,0,1,0,0,0.5,1,0.5,0.5,0,1,0.5,0.5,0.5,0.5,1,0,1,1,0.5,0.5,1,0.5,0.5,0,0.5,1,1,0.5,0.5,0,1,0,0,1]
recall
0.40625 [1,1,0.5,1,0.5,0,0.5,1,0.5,1,0,0.5,0,0.5,1,1,1,0,0,1,1,0,0,1,0,0.5,0,0,0.5,0,0,1,0.5,0,0.5,1,0,0,1,1,0,1,1,0.5,0.5,0.5,1,0,0,1,0,0,1,0.5,1,0,1,1,1,0.5,1,1,0.5,0,1,0,0,0,0,0,0.5,1,0.5,0.5,0,0.5,0,0,0.5,0.5,0.5,0,0,0,0.5,0,0,0,0,0,0,1,0.5,0,0.5,0.5,1,0,0,0]
recall
0.4125 [0,0.5,0.5,1,0.5,0,0,1,0.5,0.5,0.5,0.5,1,0,0,0,1,0,0,0,0,1,0.5,1,0,0.5,0.5,1,1,1,0,1,0.5,0,0,0,1,0,1,1,0,1,1,1,0,0,0.5,1,0.5,0.5,0,1,0,0,0,0.5,1,0.5,1,0,0,0,0,1,0.5,0.5,0,0.5,0,0,0.5,0.5,0,0.5,0,0,1,0,0.5,1,0,0,0.5,1,0,0,1,0.5,0.5,1,0.5,1,0,0,0,1,0,0.5,0,0.5]
recall
0.49375 [0.5,1,1,1,0.5,0,1,0,0,0.5,0,0.5,0,1,1,0.5,0.5,0.5,0,0,0,1,0,1,0,0.5,0.5,1,0.5,0.5,1,1,0.5,0,1,0,1,0,0,1,0.5,1,1,0,1,1,0.5,1,0.5,1,1,1,0,0,1,0,1,1,0,1,1,0,0.5,0,0.5,1,0.5,1,0,0.5,0,0,0,0.5,0,0.5,0.5,0,1,0.5,0,0,1,0,1,0,1,1,0,1,0.5,1,0,0,1,0,0,0.5,0,0]
recall
0.43125 [0.5,1,0.5,0.5,0,0.5,0,0,0,0.5,1,1,1,0,1,0,0.5,0.5,1,1,0,0.5,0,1,1,0,0,1,1,0.5,0,1,0,0,1,1,0.5,0,0.5,1,0.5,0.5,0,1,1,0,1,0,0.5,0.5,0,0,0.5,0,0,0,1,0.5,0.5,0,0.5,0.5,1,0,0.5,0,0,0.5,0,0,0.5,0.5,1,0,0,1,0.5,0,0.5,0,0,1,0,0,0,1,0,1,1,0.5,0,1,0,1,0.5,0,0.5,1,0,0]
recall
0.4375 [0.5,1,1,1,1,0,1,0.5,1,0.5,1,0.5,0,1,1,0.5,1,0.5,0,0,0.5,0.5,0.5,1,0.5,0,0,1,1,0.5,1,1,0.5,0,0,0,0,0.5,1,0,0.5,0.5,1,1,0,1,1,0,0,0.5,1,1,0.5,0,0.5,0,1,1,0,1,0.5,0,0,0,0.5,0.5,0,1,0,0.5,0,0.5,0,1,0,0,0.5,0,0.5,0,0,0,0.5,0,0,1,0,0,0,1,1,1,0,0,0,0,0.5,0,0,0.5]
recall
0.5125 [0.5,0,1,1,1,1,0.5,1,0,0.5,1,1,0.5,0,0,0,0,0,0,0,0.5,1,1,1,0,0,0,0.5,0,1,0.5,0,1,0,1,0,1,0.5,0.5,0,0,1,0.5,0.5,0,0.5,0,0.5,1,1,0,0.5,0.5,0,0.5,0.5,1,0.5,0.5,0,1,0.5,1,0,0.5,1,0,1,0.5,0,1,1,0,1,0,1,1,0,1,1,1,1,0.5,0,1,0.5,0.5,0,1,0,1,1,0,0,0,0.5,1,0,0,1]
recall
0.46875 [1,1,1,0,1,0,1,1,0,1,1,0,0,0,0,0,1,0,1,0,0,0.5,0.5,1,0.5,0,0,0.5,1,0.5,0,1,1,1,0.5,1,0.5,0.5,1,1,1,0.5,1,0,1,0.5,1,1,0,0,0,0,0,1,0.5,0,1,1,0,1,0,0.5,1,0.5,0.5,1,0,0.5,0,0,0,0.5,1,0,0,1,1,0,1,0,0,0,0,0.5,0,0.5,1,0,1,0.5,0,1,0,0,0,0.5,0.5,0,0,0.5]
recall
0.55 [0,1,1,1,1,1,0.5,0,0.5,1,0,1,1,0.5,1,0,1,0,1,0,1,1,1,1,0.5,0,0,0.5,0.5,1,1,1,0,0,1,1,0.5,0,1,0,0,0.5,0.5,0,0,0.5,1,0,0,1,0.5,0.5,0.5,0.5,0.5,0,1,1,0,0,0,0.5,0,0,1,1,0.5,0,0,1,1,1,0.5,1,0,0.5,1,0,1,0.5,1,1,0,0,0.5,1,0.5,0.5,0,0.5,1,0.5,1,0,1,0.5,0,1,0,1]
recall
0.5 [0,0,0,0.5,1,0,0.5,0,0,1,1,0,0,0.5,0.5,1,1,0,0,1,1,1,0,1,1,0,0,0.5,0,1,0,0.5,1,0,0.5,0.5,0,0,1,1,1,0.5,0.5,0.5,1,0,0,0,1,0,0,0.5,1,0,0.5,0,1,1,0,0.5,1,0,0,0.5,1,0,0.5,1,1,0,0,0,0,1,0,0.5,1,0,0,1,1,0,1,0,1,1,1,0.5,0,1,1,1,1,0.5,1,0.5,0,0.5,0,1]
relative_absolute_error
0.5158880471380466
relative_absolute_error
0.5910143097643091
relative_absolute_error
0.585332491582491
relative_absolute_error
0.5189393939393931
relative_absolute_error
0.5719696969696962
relative_absolute_error
0.5696548821548816
relative_absolute_error
0.5144149831649826
relative_absolute_error
0.5297769360269354
relative_absolute_error
0.47032828282828226
relative_absolute_error
0.5165193602693596
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
0.09530597655271504
root_mean_squared_error
0.0997684819970716
root_mean_squared_error
0.10078442339965044
root_mean_squared_error
0.09267644582692577
root_mean_squared_error
0.1004090591862441
root_mean_squared_error
0.09900021043748679
root_mean_squared_error
0.09381590276233083
root_mean_squared_error
0.09718199564619869
root_mean_squared_error
0.09138707360574702
root_mean_squared_error
0.09329035468781208
root_relative_squared_error
0.9578611045568637
root_relative_squared_error
1.0027109717806482
root_relative_squared_error
1.0129215670574403
root_relative_squared_error
0.9314333263988215
root_relative_squared_error
1.0091490147677564
root_relative_squared_error
0.9949895520829389
root_relative_squared_error
0.9428852994882361
root_relative_squared_error
0.9767158058678573
root_relative_squared_error
0.9184746479965274
root_relative_squared_error
0.9376033426019558
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
275.9136259992374
usercpu_time_millis
258.14370999978564
usercpu_time_millis
232.7463670008001
usercpu_time_millis
183.01114900077664
usercpu_time_millis
181.22923000009905
usercpu_time_millis
180.97862800004805
usercpu_time_millis
183.35171800026728
usercpu_time_millis
187.53217499943275
usercpu_time_millis
188.96506700002647
usercpu_time_millis
183.3388200002446
usercpu_time_millis_testing
1.8699789998208871
usercpu_time_millis_testing
1.8570440006442368
usercpu_time_millis_testing
1.3590970002042013
usercpu_time_millis_testing
1.350207000541559
usercpu_time_millis_testing
1.3433869999062154
usercpu_time_millis_testing
1.3437979996524518
usercpu_time_millis_testing
1.3402940003288677
usercpu_time_millis_testing
1.3422239999272279
usercpu_time_millis_testing
1.3564090004365426
usercpu_time_millis_testing
1.3453240007947898
usercpu_time_millis_training
274.0436469994165
usercpu_time_millis_training
256.2866659991414
usercpu_time_millis_training
231.3872700005959
usercpu_time_millis_training
181.66094200023508
usercpu_time_millis_training
179.88584300019284
usercpu_time_millis_training
179.6348300003956
usercpu_time_millis_training
182.01142399993842
usercpu_time_millis_training
186.18995099950553
usercpu_time_millis_training
187.60865799958992
usercpu_time_millis_training
181.9934959994498