8830363
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)
6805413
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
[]
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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
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threshold
0.0
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copy
true
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with_mean
false
7663
with_std
true
7663
C
24.3594864585759
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cache_size
200
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class_weight
null
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coef0
0.8285448398641024
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decision_function_shape
null
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degree
3
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gamma
2.1660236221554703
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kernel
"rbf"
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max_iter
-1
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probability
true
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random_state
39977
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shrinking
true
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tol
0.008042124258788
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verbose
false
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openml-pimp
openml-python
Sklearn_0.18.1.
study_71
1491
one-hundred-plants-margin
https://www.openml.org/data/download/1592283/phpCsX3fx
-1
18576510
description
https://api.openml.org/data/download/18576510/description.xml
-1
18576511
predictions
https://api.openml.org/data/download/18576511/predictions.arff
area_under_roc_curve
0.3976712436868685 [0.409801,0.401239,0.403034,0.409407,0.404514,0.410176,0.407375,0.400588,0.408302,0.385476,0.41059,0.409071,0.385239,0.410413,0.410768,0.405579,0.396839,0.39386,0.420001,0.421283,0.399937,0.403685,0.385298,0.407631,0.394176,0.376164,0.427261,0.401397,0.392401,0.380879,0.375868,0.408164,0.381293,0.380485,0.409367,0.349432,0.382102,0.403567,0.394807,0.394669,0.399187,0.401673,0.372652,0.385219,0.410176,0.389895,0.407098,0.396603,0.410156,0.372889,0.386048,0.39682,0.398793,0.405816,0.405915,0.380366,0.405875,0.392243,0.394827,0.406645,0.380899,0.382497,0.401989,0.394196,0.405461,0.397155,0.39753,0.400982,0.402975,0.402344,0.391217,0.387094,0.37863,0.406447,0.40118,0.399325,0.393762,0.400312,0.395597,0.406191,0.389106,0.394334,0.40114,0.388159,0.39029,0.391552,0.410038,0.394985,0.404908,0.39023,0.370068,0.403212,0.401456,0.407138,0.405836,0.402186,0.403133,0.398852,0.415739,0.407947]
average_cost
0
kappa
-0.003787878787878788
kb_relative_information_score
4.116036469138173
mean_absolute_error
0.01980248343236493
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
0.00625
prior_entropy
6.6438561897747395
recall
0.00625 [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.125,0,0,0,0,0,0,0,0,0,0,0,0,0.125,0.125,0.25]
relative_absolute_error
1.000125425877015
root_mean_prior_squared_error
0.09949874371066209
root_mean_squared_error
0.09951206835786296
root_relative_squared_error
1.0001339177431188
total_cost
0
area_under_roc_curve
0.24319197317092586 [0.399371,0.341772,0.332278,0.383648,0.170886,0.361635,0.341772,0.383648,0.360759,0,0.341772,0.310127,0.177215,0.341772,0.341772,0.361635,0.357595,0.446203,0.629747,0.792453,0.006289,0.383648,0,0.383648,0.383648,0.379747,0.398734,0.183544,0.181962,0.402516,0,0.181962,0,0.009494,0.360759,0.012579,0,0,0,0.172468,0,0.399371,0,0,0.341772,0.183544,0.389937,0,0.341772,0.178797,0,0,0.386792,0.35443,0.383648,0.006289,0.357595,0,0.90566,0.185127,0,0,0.341772,0.170886,0.399371,0,0.177215,0.383648,0.399371,0.389937,0.348101,0,0.172468,0.170886,0.389937,0.341772,0.341772,0.329114,0.167722,0.174051,0,0.012658,0.374214,0,0.357595,0.158228,0.360759,0,0.341772,0.393082,0,0.367925,0.18038,0.332278,0.35443,0.18038,0.393082,0.344937,0.487342,0.389937]
area_under_roc_curve
0.2595085980415572 [0.393082,0.174051,0.357595,0.396226,0.363924,0.41195,0.169304,0,0.291139,0,0.367089,0.348101,0,0.348101,0.363924,0,0.183544,0.481013,0.599684,0.430818,0.393082,0.41195,0,0.386792,0,0.493671,0.625,0.367089,0,0,0,0.344937,0,0.015823,0.332278,0,0.383648,0.006289,0.408805,0.329114,0.393082,0,0,0.357595,0.360759,0.175633,0.393082,0.389937,0.363924,0.003165,0,0.357595,0.396226,0.360759,0.402516,0.987421,0.348101,0,0,0.363924,0,0,0.18038,0.183544,0.377358,0.188291,0.34019,0,0,0.393082,0.181962,0,0,0.363924,0.386792,0.174051,0.18038,0.392405,0.181962,0.360759,0.183544,0.18038,0.41195,0.393082,0.18038,0.143987,0.357595,0.357595,0.357595,0.415094,0,0.389937,0.357595,0.294304,0.178797,0.344937,0.389937,0.186709,0.601266,0.380503]
area_under_roc_curve
0.24702763016479573 [0.338608,0.351266,0.360759,0.339623,0.35443,0.35443,0.386792,0.35443,0.35443,0,0.360759,0.338608,0,0.35443,0.360759,0.35443,0.35443,0.189873,0.006289,0.579114,0.386792,0.393082,0.155063,0.374214,0.396226,0.487342,0.661392,0,0,0,0,0.344937,0.18038,0.496835,0.339623,0,0.006289,0.012579,0.393082,0.344937,0.172468,0.389937,0,0.380503,0.35443,0,0.338608,0.380503,0.360759,0.166139,0.18038,0.374214,0,0.156646,0.396226,0,0.396226,0,0.41195,0.357595,0.396226,0,0.360759,0.399371,0.35443,0,0.003165,0.18038,0.396226,0.35443,0.424051,0.006329,0.018868,0.360759,0.377358,0,0,0.177215,0.348101,0.338608,0.371069,0,0.344937,0,0,0.380503,0.396226,0,0.178797,0.380503,0,0.36478,0.396226,0.35443,0.338608,0,0.18038,0.175633,0,0.341772]
area_under_roc_curve
0.23016492018947532 [0.351266,0.174051,0.332278,0.396226,0.329114,0.341772,0.396226,0,0.360759,0.183544,0.363924,0.310127,0,0.344937,0.357595,0.174051,0.181962,0.003165,0.383648,0.471519,0.383648,0.386792,0.003165,0.377358,0,0.018987,0.297468,0.393082,0.175633,0,0,0.363924,0,0.5,0.399371,0.006289,0.981132,0.408805,0,0.170886,0.174051,0.386792,0,0,0.351266,0,0.313291,0.355346,0.341772,0,0,0.399371,0.383648,0.367089,0.393082,0.012658,0.408805,0.172468,0,0.181962,0,0,0.359177,0,0.175633,0.332278,0,0.360759,0.36478,0.367089,0.337025,0.166139,0.006289,0.174051,0.393082,0.363924,0.329114,0.175633,0.357595,0.183544,0.399371,0.003165,0.178797,0.003165,0.383648,0,0.396226,0,0.344937,0.006289,0.170886,0.389937,0.383648,0.341772,0.181962,0,0.348101,0.170886,0.367925,0.297468]
area_under_roc_curve
0.25819699864660445 [0.344937,0.393082,0,0.344937,0.393082,0.363924,0.393082,0.363924,0.380503,0.174051,0.357595,0.357595,0.003145,0.383648,0.393082,0.363924,0,0.009494,0.77673,0.193038,0.175633,0.178797,0.175633,0.348101,0.181962,0.006329,0.832278,0.393082,0.374214,0.174051,0,0.393082,0.006329,0.015823,0.380503,0,0,0.427215,0.185127,0.175633,0.386076,0.357595,0.380503,0.393082,0.393082,0.380503,0.357595,0.175633,0.344937,0,0.393082,0.389937,0.351266,0.393082,0.376582,0.443038,0.399371,0.178797,0.006329,0.399371,0.170886,0,0.393082,0.389937,0.363924,0.344937,0,0.357595,0.357595,0.181962,0.003165,0.174051,0,0.393082,0.363924,0.358491,0.18038,0.416139,0.169304,0.393082,0,0.006329,0.18038,0.468354,0.393082,0.399371,0.393082,0.393082,0.335443,0,0.012579,0.185127,0.393082,0.393082,0.332278,0.374214,0.344937,0,0.421384,0.344937]
area_under_roc_curve
0.2822664148953108 [0.351266,0.399371,0.363924,0.363924,0.377358,0.35443,0.396226,0.175633,0.254717,0.170886,0.351266,0.338608,0.402516,0.393082,0.396226,0.341772,0.35443,0.003165,0,0.599684,0.177215,0.351266,0.177215,0.351266,0.15981,0.018987,0.626582,0.396226,0,0,0,0.399371,0,0.446203,0.308176,0.496835,0.493671,0.449367,0,0.35443,0.329114,0.177215,0.396226,0,0.399371,0.342767,0.341772,0.177215,0.35443,0.167722,0,0,0.363924,0.355346,0.367089,0.512658,0.399371,0.35443,0.003165,0.386792,0,0.367089,0.811321,0,0.335443,0.363924,0.006289,0.341772,0.322785,0.310127,0.370253,0.181962,0,0.396226,0.15981,0.393082,0.167722,0.012658,0.287975,0.386792,0.006289,0.533228,0.185127,0.471519,0.399371,0,0.374214,0,0.341772,0.183544,0,0.341772,0,0.396226,0.367089,0.374214,0.18038,0.371069,0.886792,0.332278]
area_under_roc_curve
0.23672042930499165 [0.329114,0.418239,0.418239,0.351266,0.418239,0.363924,0.344937,0.363924,0.415094,0.169304,0.386792,0.418239,0.172468,0.396226,0.41195,0.367089,0,0.025157,0.452532,0.19462,0.196203,0.335443,0.003165,0.341772,0.166139,0.443396,0.421384,0.338608,0.386792,0,0.148734,0.415094,0,0.006289,0.351266,0,0.452532,0.009494,0.178797,0.421384,0.370253,0.363924,0,0,0.415094,0.183544,0.181962,0.181962,0.41195,0,0.421384,0.172468,0.18038,0.41195,0.131329,0,0.143987,0.357595,0.441456,0.41195,0.006329,0.322785,0.006289,0.363924,0.181962,0.871069,0.009434,0.174051,0.175633,0.363924,0,0.14557,0.003165,0.415094,0.175633,0.424528,0.345912,0,0.314465,0.415094,0.125,0.418239,0.174051,0,0,0,0.310127,0.415094,0.41195,0,0,0.175633,0.360759,0.36478,0.424528,0.294304,0.348101,0.396226,0.191456,0.351266]
area_under_roc_curve
0.22140417263752887 [0.348101,0.361635,0.389937,0.329114,0.386792,0.348101,0.348101,0.294304,0.345912,0,0.386792,0.389937,0.166139,0.389937,0.386792,0.348101,0.389937,0.861635,0.363924,0.174051,0.56962,0.175633,0.003165,0.351266,0.169304,0.006289,0,0.348101,0.386792,0.177215,0,0.36478,0,0,0.341772,0,0.006329,0.46519,0.172468,0,0,0,0,0,0.342767,0,0.351266,0.351266,0.386792,0,0.371069,0.175633,0.338608,0,0.348101,0.003165,0.174051,0,0.181962,0.386792,0,0,0,0.174051,0.351266,0.361635,0.393082,0.175633,0.177215,0.306962,0.006289,0,0,0.386792,0.172468,0,0,0.795597,0.333333,0.361635,0.155063,0.377358,0.348101,0,0,0.341772,0.348101,0.371069,0.345912,0.151899,0,0.351266,0.35443,0.374214,0.371069,0.348101,0.174051,0.389937,0.375,0.281646]
area_under_roc_curve
0.24035494287875164 [0.383648,0,0,0.325949,0.275316,0.380503,0.357595,0.383648,0.335443,0,0.383648,0.383648,0.18038,0.357595,0.357595,0.383648,0,0.006289,0.188291,0.987421,0.183544,0.357595,0.393082,0.357595,0.357595,0.006289,0.408805,0.18038,0.178797,0,0,0.325949,0.371069,0,0.35443,0,0,0.870253,0.357595,0.393082,0.383648,0.357595,0,0.158228,0.341772,0.183544,0.380503,0.18038,0.383648,0.380503,0.178797,0.183544,0.178797,0.363924,0.178797,0,0.35443,0.393082,0.183544,0.357595,0.181962,0,0,0.335443,0.367925,0,0.656646,0.389937,0.338608,0,0,0.380503,0.19462,0.357595,0.158228,0.178797,0,0,0.358491,0.35443,0.178797,0,0.386792,0,0,0,0.357595,0.357595,0,0,0.006329,0.357595,0,0.178797,0.389937,0.357595,0.383648,0.170886,0.490506,0.383648]
area_under_roc_curve
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average_cost
0
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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kb_relative_information_score
0.39424731730251206
kb_relative_information_score
0.3942541425189512
kb_relative_information_score
0.4228440166988324
kb_relative_information_score
0.42279676888424256
kb_relative_information_score
0.43750341634980544
kb_relative_information_score
0.4374984443912522
kb_relative_information_score
0.40933281485256706
kb_relative_information_score
0.4092593415997709
kb_relative_information_score
0.3932448494881949
kb_relative_information_score
0.3950553570520418
mean_absolute_error
0.019802372837595554
mean_absolute_error
0.01980237283761445
mean_absolute_error
0.019802558052409432
mean_absolute_error
0.01980254880473397
mean_absolute_error
0.0198026408543344
mean_absolute_error
0.01980264065905095
mean_absolute_error
0.019802466683180323
mean_absolute_error
0.01980246691630055
mean_absolute_error
0.019802388232657706
mean_absolute_error
0.01980237844577152
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
0.00625
predictive_accuracy
0.00625
predictive_accuracy
0.00625
predictive_accuracy
0.00625
predictive_accuracy
0.00625
predictive_accuracy
0.00625
predictive_accuracy
0.00625
predictive_accuracy
0.00625
predictive_accuracy
0.00625
predictive_accuracy
0.00625
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
0.00625 [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1]
recall
0.00625 [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1]
recall
0.00625 [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0]
recall
0.00625 [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0]
recall
0.00625 [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]
recall
0.00625 [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]
recall
0.00625 [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0]
recall
0.00625 [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0]
recall
0.00625 [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1]
recall
0.00625 [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1]
relative_absolute_error
1.0001198402826021
relative_absolute_error
1.0001198402835563
relative_absolute_error
1.0001291945661313
relative_absolute_error
1.0001287275118151
relative_absolute_error
1.0001333764815339
relative_absolute_error
1.000133366618733
relative_absolute_error
1.0001245799586005
relative_absolute_error
1.0001245917323494
relative_absolute_error
1.0001206178109936
relative_absolute_error
1.0001201235238124
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
0.09951143526998799
root_mean_squared_error
0.09951143528381748
root_mean_squared_error
0.0995124796446998
root_mean_squared_error
0.09951243290527488
root_mean_squared_error
0.09951297201474014
root_mean_squared_error
0.09951297101411724
root_mean_squared_error
0.09951197705696874
root_mean_squared_error
0.0995119781945702
root_mean_squared_error
0.09951152553180082
root_mean_squared_error
0.09951147664558815
root_relative_squared_error
1.0001275549705715
root_relative_squared_error
1.0001275551095632
root_relative_squared_error
1.0001380513313582
root_relative_squared_error
1.0001375815824634
root_relative_squared_error
1.0001429998364548
root_relative_squared_error
1.0001429897798162
root_relative_squared_error
1.0001330001346063
root_relative_squared_error
1.0001330115679312
root_relative_squared_error
1.0001284621359234
root_relative_squared_error
1.0001279708109996
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
3469.198293000318
usercpu_time_millis
3389.3243729999085
usercpu_time_millis
3240.55621000025
usercpu_time_millis
3197.7906209999674
usercpu_time_millis
3583.8797680003154
usercpu_time_millis
3289.824299000429
usercpu_time_millis
3247.9607740001484
usercpu_time_millis
3290.592947999812
usercpu_time_millis
3229.8199869997006
usercpu_time_millis
3269.2760019999696
usercpu_time_millis_testing
149.80767099996228
usercpu_time_millis_testing
165.53377399986857
usercpu_time_millis_testing
146.5466889999334
usercpu_time_millis_testing
145.14860600002066
usercpu_time_millis_testing
146.87616200035336
usercpu_time_millis_testing
146.8050690000382
usercpu_time_millis_testing
141.51893500002188
usercpu_time_millis_testing
151.47114299998066
usercpu_time_millis_testing
139.65078899991568
usercpu_time_millis_testing
142.38660299997719
usercpu_time_millis_training
3319.3906220003555
usercpu_time_millis_training
3223.79059900004
usercpu_time_millis_training
3094.0095210003165
usercpu_time_millis_training
3052.6420149999467
usercpu_time_millis_training
3437.003605999962
usercpu_time_millis_training
3143.019230000391
usercpu_time_millis_training
3106.4418390001265
usercpu_time_millis_training
3139.1218049998315
usercpu_time_millis_training
3090.169197999785
usercpu_time_millis_training
3126.8893989999924