8828212
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)
6803262
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
"mean"
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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
7663
with_mean
false
7663
with_std
true
7663
C
755.3760894858318
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cache_size
200
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class_weight
null
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coef0
-0.13476497200947501
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decision_function_shape
null
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degree
4
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gamma
2.171768836058901
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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
7531
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shrinking
false
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tol
0.03618984327557112
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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
18572226
description
https://api.openml.org/data/download/18572226/description.xml
-1
18572227
predictions
https://api.openml.org/data/download/18572227/predictions.arff
area_under_roc_curve
0.3978841145833332 [0.410314,0.401417,0.404849,0.409051,0.405106,0.409466,0.407079,0.403054,0.408756,0.385377,0.409762,0.40917,0.390132,0.410117,0.410077,0.407019,0.398378,0.395971,0.420691,0.419172,0.397767,0.40554,0.387745,0.404948,0.39459,0.378295,0.422842,0.401121,0.391828,0.378512,0.375986,0.410926,0.380859,0.380524,0.410176,0.349353,0.382615,0.403705,0.392479,0.395261,0.39901,0.400213,0.374665,0.383523,0.410649,0.393999,0.410077,0.399424,0.410413,0.373422,0.385811,0.39611,0.400726,0.404691,0.406132,0.380327,0.406506,0.391907,0.394748,0.408617,0.380978,0.382753,0.401377,0.394255,0.404376,0.397629,0.395537,0.396386,0.40337,0.403034,0.387409,0.390487,0.378887,0.406743,0.401061,0.397274,0.394334,0.401002,0.39532,0.402916,0.39029,0.394669,0.401752,0.390684,0.38591,0.391986,0.410709,0.394985,0.404613,0.390625,0.371843,0.403389,0.400785,0.408795,0.406132,0.403409,0.407552,0.401752,0.414181,0.408223]
average_cost
0
kappa
-0.003787878787878788
kb_relative_information_score
4.466861894736676
mean_absolute_error
0.01980270241868903
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 [0.25,0.125,0.125,0.125,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]
relative_absolute_error
1.0001364857923734
root_mean_prior_squared_error
0.09949874371066209
root_mean_squared_error
0.09951341231722234
root_relative_squared_error
1.000147425042902
total_cost
0
area_under_roc_curve
0.23812495024281502 [0.383648,0.363924,0.341772,0.342767,0.178797,0.389937,0.35443,0.383648,0.341772,0,0.357595,0.329114,0.170886,0.35443,0.341772,0.383648,0.181962,0.446203,0.639241,0.393082,0.006289,0.383648,0,0.389937,0.367925,0.370253,0.397152,0.172468,0.170886,0.371069,0,0.341772,0,0.009494,0.344937,0.012579,0,0,0,0.183544,0,0.399371,0.172468,0,0.363924,0.18038,0.383648,0,0.341772,0.183544,0,0,0.383648,0.325949,0.402516,0.006289,0.363924,0,0.899371,0.186709,0,0,0.300633,0.170886,0.367925,0,0.178797,0,0.383648,0.396226,0.370253,0,0.172468,0.181962,0.383648,0.363924,0.341772,0.376582,0.172468,0.150316,0,0.012658,0.386792,0,0.181962,0.177215,0.325949,0,0.297468,0.371069,0,0.342767,0.172468,0.363924,0.341772,0.18038,0.380503,0.363924,0.490506,0.40566]
area_under_roc_curve
0.2656478883050713 [0.41195,0.178797,0.370253,0.41195,0.329114,0.386792,0.181962,0,0.357595,0,0.363924,0.357595,0,0.303797,0.370253,0.371069,0.322785,0.481013,0.599684,0.41195,0.399371,0.349057,0,0.380503,0,0.493671,0.625,0.357595,0,0,0,0.363924,0,0.015823,0.357595,0,0.421384,0.006289,0.41195,0.360759,0.355346,0,0,0.183544,0.357595,0.18038,0.389937,0.361635,0.357595,0.003165,0,0.363924,0.41195,0.360759,0.418239,0.987421,0.363924,0,0,0.370253,0,0,0.177215,0.178797,0.393082,0.185127,0.193038,0,0,0.402516,0.193038,0.393082,0,0.370253,0.402516,0.181962,0.169304,0.390823,0.183544,0.363924,0.181962,0.183544,0.41195,0.415094,0,0.185127,0.367089,0.357595,0.367089,0.41195,0,0.40566,0.357595,0.363924,0.183544,0.357595,0.41195,0.367089,0.599684,0.386792]
area_under_roc_curve
0.2414147709179204 [0.360759,0.360759,0.338608,0.308176,0.35443,0.35443,0.396226,0.344937,0.360759,0,0.310127,0.338608,0,0.344937,0.360759,0.303797,0.360759,0.189873,0.006289,0.609177,0.380503,0.402516,0.172468,0,0.399371,0.487342,0.650316,0,0,0,0,0.35443,0.156646,0.496835,0.389937,0,0.006289,0.012579,0,0.338608,0.177215,0.399371,0,0.402516,0.360759,0,0.35443,0.399371,0.360759,0.178797,0.166139,0.396226,0,0.178797,0.399371,0,0.396226,0,0.41195,0.357595,0.374214,0,0.365506,0.399371,0.335443,0,0.003165,0,0.377358,0.35443,0.424051,0.006329,0.018868,0.360759,0.399371,0,0,0.18038,0.18038,0.348101,0.399371,0,0.363924,0,0,0.380503,0.396226,0,0.174051,0.396226,0,0.389937,0.396226,0.35443,0.357595,0,0.35443,0.185127,0,0.363924]
area_under_roc_curve
0.23405904187564683 [0.363924,0.175633,0.344937,0.389937,0.363924,0.341772,0.396226,0.170886,0.291139,0.175633,0.348101,0.28481,0.377358,0.348101,0.332278,0.153481,0.348101,0.003165,0.399371,0.471519,0.389937,0.396226,0.003165,0.389937,0,0.018987,0.174051,0.342767,0.175633,0,0,0.363924,0,0.5,0.402516,0.006289,0.981132,0.402516,0,0.174051,0.142405,0.402516,0,0,0.363924,0,0.348101,0.36478,0.357595,0,0,0.399371,0,0.351266,0.389937,0.012658,0.386792,0.172468,0,0.348101,0,0,0.356013,0,0.181962,0.363924,0,0.332278,0.389937,0.341772,0.172468,0.178797,0.006289,0.174051,0.396226,0.341772,0.351266,0.188291,0.341772,0.175633,0.389937,0.003165,0.181962,0.178797,0.380503,0,0.408805,0,0.325949,0.006289,0.129747,0.399371,0.367925,0.341772,0.181962,0,0.325949,0.174051,0.424528,0.363924]
area_under_roc_curve
0.26381757025714514 [0.357595,0.393082,0.185127,0.335443,0.393082,0.348101,0.371069,0.341772,0.393082,0.174051,0.376582,0.357595,0.393082,0.393082,0.396226,0.373418,0,0.009494,0.81761,0.193038,0.175633,0.186709,0.18038,0.348101,0.186709,0.006329,0.824367,0.393082,0.393082,0,0,0.396226,0.006329,0.015823,0.399371,0,0,0.427215,0.188291,0.188291,0.386076,0.357595,0.36478,0.399371,0.393082,0.393082,0.370253,0.188291,0.363924,0,0.374214,0.393082,0.335443,0.402516,0.357595,0.443038,0.402516,0.178797,0.006329,0.393082,0.178797,0,0.383648,0.393082,0.363924,0.344937,0,0.338608,0.332278,0.178797,0.003165,0.174051,0,0.393082,0.344937,0.402516,0.175633,0.417722,0.186709,0,0,0.181962,0.169304,0.468354,0.358491,0.393082,0.393082,0.389937,0.357595,0,0.358491,0.186709,0.374214,0.389937,0.370253,0.393082,0.363924,0,0.421384,0.348101]
area_under_roc_curve
0.2778641479579651 [0.341772,0.393082,0.351266,0.351266,0.349057,0.332278,0.393082,0.177215,0.358491,0.18038,0.344937,0.338608,0.402516,0.389937,0.355346,0.338608,0.338608,0.003165,0,0.598101,0,0.363924,0.177215,0.351266,0.178797,0.018987,0.631329,0.380503,0,0,0,0.393082,0,0.446203,0.327044,0.496835,0.493671,0.449367,0,0.357595,0.370253,0.177215,0.396226,0,0.380503,0.380503,0.35443,0.243671,0.351266,0.177215,0,0,0.370253,0.402516,0.344937,0.509494,0.396226,0.363924,0.003165,0.402516,0,0.337025,0.814465,0,0.363924,0.363924,0.006289,0.370253,0.370253,0.35443,0.186709,0.188291,0,0.396226,0.131329,0,0.186709,0.012658,0.35443,0.396226,0.006289,0.381329,0.18038,0.471519,0.399371,0,0.399371,0,0.351266,0.177215,0,0.351266,0,0.393082,0.344937,0.399371,0.175633,0.396226,0.886792,0.351266]
area_under_roc_curve
0.2449146913064247 [0.344937,0.40566,0.418239,0.344937,0.418239,0.370253,0.348101,0.357595,0.371069,0.177215,0.40566,0.415094,0.183544,0.418239,0.418239,0.35443,0,0.355346,0.452532,0.200949,0.167722,0.329114,0.003165,0.306962,0.175633,0.795597,0.006289,0.363924,0.377358,0,0.151899,0.415094,0,0.006289,0.341772,0,0.468354,0.009494,0.18038,0.415094,0.360759,0.231013,0,0,0.421384,0.313291,0.335443,0.338608,0.415094,0,0.418239,0.175633,0.185127,0.415094,0.167722,0,0.185127,0.31962,0.439873,0.41195,0.006329,0.360759,0.006289,0.360759,0.109177,0.867925,0.009434,0.18038,0.177215,0.341772,0,0.183544,0.003165,0.424528,0.172468,0.421384,0.380503,0,0.40566,0.330189,0.186709,0.415094,0.186709,0,0,0,0.35443,0.415094,0.41195,0,0,0.172468,0.344937,0.418239,0.415094,0.344937,0.344937,0.41195,0.181962,0.367089]
area_under_roc_curve
0.23115123198789894 [0.348101,0.389937,0.386792,0.351266,0.374214,0.329114,0.332278,0.348101,0.377358,0,0.393082,0.389937,0.169304,0.389937,0.389937,0.344937,0.389937,0.861635,0.360759,0.181962,0.598101,0.329114,0.177215,0.348101,0.172468,0.006289,0,0.351266,0.31761,0.177215,0,0.377358,0,0,0.348101,0,0.006329,0.46519,0.158228,0,0,0,0,0,0.361635,0.175633,0.348101,0.348101,0.349057,0,0.389937,0.153481,0.484177,0,0.351266,0.003165,0.175633,0,0.183544,0.371069,0,0,0,0.175633,0.297468,0.389937,0.408805,0.177215,0.155063,0.348101,0.006289,0,0,0.389937,0.175633,0,0,0.805031,0.389937,0.389937,0.174051,0.399371,0.351266,0,0,0.306962,0.348101,0.349057,0.349057,0.175633,0,0.348101,0.351266,0.393082,0.361635,0.332278,0.348101,0.349057,0.378165,0.18038]
area_under_roc_curve
0.2432622551946501 [0.383648,0,0,0.338608,0.360759,0.383648,0.351266,0.383648,0.357595,0,0.383648,0.389937,0.178797,0.360759,0.325949,0.383648,0,0.006289,0.193038,0.987421,0.183544,0.360759,0.393082,0.35443,0.360759,0.006289,0.399371,0.178797,0.18038,0,0,0.357595,0.383648,0,0.363924,0,0,0.873418,0.363924,0.389937,0.383648,0.360759,0,0.181962,0.338608,0.18038,0.383648,0.161392,0.383648,0.383648,0.178797,0.167722,0.178797,0.297468,0.18038,0,0.338608,0.380503,0.166139,0.335443,0.178797,0,0,0.357595,0.380503,0,0.643987,0.380503,0.357595,0,0,0.377358,0.196203,0.360759,0.166139,0.18038,0,0,0.371069,0.335443,0.178797,0,0.396226,0,0,0,0.360759,0.360759,0,0,0.006329,0.35443,0,0.18038,0.383648,0.363924,0.371069,0.181962,0.670886,0.380503]
area_under_roc_curve
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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
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average_cost
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kappa
0
kappa
0
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
kappa
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kappa
0
kb_relative_information_score
0.4622190648338133
kb_relative_information_score
0.46222527381995554
kb_relative_information_score
0.4370221100339651
kb_relative_information_score
0.43699555042457194
kb_relative_information_score
0.4242942979278182
kb_relative_information_score
0.4242911856905871
kb_relative_information_score
0.449085969928178
kb_relative_information_score
0.44901869208299827
kb_relative_information_score
0.4599850891500436
kb_relative_information_score
0.4617246608447445
mean_absolute_error
0.0198027951697641
mean_absolute_error
0.019802795169603267
mean_absolute_error
0.019802646773126084
mean_absolute_error
0.019802638385040844
mean_absolute_error
0.019802561334505833
mean_absolute_error
0.019802561166134776
mean_absolute_error
0.019802714844435024
mean_absolute_error
0.019802715096968647
mean_absolute_error
0.01980280316086646
mean_absolute_error
0.019802793086445357
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 [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
0.00625 [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
0.00625 [0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]
recall
0.00625 [0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]
recall
0.00625 [0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]
recall
0.00625 [0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]
recall
0.00625 [0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]
recall
0.00625 [0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]
recall
0.00625 [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
0.00625 [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]
relative_absolute_error
1.0001411701901044
relative_absolute_error
1.0001411701819816
relative_absolute_error
1.0001336754104067
relative_absolute_error
1.0001332517697379
relative_absolute_error
1.000129360328576
relative_absolute_error
1.000129351824987
relative_absolute_error
1.0001371133553025
relative_absolute_error
1.000137126109526
relative_absolute_error
1.0001415737811328
relative_absolute_error
1.000141064971986
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
0.09951394870697448
root_mean_squared_error
0.09951394872855567
root_mean_squared_error
0.0995130915429095
root_mean_squared_error
0.09951304931127779
root_mean_squared_error
0.0995126012808409
root_mean_squared_error
0.09951260042758887
root_mean_squared_error
0.09951348284613375
root_mean_squared_error
0.09951348409720172
root_mean_squared_error
0.09951398324627965
root_mean_squared_error
0.09951393297072297
root_relative_squared_error
1.0001528159627489
root_relative_squared_error
1.0001528161796476
root_relative_squared_error
1.0001442011397568
root_relative_squared_error
1.000143776695888
root_relative_squared_error
1.0001392738205734
root_relative_squared_error
1.000139265245068
root_relative_squared_error
1.0001481338851328
root_relative_squared_error
1.000148146458839
root_relative_squared_error
1.0001531630958267
root_relative_squared_error
1.0001526578074702
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
3469.341840999974
usercpu_time_millis
3101.9943189999995
usercpu_time_millis
3102.4708809999875
usercpu_time_millis
3092.610845999985
usercpu_time_millis
3075.0489309999975
usercpu_time_millis
3158.5060739999735
usercpu_time_millis
3222.69375700003
usercpu_time_millis
3191.729035999998
usercpu_time_millis
3126.345600000008
usercpu_time_millis
3218.3555869999905
usercpu_time_millis_testing
154.32377599998404
usercpu_time_millis_testing
151.86301800000024
usercpu_time_millis_testing
157.87317499999176
usercpu_time_millis_testing
149.09015300000306
usercpu_time_millis_testing
148.43362799999227
usercpu_time_millis_testing
161.57099199998015
usercpu_time_millis_testing
152.64595400000758
usercpu_time_millis_testing
165.71040799999537
usercpu_time_millis_testing
155.837235000007
usercpu_time_millis_testing
152.43698099999392
usercpu_time_millis_training
3315.0180649999897
usercpu_time_millis_training
2950.131300999999
usercpu_time_millis_training
2944.597705999996
usercpu_time_millis_training
2943.520692999982
usercpu_time_millis_training
2926.6153030000055
usercpu_time_millis_training
2996.935081999993
usercpu_time_millis_training
3070.0478030000227
usercpu_time_millis_training
3026.0186280000025
usercpu_time_millis_training
2970.5083650000006
usercpu_time_millis_training
3065.9186059999965