6056385
1
Jan van Rijn
9956
Supervised Classification
6952
sklearn.pipeline.Pipeline(imputation=openmlstudy14.preprocessing.ConditionalImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,variencethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,classifier=sklearn.svm.classes.SVC)(1)
4091034
axis
0
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categorical_features
[]
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copy
true
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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
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categorical_features
[]
6948
dtype
{"oml-python:serialized_object": "type", "value": "np.float64"}
6948
handle_unknown
"ignore"
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n_values
"auto"
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sparse
true
6948
threshold
0.0
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C
0.523144455895042
6953
cache_size
200
6953
class_weight
null
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coef0
0.7602947950709278
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decision_function_shape
null
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degree
3
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gamma
0.05519951279765904
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kernel
"sigmoid"
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max_iter
-1
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probability
true
6953
random_state
20969
6953
shrinking
true
6953
tol
3.452215252838227e-05
6953
verbose
false
6953
openml-pimp
openml-python
Sklearn_0.18.1.
1493
one-hundred-plants-texture
https://www.openml.org/data/download/1592285/phpoOxxNn
-1
13035918
description
https://api.openml.org/data/download/13035918/description.xml
-1
13035919
predictions
https://api.openml.org/data/download/13035919/predictions.arff
area_under_roc_curve
0.4060506626961566 [0.377315,0.418588,0.460557,0.407217,0.444923,0.459057,0.451082,0.356049,0.428103,0.450766,0.44591,0.381988,0.427037,0.338163,0.489063,0.417956,0.35364,0.464624,0.356325,0.374131,0.371526,0.508291,0.362919,0.424905,0.508291,0.392214,0.367222,0.465611,0.314869,0.328016,0.448239,0.329872,0.520689,0.350087,0.362326,0.481049,0.402164,0.338992,0.490919,0.343967,0.379304,0.315066,0.408007,0.457004,0.515398,0.458583,0.447568,0.427077,0.433986,0.444409,0.328846,0.404138,0.463084,0.411166,0.464269,0.30334,0.305749,0.40852,0.396636,0.312066,0.40781,0.340414,0.389806,0.331846,0.452543,0.390714,0.409784,0.407375,0.396478,0.441172,0.435368,0.454912,0.361774,0.36055,0.376895,0.418707,0.447213,0.370223,0.463124,0.44133,0.480891,0.459294,0.426287,0.440816,0.401334,0.361971,0.451516,0.430946,0.416022,0.305551,0.326003,0.418628,0.439395,0.307525,0.409152,0.475521,0.41539,0.32466,0.379225,0.336229]
average_cost
0
kappa
-0.00031555870280491763
kb_relative_information_score
30.33514787597671
mean_absolute_error
0.019791298379736148
mean_prior_absolute_error
0.019799992711748222
number_of_instances
1599 [15,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16]
predictive_accuracy
0.009380863039399626
prior_entropy
6.6438309601245775
recall
0.009380863039399626 [0.666667,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.3125]
relative_absolute_error
0.9995608921609899
root_mean_prior_squared_error
0.09949872432040595
root_mean_squared_error
0.09947321414974923
root_relative_squared_error
0.9997436130881983
total_cost
0
area_under_roc_curve
0.03807419791417884 [0.037975,0.062893,0.213836,0,0.018987,0.170886,0.113924,0.062893,0.009494,0.098101,0,0.06962,0.018987,0,0.243671,0,0.031646,0.069182,0,0,0.031447,0.221519,0.018987,0.075949,0.085443,0.006289,0.006289,0.037975,0,0.037736,0.06962,0.003165,0.232704,0.006289,0.056604,0.041139,0.018868,0.006289,0.012658,0.066456,0,0.006289,0.006289,0.022152,0.18239,0,0.126582,0.025157,0.053797,0.053797,0,0,0.025157,0.025316,0.037736,0,0,0.056604,0,0,0,0.018987,0,0,0.031646,0.003165,0.018987,0.031447,0.044025,0.03481,0.03481,0.006329,0.018868,0.031447,0,0.003165,0.015823,0.006329,0.044025,0,0.106918,0.003165,0.009494,0.012658,0.025157,0.006329,0.14557,0.022152,0.063291,0.003165,0.009494,0.06962,0.012579,0,0.018987,0.031646,0.018868,0,0.006329,0]
area_under_roc_curve
0.03763857376005097 [0.063291,0.201258,0.018868,0,0.018987,0.037975,0.044304,0,0.018987,0.082278,0.018868,0.025316,0,0,0.107595,0.003165,0.025316,0.050314,0,0.050633,0.047468,0.06962,0.03481,0.03481,0.164557,0.063291,0.169811,0.012658,0,0,0.072785,0.009494,0.119497,0,0.081761,0.082278,0.044025,0.037736,0.028481,0.060127,0.006329,0.012579,0.037736,0.136076,0.08805,0.006289,0.091772,0.025157,0.012658,0.025316,0,0,0,0.031646,0.012579,0,0.018868,0.09434,0.006289,0,0,0.018987,0,0.012579,0.091772,0.066456,0.03481,0.031447,0.006289,0.066456,0.018987,0.012658,0.012579,0.018868,0.003165,0,0.006329,0.028481,0.018868,0.012579,0.025157,0.091772,0.295597,0,0.006289,0,0.050633,0.06962,0.025316,0,0.044304,0.009494,0.006289,0,0.053797,0.072785,0,0.006289,0.03481,0]
area_under_roc_curve
0.0397079750816018 [0.066456,0.056604,0.025316,0,0.031646,0.069182,0.044304,0.006289,0.025157,0.025316,0.012658,0.08805,0.025316,0,0.056962,0,0.025316,0.056962,0.003165,0,0.028481,0.382911,0.063291,0.056604,0.125786,0.018987,0.006289,0.129747,0,0,0.117089,0,0.060127,0.015823,0.053797,0.056604,0,0.025316,0.044025,0.012579,0.012658,0.006289,0.018868,0.050633,0.088608,0.012658,0.037975,0.006329,0.018987,0.037736,0,0.041139,0.03481,0,0.150943,0.003165,0,0.132075,0.006289,0.018868,0,0,0.006289,0.006289,0.044304,0.003165,0.025316,0.050314,0,0.136076,0,0.094937,0.022152,0.006289,0.003165,0.006329,0.003165,0.012579,0.03481,0.060127,0.025157,0.196203,0,0,0.006289,0.018987,0.158228,0.069182,0.053797,0.012579,0.006289,0.101266,0.009494,0,0.018987,0.031447,0.018868,0.006329,0.012658,0.012579]
area_under_roc_curve
0.04680484236923814 [0.028481,0.113208,0.003165,0,0.025316,0.119497,0.041139,0.075949,0.012579,0.050633,0.022152,0.006289,0.012658,0,0.208861,0.003165,0.031646,0.050633,0,0,0.018987,0.297468,0.028481,0.157233,0.106918,0.009494,0.006289,0.265823,0.003165,0,0.183544,0.006289,0.370253,0,0.009494,0.207547,0.062893,0.03481,0.408805,0.006289,0.003165,0.006289,0.194969,0.075949,0.037975,0.031646,0.022152,0.018987,0,0.018868,0,0.003165,0.003165,0.037975,0.037975,0.003165,0,0.025157,0,0,0,0.044025,0,0.006289,0.060127,0,0.028481,0.031447,0,0.037975,0.018987,0.091772,0.012658,0.006289,0,0.003165,0.053797,0.025157,0.079114,0.009494,0.031447,0.025316,0.056604,0.003165,0.006289,0.015823,0,0.006289,0.041139,0,0,0.075949,0.10443,0,0.056604,0.044025,0.101266,0.006329,0.037975,0]
area_under_roc_curve
0.041376582278481025 [0.044304,0.072785,0.139241,0,0.018868,0.062893,0.025157,0.183544,0.050314,0.176101,0.003165,0.08805,0.062893,0,0.226415,0,0.037975,0.06962,0,0,0.012658,0,0.041139,0.169811,0.264151,0.028481,0.009494,0.025157,0.012658,0,0.069182,0.006289,0.107595,0.006329,0.037975,0,0.044304,0.012658,0.106918,0.226415,0.009494,0,0.075949,0.098101,0.174051,0.075949,0.072785,0.050633,0.012579,0.056604,0.012658,0.006329,0,0.018868,0.079114,0.012658,0,0.025316,0.006329,0,0,0.006289,0,0,0.062893,0.031447,0.009494,0.047468,0.012658,0.053797,0.044025,0.012579,0.006329,0.037975,0.018987,0,0.012579,0,0.012658,0.006329,0.066456,0.015823,0,0.012579,0.006329,0.003165,0.056962,0.081761,0.044304,0,0.025157,0.129747,0.025316,0,0,0.044025,0.129747,0,0.056962,0.006329]
area_under_roc_curve
0.046203029217419 [0.069182,0.066456,0.117089,0.006289,0.037736,0.138365,0.018868,0.031646,0,0.08805,0.009494,0.006289,0,0.003165,0.075472,0,0.015823,0.082278,0.009494,0,0.03481,0.289308,0.072785,0.08805,0.025157,0.044304,0.012658,0.245283,0,0,0.465409,0,0.237342,0.006329,0.06962,0,0.028481,0.018987,0.044025,0,0,0.006329,0.060127,0.037975,0.193038,0.037975,0.015823,0.139241,0.012579,0.037736,0,0,0.098101,0.018868,0.053797,0.006329,0,0.161392,0,0,0,0,0.006329,0,0.031447,0.006289,0.012658,0.075949,0.047468,0.091772,0.006289,0.031447,0.006329,0.031646,0.003165,0,0.044025,0,0.003165,0.047468,0.46519,0.031447,0.031646,0.012579,0.025316,0,0.022152,0.056604,0.022152,0.006289,0.025157,0.031646,0.031646,0,0.012579,0.056604,0.053797,0.006329,0.006329,0.009494]
area_under_roc_curve
0.041988595653212356 [0.119497,0.075949,0.025316,0,0.018868,0.098101,0.025157,0.012658,0.037975,0.09434,0.136076,0.129747,0.025157,0,0.025157,0,0,0.050633,0,0.003165,0.050633,0.345912,0.194969,0.044304,0.167722,0,0.044304,0.037736,0,0,0.018868,0.003165,0.053797,0,0.022152,0.088608,0.063291,0.031646,0.053797,0.003165,0,0,0.012658,0.075472,0.281646,0.037975,0.012579,0.107595,0.006289,0.037975,0,0,0.012658,0.050314,0.03481,0.012579,0.012658,0.123418,0.006329,0,0,0.009494,0,0.028481,0.069182,0.006289,0.006289,0.066456,0.075949,0.062893,0.037736,0,0.022152,0.120253,0.012579,0,0.012579,0.018987,0.072785,0.009494,0.03481,0,0.148734,0.006289,0.015823,0,0.006289,0.015823,0.062893,0,0.03481,0.150943,0.003165,0,0.025157,0.041139,0,0,0.006289,0.012658]
area_under_roc_curve
0.05477320675105486 [0.226415,0.053797,0.132911,0,0.08805,0.129747,0.075472,0.009494,0.041139,0.163522,0.158228,0.003165,0,0.006289,0.069182,0,0.113208,0.132911,0,0.075949,0.050314,0.421384,0.031447,0.018987,0.253165,0.056604,0.015823,0.238994,0,0,0.012579,0,0.493671,0,0.037975,0.199367,0.044304,0.022152,0.186709,0,0.006289,0.018987,0.063291,0.069182,0.094937,0.018987,0,0.003165,0.025316,0.050633,0,0,0.082278,0.018868,0.025316,0.012579,0.003165,0.056962,0,0,0,0.003165,0,0.003165,0.012579,0.047468,0.006289,0.085443,0.006329,0.18239,0.012579,0,0.022152,0.03481,0,0.006289,0.012579,0.003165,0.268987,0.031646,0.009494,0,0.025316,0.025157,0.047468,0.006289,0.314465,0.028481,0,0.009494,0.018987,0.09434,0.03481,0,0.053797,0.006329,0.012658,0,0,0.009494]
area_under_roc_curve
0.03949003861157553 [0.025157,0.098101,0.012579,0.018987,0.082278,0.066456,0.015823,0.098101,0,0.075949,0.006289,0.003165,0.006329,0.006289,0.183544,0.006329,0.031447,0.069182,0.025157,0,0.062893,0.132911,0.037736,0.053797,0.088608,0,0,0.120253,0,0,0.037975,0.012658,0.031447,0.006289,0.025157,0.022152,0.056962,0.025157,0.006329,0,0.012579,0.003165,0.003165,0.150943,0.106918,0.050314,0.018868,0.132075,0.189873,0.063291,0,0.012579,0,0.031646,0.022152,0.006289,0,0.085443,0,0,0,0,0.003165,0,0.132911,0.003165,0.018868,0.028481,0.012658,0.421384,0.012658,0.031646,0.050314,0.037975,0.012579,0,0.015823,0,0.006289,0.006289,0.202532,0.050314,0.117089,0.003165,0.015823,0,0.006289,0.022152,0.031447,0.003165,0.003165,0.113208,0.044025,0,0.044304,0.015823,0.006329,0.069182,0.006289,0.015823]
area_under_roc_curve
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average_cost
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average_cost
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average_cost
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average_cost
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average_cost
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average_cost
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average_cost
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average_cost
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average_cost
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average_cost
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kappa
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kappa
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kappa
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kappa
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kappa
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kappa
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kappa
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kappa
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kappa
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kappa
0
kb_relative_information_score
3.0004831071360836
kb_relative_information_score
2.842416479859514
kb_relative_information_score
2.908990990613251
kb_relative_information_score
2.8575335143156844
kb_relative_information_score
3.162798637974456
kb_relative_information_score
3.218920849986424
kb_relative_information_score
3.0601411328957284
kb_relative_information_score
3.211971190312141
kb_relative_information_score
3.000918614049199
kb_relative_information_score
3.0709733588342556
mean_absolute_error
0.019791396220841403
mean_absolute_error
0.019791884184005838
mean_absolute_error
0.019791652393356448
mean_absolute_error
0.01979182979632487
mean_absolute_error
0.01979083941403163
mean_absolute_error
0.019790765984788055
mean_absolute_error
0.019791278670975264
mean_absolute_error
0.01979073601404916
mean_absolute_error
0.019791466413842183
mean_absolute_error
0.019791133675746742
mean_prior_absolute_error
0.01980002942907592
mean_prior_absolute_error
0.01980002942907592
mean_prior_absolute_error
0.019800029429075917
mean_prior_absolute_error
0.019800029429075917
mean_prior_absolute_error
0.01980002942907591
mean_prior_absolute_error
0.01979995585638609
mean_prior_absolute_error
0.01979995585638609
mean_prior_absolute_error
0.01979995585638609
mean_prior_absolute_error
0.019799955856386102
mean_prior_absolute_error
0.01979995631910742
number_of_instances
160 [2,1,1,2,2,2,2,1,2,2,1,2,2,2,2,2,2,1,2,2,1,2,2,2,2,1,1,2,2,1,2,2,1,1,1,2,1,1,2,2,2,1,1,2,1,1,2,1,2,2,1,2,1,2,1,2,2,1,1,1,1,2,1,1,2,2,2,1,1,2,2,2,1,1,2,2,2,2,1,1,1,2,2,2,1,2,2,2,2,2,2,2,1,2,2,2,1,1,2,1]
number_of_instances
160 [2,1,1,2,2,2,2,1,2,2,1,2,2,2,2,2,2,1,2,2,2,2,2,2,2,2,1,2,2,2,2,2,1,1,1,2,1,1,2,2,2,1,1,2,1,1,2,1,2,2,1,2,1,2,1,2,1,1,1,1,1,2,1,1,2,2,2,1,1,2,2,2,1,1,2,2,2,2,1,1,1,2,1,2,1,2,2,2,2,2,2,2,1,1,2,2,1,1,2,1]
number_of_instances
160 [2,1,2,2,2,1,2,1,1,2,2,1,2,2,2,2,2,2,2,1,2,2,2,1,1,2,1,2,2,2,2,1,2,2,2,1,1,2,1,1,2,1,1,2,2,2,2,2,2,1,1,2,2,2,1,2,1,1,1,1,2,1,1,1,2,2,2,1,1,2,2,2,2,1,2,2,2,1,2,2,1,2,1,2,1,2,2,1,2,1,1,2,2,1,2,1,1,2,2,1]
number_of_instances
160 [2,1,2,2,2,1,2,2,1,2,2,1,2,2,2,2,2,2,2,1,2,2,2,1,1,2,1,2,2,2,2,1,2,2,2,1,1,2,1,1,2,1,1,2,2,2,2,2,1,1,1,2,2,2,2,2,1,1,1,1,2,1,1,1,2,1,2,1,1,2,2,2,2,1,2,2,2,1,2,2,1,2,1,2,1,2,2,1,2,1,1,2,2,1,1,1,2,2,2,1]
number_of_instances
160 [2,2,2,1,1,1,1,2,1,1,2,1,1,2,1,1,2,2,2,1,2,1,2,1,1,2,2,1,2,2,1,1,2,2,2,1,2,2,1,1,2,2,2,2,2,2,2,2,1,1,2,2,2,1,2,2,1,2,2,2,2,1,2,2,1,1,2,2,2,2,1,1,2,2,2,1,1,1,2,2,2,2,1,1,2,2,2,1,2,1,1,2,2,1,1,1,2,2,2,2]
number_of_instances
160 [1,2,2,1,1,1,1,2,1,1,2,1,1,2,1,1,2,2,2,1,2,1,2,1,1,2,2,1,2,2,1,1,2,2,2,1,2,2,1,1,2,2,2,2,2,2,2,2,1,1,2,1,2,1,2,2,2,2,2,2,2,1,2,2,1,1,2,2,2,2,1,1,2,2,2,1,1,1,2,2,2,1,2,1,2,2,2,1,2,1,1,2,2,2,1,1,2,2,2,2]
number_of_instances
160 [1,2,2,1,1,2,1,2,2,1,2,2,1,1,1,1,1,2,1,2,2,1,1,2,2,2,2,1,1,2,1,2,2,2,2,2,2,2,2,2,1,2,2,1,2,2,1,2,1,2,2,1,2,1,2,1,2,2,2,2,2,2,2,2,1,1,1,2,2,1,1,1,2,2,1,1,1,2,2,2,2,1,2,1,2,1,1,2,1,2,2,1,2,2,1,2,2,2,1,2]
number_of_instances
160 [1,2,2,1,1,2,1,2,2,1,2,2,1,1,1,1,1,2,1,2,1,1,1,2,2,1,2,1,1,1,1,2,2,2,2,2,2,2,2,2,1,2,2,1,2,2,1,2,2,2,2,1,2,1,2,1,2,2,2,2,2,2,2,2,1,2,1,2,2,1,1,1,2,2,1,1,1,2,2,2,2,1,2,1,2,1,1,2,1,2,2,1,2,2,2,2,2,2,1,2]
number_of_instances
160 [1,2,1,2,2,2,2,2,2,2,1,2,2,1,2,2,1,1,1,2,1,2,1,2,2,1,2,2,1,1,2,2,1,1,1,2,2,1,2,2,1,2,2,1,1,1,1,1,2,2,2,1,1,2,2,1,2,2,2,2,1,2,2,2,2,2,1,2,2,1,2,2,1,2,1,2,2,2,1,1,2,1,2,2,2,1,1,2,1,2,2,1,1,2,2,2,2,1,1,2]
number_of_instances
159 [1,2,1,2,2,2,2,1,2,2,1,2,2,1,2,2,1,1,1,2,1,2,1,2,2,1,2,2,1,1,2,2,1,1,1,2,2,1,2,2,1,2,2,1,1,1,1,1,2,2,2,2,1,2,1,1,2,2,2,2,1,2,2,2,2,2,1,2,2,1,2,2,1,2,1,2,2,2,1,1,2,2,2,2,2,1,1,2,1,2,2,1,1,2,2,2,1,1,1,2]
predictive_accuracy
0.0125
predictive_accuracy
0.0125
predictive_accuracy
0.0125
predictive_accuracy
0.0125
predictive_accuracy
0.0125
predictive_accuracy
0
predictive_accuracy
0.00625
predictive_accuracy
0.00625
predictive_accuracy
0.00625
predictive_accuracy
0.012578616352201257
prior_entropy
6.6438309601245775
prior_entropy
6.6438309601245775
prior_entropy
6.6438309601245775
prior_entropy
6.6438309601245775
prior_entropy
6.6438309601245775
prior_entropy
6.6438309601245775
prior_entropy
6.6438309601245775
prior_entropy
6.6438309601245775
prior_entropy
6.6438309601245775
prior_entropy
6.6438309601245775
recall
0.0125 [1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]
recall
0.0125 [1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]
recall
0.0125 [1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]
recall
0.0125 [1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]
recall
0.0125 [1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]
recall
0 [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]
recall
0.00625 [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.5]
recall
0.00625 [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.5]
recall
0.00625 [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.5]
recall
0.012578616352201259 [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1]
relative_absolute_error
0.999563980030159
relative_absolute_error
0.9995886245977936
relative_absolute_error
0.9995769180167394
relative_absolute_error
0.9995858777493025
relative_absolute_error
0.9995358585159078
relative_absolute_error
0.9995358640360265
relative_absolute_error
0.9995617573355331
relative_absolute_error
0.9995343503589703
relative_absolute_error
0.9995712393196482
relative_absolute_error
0.9995544109684643
root_mean_prior_squared_error
0.09949890883178135
root_mean_prior_squared_error
0.09949890883178135
root_mean_prior_squared_error
0.09949890883178135
root_mean_prior_squared_error
0.09949890883178135
root_mean_prior_squared_error
0.09949890883178135
root_mean_prior_squared_error
0.09949853911503082
root_mean_prior_squared_error
0.09949853911503082
root_mean_prior_squared_error
0.09949853911503082
root_mean_prior_squared_error
0.09949853911503082
root_mean_prior_squared_error
0.0994985414402977
root_mean_squared_error
0.09947440424163441
root_mean_squared_error
0.09947539258846416
root_mean_squared_error
0.09947441764910173
root_mean_squared_error
0.09947490719692506
root_mean_squared_error
0.0994728470590448
root_mean_squared_error
0.09947153063759898
root_mean_squared_error
0.09947267251366185
root_mean_squared_error
0.09947115729412553
root_mean_squared_error
0.09947307292041832
root_mean_squared_error
0.09947173001927494
root_relative_squared_error
0.999753720011258
root_relative_squared_error
0.9997636532541583
root_relative_squared_error
0.9997538547611508
root_relative_squared_error
0.9997587748937342
root_relative_squared_error
0.9997380697633517
root_relative_squared_error
0.9997285540303197
root_relative_squared_error
0.9997400303401534
root_relative_squared_error
0.9997248017795154
root_relative_squared_error
0.9997440545877458
root_relative_squared_error
0.9997305345321184
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
3229.136162000941
usercpu_time_millis
3065.5239059997257
usercpu_time_millis
3086.973814997691
usercpu_time_millis
3074.4960919982987
usercpu_time_millis
3089.5609929993952
usercpu_time_millis
3093.5043999998015
usercpu_time_millis
3089.299804001712
usercpu_time_millis
3117.8244239999913
usercpu_time_millis
3104.3877899992367
usercpu_time_millis
3100.2116330000717
usercpu_time_millis_testing
165.38142500030517
usercpu_time_millis_testing
163.09593500045594
usercpu_time_millis_testing
164.56556399862166
usercpu_time_millis_testing
164.23254899927997
usercpu_time_millis_testing
157.97275399927457
usercpu_time_millis_testing
164.20458799984772
usercpu_time_millis_testing
163.004236001143
usercpu_time_millis_testing
163.5365140009526
usercpu_time_millis_testing
164.07370299930335
usercpu_time_millis_testing
162.63077999974485
usercpu_time_millis_training
3063.754737000636
usercpu_time_millis_training
2902.4279709992697
usercpu_time_millis_training
2922.4082509990694
usercpu_time_millis_training
2910.2635429990187
usercpu_time_millis_training
2931.5882390001207
usercpu_time_millis_training
2929.299811999954
usercpu_time_millis_training
2926.295568000569
usercpu_time_millis_training
2954.2879099990387
usercpu_time_millis_training
2940.3140869999334
usercpu_time_millis_training
2937.580853000327