10208595
1
Jan van Rijn
9954
Supervised Classification
9666
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,gradientboostingclassifier=sklearn.ensemble.gradient_boosting.GradientBoostingClassifier)(4)
8134027
copy
true
9559
fill_value
-1
9559
missing_values
NaN
9559
strategy
"constant"
9559
verbose
0
9559
n_jobs
null
9606
remainder
"passthrough"
9606
sparse_threshold
0.3
9606
transformer_weights
null
9606
transformers
[{"oml-python:serialized_object": "component_reference", "value": {"key": "numeric", "step_name": "numeric", "argument_1": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63]}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "nominal", "step_name": "nominal", "argument_1": []}}]
9606
memory
null
9607
steps
[{"oml-python:serialized_object": "component_reference", "value": {"key": "imputer", "step_name": "imputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "standardscaler", "step_name": "standardscaler"}}]
9607
axis
0
9608
copy
true
9608
missing_values
"NaN"
9608
strategy
"mean"
9608
verbose
0
9608
copy
true
9609
with_mean
true
9609
with_std
true
9609
memory
null
9610
steps
[{"oml-python:serialized_object": "component_reference", "value": {"key": "simpleimputer", "step_name": "simpleimputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "onehotencoder", "step_name": "onehotencoder"}}]
9610
categorical_features
null
9611
categories
null
9611
dtype
{"oml-python:serialized_object": "type", "value": "np.float64"}
9611
handle_unknown
"ignore"
9611
n_values
null
9611
sparse
true
9611
threshold
0.0
9612
memory
null
9666
steps
[{"oml-python:serialized_object": "component_reference", "value": {"key": "columntransformer", "step_name": "columntransformer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "variancethreshold", "step_name": "variancethreshold"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "gradientboostingclassifier", "step_name": "gradientboostingclassifier"}}]
9666
criterion
"friedman_mse"
9667
init
null
9667
learning_rate
0.001309934740014382
9667
loss
"deviance"
9667
max_depth
17
9667
max_features
0.8918767676071436
9667
max_leaf_nodes
null
9667
min_impurity_decrease
0.41724437242561563
9667
min_impurity_split
null
9667
min_samples_leaf
8
9667
min_samples_split
10
9667
min_weight_fraction_leaf
0.07771601367523312
9667
n_estimators
642
9667
n_iter_no_change
700
9667
presort
"auto"
9667
random_state
53540
9667
subsample
0.5317701356531108
9667
tol
2.8680717303170383e-05
9667
validation_fraction
0.8079103924062544
9667
verbose
0
9667
warm_start
false
9667
openml-python
Sklearn_0.20.3.
1491
one-hundred-plants-margin
https://www.openml.org/data/download/1592283/phpCsX3fx
-1
21338106
description
https://api.openml.org/data/download/21338106/description.xml
-1
21338107
predictions
https://api.openml.org/data/download/21338107/predictions.arff
area_under_roc_curve
0.5390013415404039 [0.838699,0.382418,0.461411,0.283144,0.209793,0.744437,0.210898,0.816248,0.55524,0.180082,0.567472,0.164457,0.586766,0.479127,0.267835,0.744121,0.859967,0.630642,0.404514,0.819444,0.618253,0.354246,0.374882,0.972932,0.582663,0.480508,0.629932,0.685369,0.663431,0.691604,0.67223,0.352904,0.805279,0.143821,0.579664,0.1948,0.29794,0.511324,0.577652,0.316525,0.633404,0.561001,0.143032,0.75801,0.11194,0.683988,0.027265,0.392045,0.909446,0.47968,0.825008,0.222854,0.427675,0.413116,0.806384,0.275726,0.957505,0.57047,0.389954,0.462792,0.287247,0.766493,0.065144,0.576113,0.397569,0.75142,0.704901,0.354246,0.722301,0.866911,0.555595,0.103022,0.635732,0.548887,0.382655,0.510851,0.672861,0.660354,0.700047,0.540128,0.790483,0.989149,0.965278,0.336687,0.682331,0.65191,0.447562,0.973248,0.856889,0.602312,0.384509,0.385614,0.18679,0.414536,0.596828,0.618134,0.559067,0.632773,0.723603,0.535985]
average_cost
0
kappa
0.014520202020202022
kb_relative_information_score
51.068279242135276
mean_absolute_error
0.019759386591557262
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
0.024375
prior_entropy
6.6438561897747395
recall
0.024375 [0.1875,0,0,0,0,0,0,0.0625,0,0,0,0,0,0,0,0,0.0625,0,0,0,0,0,0,0.4375,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0625,0.0625,0.75,0,0,0,0,0.8125,0,0,0,0,0,0,0,0,0,0,0,0]
relative_absolute_error
0.9979488177554154
root_mean_prior_squared_error
0.09949874371066209
root_mean_squared_error
0.09972642664858482
root_relative_squared_error
1.0022882996250166
total_cost
0
area_under_roc_curve
0.5268260886872064 [0.484277,0.28481,0.522152,0.389937,0.35443,0.698113,0.123418,0.836478,0.443038,0.037736,0.35443,0.170886,0.636076,0.148734,0.348101,0.874214,0.936709,0.610759,0.550633,0.874214,0.553459,0.201258,0.194969,0.981132,0.672956,0.189873,0.617089,0.636076,0.702532,0.496855,0.455696,0.287975,0.746835,0.177215,0.575949,0.081761,0.119497,0.666667,0.786164,0.253165,0.81761,0.861635,0.443038,0.829114,0.003165,0.759494,0.018868,0.09434,0.968354,0.708861,0.746835,0.227848,0.716981,0.420886,0.754717,0.08805,0.93038,0.396226,0.08805,0.689873,0.18239,0.484277,0.044304,0.629747,0.54717,0.829114,0.863924,0.163522,0.710692,0.962264,0.670886,0.044025,0.718354,0.699367,0.050314,0.278481,0.506329,0.746835,0.806962,0.737342,0.721519,0.993671,0.955975,0.333333,0.756329,0.613924,0.496835,0.987342,0.946203,0.339623,0.414557,0.201258,0.139241,0.25,0.531646,0.376582,0.339623,0.518987,0.594937,0.735849]
area_under_roc_curve
0.5497497213597644 [1,0.778481,0.452532,0.125786,0.278481,0.704403,0.218354,0.899371,0.398734,0.264151,0.75,0.129747,0.481013,0.768987,0.139241,0.867925,0.936709,0.408228,0.594937,0.698113,0.503145,0.849057,0.327044,0.974843,0.584906,0.411392,0.607595,0.835443,0.721519,0.188679,0.664557,0.31962,0.731013,0.03481,0.607595,0.08805,0.163522,0.779874,0.836478,0.088608,0.836478,0.283019,0.107595,0.860759,0.022152,0.734177,0.044025,0.578616,0.949367,0.414557,0.806962,0.379747,0.264151,0.332278,0.685535,0.125786,0.946203,0.308176,0.45283,0.487342,0.345912,0.937107,0.03481,0.64557,0.459119,0.867089,0.781646,0.496855,0.792453,0.918239,0.667722,0.044025,0.825949,0.639241,0.194969,0.518987,0.762658,0.93038,0.876582,0.132911,0.566456,0.990506,0.974843,0.402516,0.667722,0.787975,0.376582,0.968354,0.927215,0.880503,0.218354,0.213836,0.237342,0.417722,0.56962,0.468354,0.811321,0.639241,0.398734,0.421384]
area_under_roc_curve
0.5489667920547727 [0.901899,0.803797,0.379747,0.169811,0.443038,0.759494,0.415094,0.971519,0.455696,0.329114,0.582278,0.148734,0.327044,0.43038,0.151899,0.632911,0.892405,0.794304,0.773585,0.93038,0.446541,0.308176,0.262658,0.974843,0.767296,0.484177,0.772152,0.90566,0.791139,0.585443,0.591195,0.325949,0.759494,0.142405,0.515723,0.132075,0.471698,0.761006,0.849057,0.35443,0.566456,0.597484,0.062893,0.559748,0.053797,0.446541,0.006329,0.27673,0.648734,0.155063,0.968354,0.100629,0.345912,0.259494,0.811321,0.075949,0.949686,0.686709,0.748428,0.322785,0.150943,0.72327,0.060127,0.603774,0.357595,0.876582,0.81962,0.294304,0.974843,0.984177,0.439873,0.041139,0.610063,0.64557,0.572327,0.481013,0.544304,0.879747,0.768987,0.699367,0.861635,0.993671,0.990506,0.28481,0.320755,0.773585,0.496855,0.952532,0.832278,0.786164,0.462025,0.264151,0.044025,0.316456,0.626582,0.672956,0.436709,0.746835,0.955975,0.493671]
area_under_roc_curve
0.5343618143459916 [0.781646,0.332278,0.310127,0.125786,0.012658,0.724684,0.377358,0.89557,0.493671,0.120253,0.598101,0.142405,0.779874,0.341772,0.234177,0.905063,0.89557,0.705696,0.477987,0.708861,0.113208,0.289308,0.443038,0.993711,0.176101,0.481013,0.411392,0.748428,0.775316,0.601266,0.949686,0.351266,0.848101,0.142405,0.496855,0.069182,0.194969,0.427673,0.767296,0.193038,0.588608,0.767296,0.119497,0.754717,0.110759,0.679245,0.063291,0.163522,0.984177,0.275316,0.674051,0.666667,0.610063,0.458861,0.836478,0.208861,0.855346,0.588608,0.345912,0.591772,0.207547,0.188679,0.047468,0.603774,0.5,0.800633,0.886076,0.594937,0.440252,0.936709,0.560127,0.066456,0.974843,0.556962,0.566038,0.579114,0.566456,0.721519,0.373418,0.693038,0.811321,0.996835,0.974684,0.246835,0.704403,0.710692,0.761006,0.977848,0.756329,0.194969,0.335443,0.672956,0.408805,0.544304,0.734177,0.698113,0.670886,0.490506,0.603774,0.477848]
area_under_roc_curve
0.5499392962343762 [0.914557,0.264151,0.449367,0.227848,0.018868,0.775316,0.006289,0.943038,0.672956,0.199367,0.462025,0.205696,0.45283,0.830189,0.408805,0.886076,0.712025,0.610759,0.08805,0.825949,0.405063,0.265823,0.234177,0.984177,0.544304,0.474684,0.718354,0.742138,0.566038,0.927215,0.886792,0.251572,0.936709,0.21519,0.779874,0.158228,0.452532,0.389241,0.56962,0.199367,0.724684,0.186709,0.044025,0.968553,0.257862,0.691824,0.037975,0.294304,0.981013,0.550633,0.849057,0.176101,0.224684,0.45283,0.727848,0.14557,0.949686,0.648734,0.623418,0.27044,0.332278,0.810127,0.220126,0.779874,0.348101,0.876582,0.522013,0.313291,0.787975,0.851266,0.484177,0.281646,0.742138,0.465409,0.183544,0.320755,0.835443,0.977848,0.772152,0.679245,0.987421,0.977848,0.974684,0.373418,0.918239,0.842767,0.685535,0.955975,0.759494,0.531646,0.477987,0.506329,0,0.18239,0.556962,0.698113,0.370253,0.528302,0.899371,0.490506]
area_under_roc_curve
0.5529889140991958 [0.905063,0,0.417722,0.237342,0.188679,0.686709,0.069182,0.863924,0.377358,0.303797,0.702532,0.170886,0.779874,0.522013,0.320755,0.617089,0.946203,0.585443,0.823899,0.781646,0.360759,0.528481,0.35443,0.984177,0.613924,0.835443,0.522152,0.72956,0.496855,0.661392,0.842767,0.421384,0.550633,0.088608,0.874214,0.231013,0.212025,0.617089,0.468354,0.098101,0.756329,0.43038,0.194969,0.955975,0.295597,0.622642,0.018987,0.582278,0.905063,0.46519,0.993711,0.125786,0.452532,0.371069,0.740506,0.556962,0.955975,0.433544,0.338608,0.685535,0.351266,0.860759,0.138365,0.377358,0.256329,0.221519,0.616352,0.297468,0.800633,0.746835,0.547468,0.158228,0.735849,0.63522,0.443038,0.886792,0.686709,0.867089,0.610759,0.559748,0.949686,1,0.955696,0.455696,0.484277,0.767296,0.327044,0.993711,0.917722,0.882911,0.245283,0.275316,0.358491,0.754717,0.5,0.698113,0.762658,0.408805,0.855346,0.39557]
area_under_roc_curve
0.5412974683544302 [0.914557,0.27044,0.27673,0.43038,0.006289,0.75,0.231013,0.873418,0.54717,0.243671,0.603774,0.150943,0.829114,0.654088,0.213836,0.873418,0.886792,0.91195,0.079114,0.765823,0.705696,0.253165,0.582278,0.990506,0.626582,0.742138,0.446541,0.768987,0.660377,0.860759,0.379747,0.503145,0.90566,0.396226,0.727848,0.398734,0.481013,0.64557,0.623418,0.232704,0.696203,0.139241,0.075949,0.705696,0.062893,0.753165,0.003165,0.35443,0.949686,0.232704,0.968553,0.196203,0.35443,0.45283,0.822785,0.161392,0.984177,0.674051,0.382911,0.226415,0.117089,0.958861,0.031447,0.639241,0.281646,0.377358,0.597484,0.481013,0.879747,0.844937,0.408805,0.037975,0.601266,0.496855,0.259494,0.301887,0.628931,0.993711,0.823899,0.698113,0.996835,1,0.971519,0.376582,0.768987,0.607595,0.376582,0.993711,0.874214,0.110759,0.371069,0.351266,0.335443,0.779874,0.685535,0.43038,0.585443,0.63522,0.620253,0.332278]
area_under_roc_curve
0.5553364580845475 [0.892405,0.056604,0.515723,0.367089,0.081761,0.775316,0.199367,0.917722,0.383648,0.098101,0.773585,0.069182,0.433544,0.597484,0.320755,0.579114,0.685535,0.899371,0.335443,0.949367,0.702532,0.243671,0.411392,0.981013,0.613924,0.163522,0.63522,0.655063,0.893082,0.81962,0.496835,0.748428,0.867925,0.081761,0.699367,0.142405,0.148734,0.471519,0.623418,0.27044,0.781646,0.642405,0.028481,0.699367,0.194969,0.667722,0.009494,0.528481,0.761006,0.798742,0.993711,0.174051,0.623418,0.283019,0.800633,0.297468,0.96519,0.670886,0.677215,0.72327,0.224684,0.96519,0.018868,0.506329,0.443038,0.842767,0.962264,0.363924,0.886076,0.753165,0.566038,0.107595,0.740506,0.54717,0.525316,0.578616,0.559748,0.72956,0.805031,0.691824,0.914557,0.987421,0.946203,0.452532,0.639241,0.411392,0.325949,0.981132,0.861635,0.848101,0.226415,0.405063,0.174051,0.056604,0.767296,0.632911,0.370253,0.113208,0.879747,0.740506]
area_under_roc_curve
0.5449688022450443 [0.993711,0.155063,0.836478,0.424051,0.341772,0.81761,0.189873,0.176101,0.879747,0.006289,0.63522,0.232704,0.5,0.487342,0.278481,0.754717,0.748428,0.660377,0.300633,0.792453,0.889241,0.325949,0.591195,0.924051,0.503165,0.283019,0.72327,0.528481,0.541139,0.503145,0.892405,0.107595,0.893082,0.132075,0.601266,0.132911,0.240506,0.161392,0.142405,0.496855,0.383648,0.797468,0.189873,0.800633,0.25,0.806962,0,0.443038,0.974843,0.773585,0.658228,0.218354,0.246835,0.509494,0.981013,0.72956,0.996835,0.522013,0.348101,0.398734,0.411392,0.857595,0.018987,0.446203,0.408805,0.893082,0.689873,0.232704,0.746835,0.987421,0.484277,0.132075,0.712025,0.348101,0.174051,0.838608,0.937107,0.924528,0.503145,0.420886,0.990506,0.968553,0.987421,0.18239,0.689873,0.71519,0.506329,0.996835,0.861635,0.835443,0.560127,0.155063,0.212025,0.322785,0.792453,0.873418,0.415094,0.981013,0.806962,0.81761]
area_under_roc_curve
0.5457716344240108 [1,0.417722,0.628931,0.208861,0.041139,0.880503,0.139241,0.037736,0.93038,0.031447,0.257862,0,0.655063,0.313291,0.310127,0.333333,0.805031,0.213836,0.43038,0.974843,0.768987,0.642405,0.352201,0.993671,0.756329,0.383648,0.836478,0.620253,0.503165,0.924528,0.889241,0.436709,1,0.056604,0.626582,0.278481,0.373418,0.477848,0.636076,0.056604,0.679245,0.775316,0.113924,0.518987,0.056962,0.575949,0.012579,0.351266,0.968553,0.283019,0.857595,0.161392,0.515823,0.553797,0.832278,0.503145,0.977848,0.660377,0.303797,0.620253,0.398734,0.487342,0.107595,0.607595,0.515723,0.805031,0.901899,0.220126,0.316456,0.823899,0.767296,0.018868,0.601266,0.607595,0.531646,0.651899,0.666667,0.955975,0.622642,0.28481,0.993671,0.968553,0.955975,0.044025,0.689873,0.579114,0.405063,0.996835,0.830189,0.522152,0.455696,0.607595,0.047468,0.64557,0.251572,0.794304,0.943396,0.962025,0.85443,0.622642]
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
0.0026039611773060844
kappa
0.02173484280698986
kappa
0.014451551764984602
kappa
0.026702480644651604
kappa
0.015501124127322212
kappa
0.015268079062610962
kappa
0.009541834240201877
kappa
0.009307461744754693
kappa
0.00891659433441174
kappa
0.021387420093126035
kb_relative_information_score
4.310771352692405
kb_relative_information_score
4.973235713505513
kb_relative_information_score
5.740043745167367
kb_relative_information_score
5.33071120619258
kb_relative_information_score
5.022154287977711
kb_relative_information_score
5.243641648791545
kb_relative_information_score
4.7823423678805606
kb_relative_information_score
4.519367900253823
kb_relative_information_score
5.435344475146963
kb_relative_information_score
5.710666544526855
mean_absolute_error
0.019770535734159177
mean_absolute_error
0.019763471084247645
mean_absolute_error
0.019748054770706153
mean_absolute_error
0.019737180086614785
mean_absolute_error
0.019764758887294183
mean_absolute_error
0.0197551164931485
mean_absolute_error
0.019756216094124306
mean_absolute_error
0.019779309949569328
mean_absolute_error
0.019761358125088925
mean_absolute_error
0.019757864690619638
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
0.03125
predictive_accuracy
0.025
predictive_accuracy
0.0375
predictive_accuracy
0.025
predictive_accuracy
0.025
predictive_accuracy
0.01875
predictive_accuracy
0.01875
predictive_accuracy
0.01875
predictive_accuracy
0.03125
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 [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0]
recall
0.03125 [1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0]
recall
0.025 [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0.5,0,0,0,0,0,0,0,0,0,0,0,0]
recall
0.0375 [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.5,1,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0]
recall
0.025 [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.5,0,0,0,0,0,0,0.5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.5,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0]
recall
0.025 [0.5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.5,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0]
recall
0.01875 [0.5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]
recall
0.01875 [0,0,0,0,0,0,0,0.5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]
recall
0.01875 [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0]
recall
0.03125 [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.5,0,1,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0]
relative_absolute_error
0.9985119057656132
relative_absolute_error
0.9981551052650309
relative_absolute_error
0.9973765035710161
relative_absolute_error
0.9968272771017551
relative_absolute_error
0.9982201458229369
relative_absolute_error
0.9977331562196196
relative_absolute_error
0.9977886916224381
relative_absolute_error
0.9989550479580452
relative_absolute_error
0.9980483901560047
relative_absolute_error
0.9978719540716972
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
0.099787231496248
root_mean_squared_error
0.09976268147656854
root_mean_squared_error
0.09965330453272168
root_mean_squared_error
0.09961843057349312
root_mean_squared_error
0.09971652943219207
root_mean_squared_error
0.09964085463109182
root_mean_squared_error
0.0997554252536931
root_mean_squared_error
0.09982247478357006
root_mean_squared_error
0.09973386118186106
root_mean_squared_error
0.09977326376508572
root_relative_squared_error
1.0028994113375427
root_relative_squared_error
1.0026526743561106
root_relative_squared_error
1.0015533947092747
root_relative_squared_error
1.0012028982313497
root_relative_squared_error
1.0021888288576117
root_relative_squared_error
1.001428268489932
root_relative_squared_error
1.0025797465722528
root_relative_squared_error
1.00325361970247
root_relative_squared_error
1.002363019495831
root_relative_squared_error
1.002759030357428
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
51619.122276999406
usercpu_time_millis
51344.77216399955
usercpu_time_millis
51391.84886900057
usercpu_time_millis
51217.77390900024
usercpu_time_millis
51468.51283000069
usercpu_time_millis
51515.2197740008
usercpu_time_millis
51366.643163000845
usercpu_time_millis
51490.53986299987
usercpu_time_millis
51614.85585199898
usercpu_time_millis
51295.674287999645
usercpu_time_millis_testing
43.92520599958516
usercpu_time_millis_testing
43.43993299971771
usercpu_time_millis_testing
46.96090700053901
usercpu_time_millis_testing
43.05690599994705
usercpu_time_millis_testing
47.96277100012958
usercpu_time_millis_testing
41.00618200027384
usercpu_time_millis_testing
51.26068900062819
usercpu_time_millis_testing
43.68790699936653
usercpu_time_millis_testing
43.348790999516496
usercpu_time_millis_testing
46.97860899977968
usercpu_time_millis_training
51575.19707099982
usercpu_time_millis_training
51301.33223099983
usercpu_time_millis_training
51344.88796200003
usercpu_time_millis_training
51174.717003000296
usercpu_time_millis_training
51420.55005900056
usercpu_time_millis_training
51474.213592000524
usercpu_time_millis_training
51315.38247400022
usercpu_time_millis_training
51446.8519560005
usercpu_time_millis_training
51571.507060999465
usercpu_time_millis_training
51248.695678999866