10087321
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)
8012389
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
2
8783
min_samples_split
7
8783
min_weight_fraction_leaf
0.0
8783
presort
false
8783
random_state
25859
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
21095178
description
https://api.openml.org/data/download/21095178/description.xml
-1
21095179
predictions
https://api.openml.org/data/download/21095179/predictions.arff
area_under_roc_curve
0.7623845880681819 [0.745403,0.871824,0.874724,0.842645,0.873737,0.746922,0.746705,0.811119,0.77837,0.842902,0.809639,0.778587,0.713246,0.712101,0.873067,0.71224,0.905875,0.557252,0.681029,0.680398,0.746607,0.841126,0.744949,0.99998,0.778606,0.521662,0.619673,0.810113,0.810192,0.779849,0.841027,0.873658,0.747534,0.585208,0.808337,0.873501,0.712318,0.712161,0.966619,0.90408,0.746705,0.840041,0.842073,0.746982,0.810488,0.682351,0.780106,0.685034,0.682489,0.84231,0.804806,0.651199,0.840061,0.6759,0.745896,0.582051,0.905934,0.809403,0.68172,0.681147,0.748441,0.775568,0.682962,0.65331,0.81033,0.777738,0.615747,0.873836,0.616675,0.58722,0.647274,0.840968,0.683712,0.840495,0.485795,0.810646,0.87358,0.614169,0.873836,0.872593,0.840949,0.619752,0.682114,0.712851,0.805279,0.810863,0.841501,0.741852,0.714173,0.777048,0.873343,0.905362,0.776555,0.6802,0.873382,0.810941,0.742799,0.682489,0.645084,0.745344]
average_cost
0
f_measure
0.46957113385494786 [0.421053,0.564103,0.827586,0.647059,0.666667,0.457143,0.516129,0.666667,0.5,0.758621,0.5,0.533333,0.25,0.325581,0.705882,0.30303,0.866667,0.129032,0.307692,0.285714,0.387097,0.611111,0.410256,0.9375,0.5,0.0625,0.285714,0.571429,0.580645,0.6,0.571429,0.705882,0.571429,0.142857,0.473684,0.642857,0.4375,0.2,0.736842,0.709677,0.5,0.512821,0.647059,0.457143,0.606061,0.315789,0.571429,0.4,0.37037,0.666667,0.372093,0.357143,0.5,0.1875,0.424242,0.15,0.866667,0.580645,0.30303,0.3125,0.551724,0.388889,0.342857,0.347826,0.606061,0.428571,0.181818,0.8,0.307692,0.206897,0.25,0.551724,0.413793,0.5625,0,0.580645,0.709677,0.129032,0.769231,0.580645,0.588235,0.2,0.344828,0.294118,0.378378,0.64,0.580645,0.277778,0.461538,0.461538,0.666667,0.774194,0.482759,0.214286,0.689655,0.538462,0.342857,0.344828,0.066667,0.428571]
kappa
0.46148989898989895
kb_relative_information_score
809.9684864859614
mean_absolute_error
0.01083458333333319
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
0.4864565542256014 [0.363636,0.478261,0.923077,0.611111,0.6,0.421053,0.533333,0.818182,0.5,0.846154,0.5,0.571429,0.25,0.259259,0.666667,0.294118,0.928571,0.133333,0.26087,0.230769,0.4,0.55,0.347826,0.9375,0.5,0.0625,0.333333,0.526316,0.6,0.642857,0.526316,0.666667,0.666667,0.166667,0.409091,0.75,0.4375,0.214286,0.636364,0.733333,0.583333,0.434783,0.611111,0.421053,0.588235,0.272727,0.666667,0.428571,0.454545,0.714286,0.296296,0.416667,0.5,0.1875,0.411765,0.125,0.928571,0.6,0.294118,0.3125,0.615385,0.35,0.315789,0.571429,0.588235,0.5,0.176471,0.857143,0.4,0.230769,0.25,0.615385,0.461538,0.5625,0,0.6,0.733333,0.133333,1,0.6,0.555556,0.214286,0.384615,0.277778,0.333333,0.888889,0.6,0.25,0.6,0.391304,0.714286,0.8,0.538462,0.25,0.769231,0.7,0.315789,0.384615,0.071429,0.5]
predictive_accuracy
0.466875
prior_entropy
6.6438561897747395
recall
0.466875 [0.5,0.6875,0.75,0.6875,0.75,0.5,0.5,0.5625,0.5,0.6875,0.5,0.5,0.25,0.4375,0.75,0.3125,0.8125,0.125,0.375,0.375,0.375,0.6875,0.5,0.9375,0.5,0.0625,0.25,0.625,0.5625,0.5625,0.625,0.75,0.5,0.125,0.5625,0.5625,0.4375,0.1875,0.875,0.6875,0.4375,0.625,0.6875,0.5,0.625,0.375,0.5,0.375,0.3125,0.625,0.5,0.3125,0.5,0.1875,0.4375,0.1875,0.8125,0.5625,0.3125,0.3125,0.5,0.4375,0.375,0.25,0.625,0.375,0.1875,0.75,0.25,0.1875,0.25,0.5,0.375,0.5625,0,0.5625,0.6875,0.125,0.625,0.5625,0.625,0.1875,0.3125,0.3125,0.4375,0.5,0.5625,0.3125,0.375,0.5625,0.625,0.75,0.4375,0.1875,0.625,0.4375,0.375,0.3125,0.0625,0.375]
relative_absolute_error
0.5472011784511701
root_mean_prior_squared_error
0.09949874371066209
root_mean_squared_error
0.09453304463402058
root_relative_squared_error
0.9500928464877755
total_cost
0
area_under_roc_curve
0.7653749701456886 [1,0.990506,1,0.496855,0.75,0.996855,0.5,1,0.75,1,0.996835,0.75,0.737342,0.75,1,0.484277,1,0.496835,0.493671,0.496855,0.996855,0.496855,0.487421,1,0.493711,0.493671,0.496835,1,0.75,0.5,1,1,0.746835,0.484177,1,0.487421,0.484277,0.490566,1,1,0.493711,0.496855,0.75,0.996835,0.996835,0.75,1,1,0.496835,0.75,0.748418,0.493671,0.993711,0.742089,0.996855,0.481132,0.746835,0.996855,0.993711,0.742089,0.496855,0.996855,0.75,0.496835,1,0.75,0.5,1,0.493711,0.496855,0.743671,1,0.746835,0.746835,0.490566,1,0.75,0.743671,0.746835,0.996835,1,0.5,0.993711,0.996855,0.745253,0.748418,1,0.746835,0.743671,0.493711,0.735759,1,0.996835,0.75,1,0.493671,0.996855,0.493671,0.493671,1]
area_under_roc_curve
0.7453588985749542 [1,1,0.75,1,0.996835,1,0.496835,1,0.748418,1,0.5,0.75,0.493671,0.746835,1,0.996855,1,0.493671,0.493671,0.996855,1,0.490566,0.990566,1,1,0.490506,0.493671,0.496835,0.998418,0.5,0.746835,1,0.496835,0.487342,0.490506,1,0.487421,0.496855,1,1,0.496855,1,1,0.746835,0.746835,0.737342,0.996855,0.493711,0.484177,1,0.732595,0.481013,0.996855,0.995253,1,0.490566,0.5,1,0.990566,0.490506,1,0.993711,0.75,0.496835,1,0.998418,0.493671,1,0.484277,0.5,0.72943,1,0.748418,0.75,0.468553,0.75,0.998418,0.484177,0.998418,0.75,0.746835,0.493671,0.477987,0.490566,0.740506,0.748418,0.745253,0.484177,0.746835,0.493711,0.748418,1,0.748418,0.745253,0.995253,1,0.996855,0.496835,0.742089,0.496855]
area_under_roc_curve
0.7396014947058351 [0.493671,0.745253,0.745253,1,0.748418,0.738924,0.493711,1,0.995253,0.746835,0.75,0.75,0.493711,0.496835,0.496835,0.493671,1,0.490506,0.493711,0.490506,0.5,1,0.737342,1,0.496855,0.748418,0.75,0.996855,1,0.996835,0.993711,0.993671,1,0.738924,0.496855,1,0.996855,0.493711,1,1,0.5,0.996855,1,0.996855,0.493671,0.493711,0.746835,0.993711,0.743671,0.75,0.737342,0.996855,0.5,0.487342,0.493711,0.487342,1,0.992089,0.996855,0.493671,0.496855,0.496855,0.493671,1,0.746835,0.748418,0.5,0.748418,0.493711,0.5,0.742089,0.993671,0.490566,0.742089,0.493711,0.5,0.996835,0.487342,0.5,0.996835,0.493711,0.493671,0.748418,1,0.493711,1,1,0.996835,0.746835,0.996855,1,1,0.5,0.740506,0.75,1,0.487342,0.996835,0.493711,0.745253]
area_under_roc_curve
0.7801498686410316 [0.745253,0.996835,1,1,0.75,0.493671,0.996855,0.75,0.75,0.75,0.992089,0.995253,0.493711,0.748418,0.998418,0.998418,0.746835,0.740506,0.490566,0.490506,0.987421,1,0.5,1,0.496855,0.493671,0.746835,1,0.746835,0.746835,0.993711,1,0.746835,0.493671,0.996855,0.496855,0.996855,1,0.996855,1,0.746835,0.993711,1,0.5,1,0.493711,0.746835,0.996855,0.993671,1,0.996835,1,0.984277,0.490506,0.996855,0.746835,1,1,0.487421,0.998418,1,0.996855,0.738924,0.5,0.746835,0.993671,0.738924,1,0.487421,0.745253,0.5,0.487342,0.496855,0.996835,0.490566,0.748418,0.75,0.484177,1,0.75,0.496855,0.5,1,0.727848,0.981132,0.5,1,0.996835,0.484177,0.996855,0.748418,0.496855,0.490566,0.490506,1,0.5,0.5,0.746835,0.977987,0.490506]
area_under_roc_curve
0.7238003542711569 [0.742089,1,0.75,1,0.496855,0.75,0.493711,0.496835,0.496855,0.75,0.748418,0.746835,1,0.477987,0.996855,0.496835,0.75,0.75,0.996855,0.737342,0.496835,0.745253,0.75,1,1,0.490506,0.493671,1,1,0.496835,0.493711,0.490566,0.496835,0.5,0.493711,1,0.746835,0.493671,0.990506,0.990506,0.748418,0.75,0.5,1,0.996855,0.490566,0.75,0.5,0.748418,1,0.987421,0.493711,0.5,0.993711,0.496835,0.477848,1,0.487342,0.75,0.493711,0.75,0.748418,1,0.5,0.746835,0.493671,0.490566,0.745253,0.496835,0.474684,0.490506,0.996835,1,0.493711,0.487342,1,0.746835,0.745253,1,0.996855,0.996855,0.996835,0.487342,0.737342,0.496855,0.996855,0.496855,0.496855,1,0.743671,0.996855,1,0.996855,0.993711,0.75,1,0.740506,0.996855,0.484277,0.493671]
area_under_roc_curve
0.75839154923971 [0.746835,1,1,1,1,0.5,1,0.748418,0.996855,0.748418,0.993671,0.742089,0.993711,0.987421,1,0.75,1,0.490506,0.487421,0.490506,0.75,0.743671,0.75,1,0.745253,0.474684,0.745253,1,1,0.75,1,1,0.740506,0.5,0.496855,1,0.493671,0.737342,1,1,1,0.745253,1,0.996855,0.5,0.993711,1,0.5,0.493671,0.746835,0.990566,1,0.985759,0.493711,0.745253,0.493671,1,1,0.740506,0.996855,0.746835,0.493671,0.496855,1,0.748418,0.75,0.487421,1,0.743671,0.748418,0.487342,0.743671,0.493711,1,0.493671,0.993711,0.75,0.487342,0.995253,0.5,0.996855,0.493671,0.5,0.487342,0.496855,1,0.5,0.490566,0.5,0.993671,1,0.75,0.493711,0.493711,0.996835,1,0.742089,0.493711,0.490566,0.746835]
area_under_roc_curve
0.7867749134224982 [0.998418,0.493711,1,0.748418,1,1,1,1,0.993711,0.745253,1,0.996855,0.743671,0.990566,0.5,0.743671,0.5,0.496855,0.487342,1,0.742089,1,0.993671,1,0.745253,0.490566,0.493711,0.746835,0.490566,1,1,0.5,1,0.490566,1,0.75,0.990506,0.75,0.746835,0.5,0.746835,1,0.746835,0.748418,1,0.746835,0.5,0.75,1,1,0.990566,0.746835,1,0.481132,0.746835,0.737342,1,0.5,0.496835,0.971698,1,0.738924,0.993711,0.496835,0.745253,0.996855,0.496855,0.996835,0.487342,0.487342,1,1,0.493671,1,0.477848,0.996855,1,0.996855,1,0.996855,0.748418,0.5,0.75,0.745253,0.998418,0.496835,0.75,0.487421,1,0.5,1,1,0.487342,0.490566,0.496855,0.746835,1,0.496855,0.740506,0.990506]
area_under_roc_curve
0.761182927314704 [0.75,0.993711,1,0.493671,0.996855,0.496835,0.996835,1,0.496855,1,0.5,0.496855,0.745253,0.496855,0.496855,0.487342,1,0.490566,0.993671,0.5,0.493671,0.748418,0.748418,1,0.748418,0.490566,0.477987,0.748418,1,0.746835,0.745253,0.996855,1,1,0.742089,1,0.746835,1,0.996835,0.996855,1,0.740506,0.996835,0.5,1,0.745253,0.75,1,0.990566,0.5,0.990566,0.493671,0.493671,1,0.742089,0.743671,1,0.998418,0.740506,1,0.5,0.748418,1,0.746835,0.75,0.493711,0.481132,0.75,0.493671,0.487342,0.481132,0.75,0.996835,0.484277,0.493671,1,1,0.981132,1,0.490566,0.745253,0.993711,0.490506,0.75,0.724684,0.748418,1,0.493711,1,0.745253,0.5,0.996835,0.746835,0.487421,0.5,0.996835,0.987342,0.496855,0.484177,0.740506]
area_under_roc_curve
0.7901755682270519 [0.496855,1,1,1,1,0.996855,0.742089,0.493711,0.746835,1,0.496855,1,0.996835,0.75,1,1,1,0.496855,1,1,0.998418,1,0.996855,1,0.75,0.487421,0.493711,0.743671,0.745253,1,1,0.75,0.493711,0.990566,0.993671,1,0.745253,0.743671,1,0.5,0.496855,0.748418,0.75,0.493671,0.493671,0.5,1,0.490506,0.5,1,0.496835,0.745253,1,0.727848,0.746835,0.490566,1,0.493711,0.493671,0.493671,0.5,0.996835,0.493671,0.748418,1,0.987421,0.990506,0.5,0.738924,1,1,0.490566,0.75,1,0.477848,0.490506,0.996855,0.490566,1,1,1,0.996855,0.5,0.496855,1,1,0.745253,0.746835,0.496855,0.75,1,0.75,1,0.740506,0.996855,0.496835,0.484277,0.995253,0.735759,1]
area_under_roc_curve
0.7741953019265982 [0.487421,0.496835,0.5,0.746835,1,0.996855,0.743671,0.496855,0.742089,1,0.990566,0.5,0.496835,0.748418,0.996835,0.993711,1,0.5,0.745253,1,0.75,0.996835,0.496855,1,1,0.490566,1,0.746835,0.493671,0.996855,0.5,0.75,1,0.484277,0.995253,0.75,0.487342,0.740506,0.996835,0.5,0.993711,0.993671,0.75,0.746835,1,0.745253,0.5,0.5,0.490566,0.496855,0.745253,0.496835,0.996835,0.484177,0.748418,0.487421,1,0.496855,0.493671,0.493671,0.996835,0.746835,0.487342,0.75,0.996855,0.5,0.734177,0.996855,0.998418,0.496855,0.493711,1,0.496835,0.996835,0.484177,0.998418,1,0.490566,0.496855,0.996835,0.996835,0.490566,1,0.5,0.998418,1,0.998418,0.988924,0.484277,0.996835,1,0.996835,1,0.737342,1,1,0.496855,0.5,0.745253,1]
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
0.48855564325177586
kappa
0.4191002367797948
kappa
0.4378873406229029
kappa
0.48224151539068666
kappa
0.39386764531786433
kappa
0.45047570170936796
kappa
0.5010066716671272
kappa
0.4506058333662233
kappa
0.50726468730259
kappa
0.4819962097283639
kb_relative_information_score
82.82280721158286
kb_relative_information_score
75.76640776719141
kb_relative_information_score
74.8808148308604
kb_relative_information_score
85.32240237923219
kb_relative_information_score
70.0152678368664
kb_relative_information_score
79.42319991345175
kb_relative_information_score
87.82921964701123
kb_relative_information_score
79.8267916764185
kb_relative_information_score
89.02767453810507
kb_relative_information_score
85.05390068524625
mean_absolute_error
0.010318750000000005
mean_absolute_error
0.011422916666666671
mean_absolute_error
0.011391666666666677
mean_absolute_error
0.010602083333333337
mean_absolute_error
0.011877083333333342
mean_absolute_error
0.011056250000000007
mean_absolute_error
0.010275000000000005
mean_absolute_error
0.011179166666666674
mean_absolute_error
0.009922916666666674
mean_absolute_error
0.010300000000000007
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
0.49375
predictive_accuracy
0.425
predictive_accuracy
0.44375
predictive_accuracy
0.4875
predictive_accuracy
0.4
predictive_accuracy
0.45625
predictive_accuracy
0.50625
predictive_accuracy
0.45625
predictive_accuracy
0.5125
predictive_accuracy
0.4875
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
0.49375 [1,0.5,1,0,0.5,1,0,1,0.5,1,1,0.5,0,0.5,1,0,1,0,0,0,1,0,0,1,0,0,0,1,0.5,0,1,1,0.5,0,1,0,0,0,1,1,0,0,0.5,1,1,0.5,0,1,0,0.5,0.5,0,1,0.5,1,0,0.5,1,1,0.5,0,1,0.5,0,1,0,0,1,0,0,0,1,0.5,0.5,0,1,0.5,0.5,0.5,1,1,0,1,1,0.5,0.5,1,0.5,0.5,0,0,1,1,0.5,0.5,0,1,0,0,1]
recall
0.425 [1,1,0.5,1,1,1,0,1,0.5,1,0,0.5,0,0.5,1,1,1,0,0,1,1,0,1,1,1,0,0,0,0.5,0,0.5,1,0,0,0,1,0,0,1,1,0,1,1,0.5,0.5,0.5,1,0,0,1,0,0,1,0.5,1,0,0,1,1,0,1,1,0.5,0,1,0.5,0,1,0,0,0.5,1,0.5,0.5,0,0.5,0.5,0,0.5,0.5,0.5,0,0,0,0.5,0,0.5,0,0,0,0.5,1,0.5,0,0.5,0.5,1,0,0,0]
recall
0.44375 [0,0.5,0.5,1,0.5,0.5,0,1,1,0.5,0.5,0.5,0,0,0,0,1,0,0,0,0,1,0.5,1,0,0.5,0.5,1,1,1,1,1,1,0.5,0,1,1,0,1,1,0,1,1,1,0,0,0.5,1,0.5,0.5,0.5,1,0,0,0,0,1,0.5,1,0,0,0,0,1,0.5,0.5,0,0.5,0,0,0.5,0.5,0,0.5,0,0,1,0,0,1,0,0,0,1,0,0,1,1,0.5,1,0.5,1,0,0,0.5,1,0,0.5,0,0.5]
recall
0.4875 [0.5,1,1,1,0.5,0,1,0,0.5,0.5,0.5,0.5,0,0.5,1,0.5,0.5,0.5,0,0,0,1,0,1,0,0,0.5,1,0.5,0.5,1,1,0.5,0,1,0,1,0,1,1,0.5,1,1,0,1,0,0.5,1,1,1,1,1,0,0,1,0.5,1,1,0,1,1,0,0.5,0,0.5,1,0.5,1,0,0.5,0,0,0,0.5,0,0.5,0.5,0,1,0.5,0,0,1,0,1,0,1,0,0,1,0.5,0,0,0,1,0,0,0.5,0,0]
recall
0.4 [0.5,1,0.5,1,0,0.5,0,0,0,0.5,0.5,0.5,1,0,1,0,0.5,0.5,1,0.5,0,0.5,0.5,1,1,0,0,1,1,0,0,0,0,0,0,1,0.5,0,0.5,1,0.5,0.5,0,1,1,0,0.5,0,0.5,0.5,0,0,0,0,0,0,1,0,0.5,0,0.5,0.5,1,0,0.5,0,0,0.5,0,0,0,0.5,1,0,0,1,0.5,0,1,0,1,1,0,0,0,1,0,0,1,0.5,1,1,0,1,0.5,1,0.5,1,0,0]
recall
0.45625 [0.5,1,1,1,1,0,1,0.5,1,0.5,1,0.5,0,1,1,0.5,1,0,0,0,0.5,0.5,0.5,1,0.5,0,0.5,1,1,0.5,1,1,0.5,0,0,0,0,0.5,1,0,1,0.5,1,1,0,1,1,0,0,0.5,1,1,0.5,0,0.5,0,1,1,0,1,0.5,0,0,0,0.5,0.5,0,1,0.5,0.5,0,0.5,0,1,0,0,0.5,0,0.5,0,1,0,0,0,0,1,0,0,0,1,1,0.5,0,0,1,0,0.5,0,0,0.5]
recall
0.50625 [1,0,1,0.5,1,1,1,1,0,0.5,0,1,0.5,1,0,0,0,0,0,1,0.5,1,1,1,0,0,0,0.5,0,1,1,0,1,0,1,0,1,0.5,0.5,0,0.5,1,0.5,0.5,1,0.5,0,0.5,0,1,1,0.5,0.5,0,0.5,0.5,1,0,0,0,1,0.5,1,0,0.5,1,0,1,0,0,1,1,0,0,0,1,1,1,1,1,0.5,0,0.5,0.5,0.5,0,0,0,1,0,1,1,0,0,0,0.5,1,0,0.5,0.5]
recall
0.45625 [0.5,1,1,0,1,0,1,1,0,1,0,0,0,0,0,0,1,0,1,0,0,0.5,0.5,0.5,0.5,0,0,0.5,1,0.5,0,1,1,1,0.5,1,0.5,0,1,1,1,0.5,1,0,1,0.5,0.5,1,1,0,1,0,0,1,0.5,0.5,1,1,0.5,1,0,0.5,1,0.5,0.5,0,0,0.5,0,0,0,0.5,1,0,0,1,1,0,1,0,0,0,0,0.5,0,0.5,1,0,1,0.5,0,1,0,0,0,1,0,0,0,0.5]
recall
0.5125 [0,1,1,1,1,1,0.5,0,0.5,1,0,1,1,0.5,1,1,1,0,1,1,1,1,1,1,0.5,0,0,0.5,0.5,1,1,0.5,0,0,1,1,0.5,0,1,0,0,0.5,0.5,0,0,0,1,0,0,1,0,0.5,1,0,0,0,1,0,0,0,0,1,0,0.5,1,0,0.5,0,0.5,1,1,0,0.5,1,0,0,1,0,1,0.5,1,1,0,0,0.5,1,0.5,0.5,0,0.5,1,0,1,0,1,0,0,1,0,0]
recall
0.4875 [0,0,0,0.5,1,1,0.5,0,0.5,1,1,0,0,0.5,1,1,1,0,0.5,1,0,1,0,1,1,0,1,0.5,0,1,0,0.5,1,0,0.5,0.5,0,0.5,1,0,0,0.5,0.5,0.5,1,0.5,0,0,0,0,0.5,0,1,0,0.5,0,1,0,0,0,1,0,0,0.5,1,0,0.5,1,1,0,0,0,0,1,0,1,1,0,0,0.5,1,0,1,0,1,1,0.5,0.5,0,1,1,1,1,0.5,1,0.5,0,0,0,1]
relative_absolute_error
0.5211489898989893
relative_absolute_error
0.5769149831649825
relative_absolute_error
0.5753367003366999
relative_absolute_error
0.5354587542087534
relative_absolute_error
0.5998526936026931
relative_absolute_error
0.5583964646464641
relative_absolute_error
0.5189393939393934
relative_absolute_error
0.5646043771043765
relative_absolute_error
0.5011574074074069
relative_absolute_error
0.5202020202020197
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
0.09382811560389442
root_mean_squared_error
0.0962319607915051
root_mean_squared_error
0.09825332196815424
root_mean_squared_error
0.09280692323312954
root_mean_squared_error
0.10032568492442778
root_mean_squared_error
0.09654086641878086
root_mean_squared_error
0.09110338297170358
root_mean_squared_error
0.09603005171993471
root_mean_squared_error
0.08879107030927529
root_mean_squared_error
0.09079089222554822
root_relative_squared_error
0.9430080431642678
root_relative_squared_error
0.9671675963200438
root_relative_squared_error
0.9874830405283361
root_relative_squared_error
0.9327446736715386
root_relative_squared_error
1.0083110719083088
root_relative_squared_error
0.9702722146876289
root_relative_squared_error
0.915623449846042
root_relative_squared_error
0.9651383337983226
root_relative_squared_error
0.8923838331816107
root_relative_squared_error
0.9124827996779952
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
230.9949009977572
usercpu_time_millis
225.0546850009414
usercpu_time_millis
173.00581900053658
usercpu_time_millis
167.22179199859966
usercpu_time_millis
163.88266300054966
usercpu_time_millis
167.66995999932988
usercpu_time_millis
169.19600699839066
usercpu_time_millis
166.5122220001649
usercpu_time_millis
165.55197900015628
usercpu_time_millis
167.34407999683754
usercpu_time_millis_testing
1.7088479980884586
usercpu_time_millis_testing
1.7118559990194626
usercpu_time_millis_testing
1.3036720010859426
usercpu_time_millis_testing
1.329017999523785
usercpu_time_millis_testing
1.3478869987011421
usercpu_time_millis_testing
1.5426479985762853
usercpu_time_millis_testing
1.3338659991859458
usercpu_time_millis_testing
1.3066069986962248
usercpu_time_millis_testing
1.3057899996056221
usercpu_time_millis_testing
1.2885029973404016
usercpu_time_millis_training
229.28605299966875
usercpu_time_millis_training
223.34282900192193
usercpu_time_millis_training
171.70214699945063
usercpu_time_millis_training
165.89277399907587
usercpu_time_millis_training
162.5347760018485
usercpu_time_millis_training
166.1273120007536
usercpu_time_millis_training
167.8621409992047
usercpu_time_millis_training
165.2056150014687
usercpu_time_millis_training
164.24618900055066
usercpu_time_millis_training
166.05557699949713