8708742
1
Jan van Rijn
9954
Supervised Classification
7707
sklearn.pipeline.Pipeline(imputation=openmlstudy14.preprocessing.ConditionalImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,scaling=sklearn.preprocessing.data.StandardScaler,variencethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,classifier=sklearn.svm.classes.SVC)(1)
6686161
axis
0
7660
categorical_features
[]
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copy
true
7660
fill_empty
0
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missing_values
"NaN"
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strategy
"most_frequent"
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strategy_nominal
"most_frequent"
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verbose
0
7660
categorical_features
[]
7661
dtype
{"oml-python:serialized_object": "type", "value": "np.float64"}
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handle_unknown
"ignore"
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n_values
"auto"
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sparse
true
7661
threshold
0.0
7662
copy
true
7663
with_mean
false
7663
with_std
true
7663
C
13984.150975333469
7708
cache_size
200
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class_weight
null
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coef0
0.5162429369688231
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decision_function_shape
null
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degree
2
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gamma
3.211312342542643
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kernel
"sigmoid"
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max_iter
-1
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probability
true
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random_state
15128
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shrinking
true
7708
tol
0.0009128728861118195
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verbose
false
7708
openml-pimp
openml-python
Sklearn_0.18.1.
study_71
1491
one-hundred-plants-margin
https://www.openml.org/data/download/1592283/phpCsX3fx
-1
18334334
description
https://api.openml.org/data/download/18334334/description.xml
-1
18334335
predictions
https://api.openml.org/data/download/18334335/predictions.arff
area_under_roc_curve
0.5770022490530302 [0.585306,0.521978,0.585069,0.487788,0.584892,0.533933,0.5872,0.582268,0.550979,0.517322,0.5683,0.574771,0.562184,0.584103,0.584261,0.584675,0.584517,0.575659,0.585977,0.584162,0.553543,0.584576,0.581479,0.57848,0.56974,0.556009,0.583688,0.585938,0.583728,0.581341,0.574712,0.584103,0.584063,0.562816,0.584557,0.51815,0.584458,0.578973,0.611683,0.583728,0.584359,0.584339,0.585464,0.585503,0.58505,0.58576,0.516611,0.572956,0.583886,0.583708,0.584063,0.585661,0.584635,0.585543,0.586016,0.572345,0.512271,0.584714,0.584813,0.58432,0.584872,0.584655,0.584359,0.58578,0.584635,0.583491,0.584478,0.584695,0.584833,0.584813,0.583905,0.584537,0.578697,0.584063,0.584557,0.584201,0.583767,0.583708,0.583649,0.583984,0.586095,0.584083,0.584458,0.584596,0.585385,0.585444,0.585326,0.584596,0.584261,0.582031,0.57339,0.558396,0.586174,0.584912,0.584596,0.585997,0.58211,0.561533,0.585642,0.586391]
average_cost
0
kappa
0.002525252525252526
kb_relative_information_score
17.943053037283445
mean_absolute_error
0.019794728120402755
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
0.0125
prior_entropy
6.6438561897747395
recall
0.0125 [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.25,0,0.5,0.5]
relative_absolute_error
0.9997337434546827
root_mean_prior_squared_error
0.09949874371066209
root_mean_squared_error
0.09950787933001722
root_relative_squared_error
1.0000918164291772
total_cost
0
area_under_roc_curve
0.5229508747313111 [0.578616,0.063291,0.566456,0.075472,0.566456,0.012579,0.566456,0.581761,0.063291,0.987421,0.566456,0.566456,0.566456,0.566456,0.566456,0.581761,0.566456,0.566456,0.566456,0.581761,0.581761,0.581761,0.575472,0.578616,0.125786,0.300633,0.566456,0.566456,0.566456,0.578616,0.566456,0.572785,0.566456,0.325949,0.566456,0.031447,0.572327,0.578616,0.987421,0.566456,0.572327,0.572327,0.566456,0.566456,0.566456,0.566456,0.006289,0.075472,0.566456,0.566456,0.566456,0.566456,0.572327,0.566456,0.581761,0.106918,0.028481,0.581761,0.578616,0.566456,0.572327,0.578616,0.566456,0.566456,0.575472,0.566456,0.566456,0.578616,0.578616,0.575472,0.566456,0.572327,0.34019,0.575949,0.581761,0.566456,0.572785,0.566456,0.566456,0.566456,0.566456,0.566456,0.572327,0.578616,0.566456,0.566456,0.566456,0.566456,0.566456,0.575472,0.566456,0.572327,0.566456,0.566456,0.566456,0.566456,0.575472,0.518987,0.566456,0.575472]
area_under_roc_curve
0.4960181812753762 [0.566038,0.262658,0.528481,0.544025,0.528481,0.031447,0.53481,0.559748,0.503165,0.006289,0.28481,0.302215,0.528481,0.531646,0.528481,0.556604,0.528481,0.531646,0.528481,0.559748,0.072327,0.569182,0.556604,0.553459,0.106918,0.544304,0.528481,0.537975,0.528481,0.553459,0.528481,0.528481,0.528481,0.300633,0.528481,0.006289,0.566038,0.553459,0.515723,0.531646,0.553459,0.566038,0.528481,0.531646,0.528481,0.528481,0.050314,0.559748,0.528481,0.528481,0.53481,0.528481,0.553459,0.528481,0.553459,0.037736,0.012658,0.556604,0.562893,0.528481,0.562893,0.556604,0.544304,0.528481,0.553459,0.528481,0.541139,0.562893,0.559748,0.559748,0.528481,0.553459,0.537975,0.528481,0.550314,0.53481,0.528481,0.528481,0.537975,0.528481,0.531646,0.528481,0.553459,0.559748,0.528481,0.528481,0.537975,0.528481,0.556962,0.553459,0.295886,0.553459,0.528481,0.528481,0.528481,0.541139,0.556604,0.75,0.528481,0.553459]
area_under_roc_curve
0.4969733948332138 [0.556962,0.044304,0.56962,0.09434,0.563291,0.025316,0.584906,0.572785,0.278481,0.022152,0.064873,0.325949,0.075472,0.563291,0.572785,0.563291,0.56962,0.352848,0.58805,0.56962,0.572327,0.58805,0.556962,0.578616,0.578616,0.286392,0.556962,0.578616,0.556962,0.329114,0.572327,0.556962,0.579114,0.333861,0.578616,0.025157,0.572327,0.160377,0.522013,0.572785,0.563291,0.578616,0.578616,0.578616,0.556962,0.581761,0.041139,0.572327,0.572785,0.582278,0.566456,0.572327,0.578616,0.56962,0.575472,0.556962,0,0.556962,0.578616,0.556962,0.581761,0.578616,0.566456,0.581761,0.556962,0.556962,0.556962,0.556962,0.572327,0.566456,0.582278,0.560127,0.578616,0.556962,0.578616,0.556962,0.556962,0.563291,0.556962,0.560127,0.578616,0.566456,0.56962,0.556962,0.578616,0.572327,0.575472,0.556962,0.563291,0.578616,0.343354,0.566038,0.572327,0.566456,0.566456,0.578616,0.556962,0.56962,0.575472,0.563291]
area_under_roc_curve
0.49806382354111944 [0.56962,0.031646,0.560127,0.075472,0.560127,0.272152,0.572327,0.560127,0.280063,0.012658,0.560127,0.566456,0.572327,0.56962,0.56962,0.56962,0.56962,0.330696,0.575472,0.56962,0.100629,0.572327,0.56962,0.572327,0.069182,0.316456,0.56962,0.572327,0.563291,0.56962,0.119497,0.56962,0.566456,0.311709,0.572327,0.031447,0.575472,0.572327,0.522013,0.556962,0.560127,0.575472,0.572327,0.572327,0.560127,0.572327,0.262658,0.100629,0.572785,0.560127,0.560127,0.572327,0.572327,0.560127,0.572327,0.556962,0.037736,0.566456,0.572327,0.560127,0.572327,0.572327,0.56962,0.575472,0.560127,0.560127,0.575949,0.560127,0.572327,0.560127,0.560127,0.56962,0.572327,0.560127,0.572327,0.556962,0.56962,0.566456,0.560127,0.556962,0.572327,0.560127,0.560127,0.560127,0.572327,0.575472,0.572327,0.560127,0.560127,0.575472,0.318038,0.125786,0.572327,0.566456,0.556962,0.575472,0.556962,0.064873,0.572327,0.556962]
area_under_roc_curve
0.5123254766738317 [0.556962,0.122642,0.556962,0.009494,0.569182,0.044304,0.569182,0.556962,0.569182,0.256329,0.556962,0.556962,0.572327,0.575472,0.569182,0.556962,0.556962,0.556962,0.575472,0.556962,0.556962,0.556962,0.556962,0.311709,0.335443,0.556962,0.556962,0.575472,0.569182,0.566456,0.09434,0.569182,0.556962,0.553797,0.569182,0.028481,0.556962,0.556962,0.982595,0.556962,0.563291,0.556962,0.569182,0.575472,0.578616,0.569182,0.028481,0.556962,0.556962,0.556962,0.569182,0.569182,0.556962,0.569182,0.560127,0.302215,0.037736,0.556962,0.566456,0.569182,0.556962,0.556962,0.572327,0.569182,0.556962,0.556962,0.569182,0.556962,0.556962,0.556962,0.556962,0.575949,0.569182,0.569182,0.556962,0.575472,0.556962,0.556962,0.556962,0.569182,0.575472,0.556962,0.556962,0.560127,0.569182,0.575472,0.575472,0.569182,0.556962,0.556962,0.569182,0.325949,0.569182,0.569182,0.556962,0.575472,0.556962,0.08805,0.575472,0.566456]
area_under_roc_curve
0.5113573262479103 [0.537975,0.056604,0.544304,0.003165,0.550314,0.537975,0.544025,0.537975,0.056604,0.25,0.276899,0.537975,0.544025,0.544025,0.550314,0.541139,0.541139,0.537975,0.544025,0.537975,0.295886,0.541139,0.541139,0.541139,0.537975,0.544304,0.544304,0.550314,0.544025,0.537975,0.544025,0.556604,0.541139,0.531646,0.550314,0.256329,0.537975,0.541139,0.987342,0.541139,0.537975,0.541139,0.544025,0.550314,0.544025,0.544025,0.268987,0.310127,0.537975,0.537975,0.544025,0.550314,0.541139,0.550314,0.544304,0.531646,0.037736,0.544304,0.544304,0.544025,0.544304,0.537975,0.544025,0.544025,0.544304,0.537975,0.550314,0.541139,0.537975,0.537975,0.544304,0.537975,0.544025,0.544025,0.537975,0.544025,0.541139,0.537975,0.541139,0.550314,0.550314,0.541139,0.537975,0.541139,0.544025,0.550314,0.544025,0.544025,0.537975,0.537975,0.544025,0.537975,0.550314,0.550314,0.537975,0.550314,0.537975,0.550314,0.544025,0.537975]
area_under_roc_curve
0.510440550115437 [0.56962,0.166667,0.575472,0.015823,0.581761,0.047468,0.56962,0.56962,0.556604,0.509494,0.569182,0.572327,0.324367,0.572327,0.569182,0.56962,0.569182,0.569182,0.56962,0.56962,0.088608,0.56962,0.360759,0.575949,0.34019,0.119497,0.569182,0.56962,0.572327,0.56962,0.575949,0.572327,0.572327,0.122642,0.56962,0.050633,0.56962,0.56962,0.990506,0.569182,0.575949,0.56962,0.56962,0.56962,0.572327,0.56962,0.025316,0.56962,0.572327,0.569182,0.569182,0.56962,0.56962,0.569182,0.56962,0.56962,0.066456,0.56962,0.56962,0.572327,0.56962,0.56962,0.572327,0.56962,0.575949,0.572327,0.572327,0.575949,0.572785,0.56962,0.569182,0.56962,0.56962,0.569182,0.56962,0.569182,0.569182,0.569182,0.572327,0.572327,0.579114,0.569182,0.575949,0.56962,0.56962,0.56962,0.56962,0.572327,0.569182,0.56962,0.569182,0.085443,0.56962,0.569182,0.569182,0.56962,0.56962,0.113208,0.575949,0.56962]
area_under_roc_curve
0.5011928041159143 [0.563291,0.119497,0.575472,0.322785,0.578616,0.306962,0.566456,0.560127,0.572327,0.496835,0.575472,0.056604,0.327532,0.575472,0.578616,0.56962,0.575472,0.584906,0.566456,0.560127,0.063291,0.560127,0.566456,0.560127,0.560127,0.132075,0.584906,0.566456,0.584906,0.566456,0.566456,0.581761,0.584906,0.141509,0.566456,0.022152,0.560127,0.560127,0.512658,0.584906,0.566456,0.560127,0.56962,0.563291,0.584906,0.560127,0.012658,0.332278,0.584906,0.575472,0.584906,0.563291,0.56962,0.575472,0.560127,0.563291,0.053797,0.560127,0.560127,0.584906,0.563291,0.560127,0.575472,0.575949,0.560127,0.584906,0.584906,0.563291,0.566456,0.585443,0.575472,0.560127,0.566456,0.578616,0.563291,0.575472,0.584906,0.578616,0.578616,0.575472,0.563291,0.575472,0.560127,0.56962,0.566456,0.560127,0.560127,0.584906,0.584906,0.566456,0.157233,0.056962,0.566456,0.575472,0.584906,0.566456,0.322785,0.012579,0.566456,0.566456]
area_under_roc_curve
0.5058928678051109 [0.578616,0.313291,0.578616,0.018987,0.556962,0.559748,0.556962,0.160377,0.30538,0.006289,0.119497,0.58805,0.28481,0.560127,0.566456,0.581761,0.572327,0.572327,0.588608,0.575472,0.311709,0.560127,0.572327,0.330696,0.556962,0.075472,0.581761,0.572785,0.556962,0.581761,0.338608,0.560127,0.575472,0.572327,0.560127,0.012658,0.566456,0.335443,0.740506,0.581761,0.575472,0.560127,0.560127,0.560127,0.566456,0.560127,0.012579,0.582278,0.572327,0.572327,0.560127,0.556962,0.556962,0.572785,0.566456,0.584906,0.072785,0.572327,0.566456,0.563291,0.556962,0.560127,0.560127,0.566456,0.581761,0.575472,0.556962,0.572327,0.560127,0.572327,0.581761,0.581761,0.582278,0.560127,0.563291,0.566456,0.572327,0.572327,0.572327,0.56962,0.556962,0.572327,0.572327,0.572327,0.56962,0.560127,0.560127,0.560127,0.575472,0.351266,0.566456,0.335443,0.566456,0.560127,0.572327,0.575949,0.572327,0.522152,0.560127,0.584906]
area_under_roc_curve
0.5003176996258258 [0.591195,0.063291,0.584906,0.060127,0.566456,0.031447,0.566456,0.584906,0.072785,0,0.591195,0.584906,0.337025,0.566456,0.566456,0.600629,0.597484,0.081761,0.566456,0.597484,0.56962,0.566456,0.591195,0.572785,0.566456,0.100629,0.584906,0.566456,0.566456,0.584906,0.348101,0.575949,0.591195,0.050314,0.575949,0.037975,0.566456,0.566456,0.496835,0.584906,0.600629,0.56962,0.566456,0.566456,0.566456,0.566456,0.050314,0.566456,0.597484,0.58805,0.566456,0.56962,0.566456,0.566456,0.566456,0.176101,0.012658,0.597484,0.566456,0.566456,0.575949,0.566456,0.566456,0.566456,0.584906,0.58805,0.566456,0.591195,0.572785,0.597484,0.597484,0.584906,0.338608,0.56962,0.566456,0.566456,0.58805,0.597484,0.584906,0.566456,0.566456,0.584906,0.581761,0.597484,0.566456,0.582278,0.566456,0.566456,0.581761,0.582278,0.566456,0.075949,0.566456,0.566456,0.581761,0.566456,0.584906,0.356013,0.566456,0.597484]
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
0.0000791076655327902
kappa
0
kappa
0
kappa
0
kappa
0
kappa
0
kappa
0
kappa
0
kappa
0
kappa
0
kb_relative_information_score
1.7584037633649816
kb_relative_information_score
1.7584788110000482
kb_relative_information_score
1.81757476742174
kb_relative_information_score
1.8173216474887102
kb_relative_information_score
1.853983477377752
kb_relative_information_score
1.8444724858579105
kb_relative_information_score
1.7954700748960182
kb_relative_information_score
1.7873157379846145
kb_relative_information_score
1.7555380816489279
kb_relative_information_score
1.7544941902427726
mean_absolute_error
0.019794725963289066
mean_absolute_error
0.019794726425522935
mean_absolute_error
0.019794542927504155
mean_absolute_error
0.019794544500852027
mean_absolute_error
0.01979440101133728
mean_absolute_error
0.0197944603575164
mean_absolute_error
0.019794584238900337
mean_absolute_error
0.019794635311485044
mean_absolute_error
0.019794736994794948
mean_absolute_error
0.019795923472825064
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
0.0125
predictive_accuracy
0.0125
predictive_accuracy
0.0125
predictive_accuracy
0.0125
predictive_accuracy
0.0125
predictive_accuracy
0.0125
predictive_accuracy
0.0125
predictive_accuracy
0.0125
predictive_accuracy
0.0125
predictive_accuracy
0.0125
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
0.0125 [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0]
recall
0.0125 [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0]
recall
0.0125 [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1]
recall
0.0125 [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1]
recall
0.0125 [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0]
recall
0.0125 [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0]
recall
0.0125 [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1]
recall
0.0125 [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1]
recall
0.0125 [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0]
recall
0.0125 [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0]
relative_absolute_error
0.9997336345095471
relative_absolute_error
0.999733657854692
relative_absolute_error
0.999724390277986
relative_absolute_error
0.9997244697399996
relative_absolute_error
0.9997172227948106
relative_absolute_error
0.9997202200765842
relative_absolute_error
0.9997264767121365
relative_absolute_error
0.9997290561356067
relative_absolute_error
0.9997341916563088
relative_absolute_error
0.999794114789143
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
0.09947748022474265
root_mean_squared_error
0.09947650069161248
root_mean_squared_error
0.09947581486331353
root_mean_squared_error
0.09947582413917591
root_mean_squared_error
0.09947568575535345
root_mean_squared_error
0.09947562160001044
root_mean_squared_error
0.09947597964605473
root_mean_squared_error
0.09947622880349401
root_mean_squared_error
0.09947662929692987
root_mean_squared_error
0.09979257560549815
root_relative_squared_error
0.9997862939256676
root_relative_squared_error
0.9997764492472965
root_relative_squared_error
0.9997695564135443
root_relative_squared_error
0.9997696496394688
root_relative_squared_error
0.9997682588297231
root_relative_squared_error
0.9997676140442653
root_relative_squared_error
0.9997712125424063
root_relative_squared_error
0.9997737166688907
root_relative_squared_error
0.9997777417793686
root_relative_squared_error
1.0029531216563954
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
2008.2906379975611
usercpu_time_millis
1797.0911130032619
usercpu_time_millis
1811.730567998893
usercpu_time_millis
1814.629694003088
usercpu_time_millis
1813.3044249989325
usercpu_time_millis
1823.1933020069846
usercpu_time_millis
1848.3761430034065
usercpu_time_millis
1826.51293600793
usercpu_time_millis
1795.2279169985559
usercpu_time_millis
1798.5992819958483
usercpu_time_millis_testing
123.05926399858436
usercpu_time_millis_testing
122.9067029998987
usercpu_time_millis_testing
121.6812420025235
usercpu_time_millis_testing
120.89074800314847
usercpu_time_millis_testing
126.40943199949106
usercpu_time_millis_testing
126.27137500385288
usercpu_time_millis_testing
130.5130350010586
usercpu_time_millis_testing
121.5049650054425
usercpu_time_millis_testing
121.06119199597742
usercpu_time_millis_testing
121.13420599780511
usercpu_time_millis_training
1885.2313739989768
usercpu_time_millis_training
1674.1844100033632
usercpu_time_millis_training
1690.0493259963696
usercpu_time_millis_training
1693.7389459999395
usercpu_time_millis_training
1686.8949929994415
usercpu_time_millis_training
1696.9219270031317
usercpu_time_millis_training
1717.8631080023479
usercpu_time_millis_training
1705.0079710024875
usercpu_time_millis_training
1674.1667250025785
usercpu_time_millis_training
1677.4650759980432