6021907
1
Jan van Rijn
9954
Supervised Classification
6969
sklearn.pipeline.Pipeline(imputation=openmlstudy14.preprocessing.ConditionalImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,variencethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,classifier=sklearn.ensemble.forest.RandomForestClassifier)(1)
4056592
bootstrap
false
6902
class_weight
null
6902
criterion
"entropy"
6902
max_depth
null
6902
max_features
0.8786210683027665
6902
max_leaf_nodes
null
6902
min_impurity_split
1e-07
6902
min_samples_leaf
10
6902
min_samples_split
18
6902
min_weight_fraction_leaf
0.0
6902
n_estimators
100
6902
n_jobs
1
6902
oob_score
false
6902
random_state
33400
6902
verbose
0
6902
warm_start
false
6902
axis
0
6947
categorical_features
[]
6947
copy
true
6947
fill_empty
0
6947
missing_values
"NaN"
6947
strategy
"median"
6947
strategy_nominal
"most_frequent"
6947
verbose
0
6947
categorical_features
[]
6948
dtype
{"oml-python:serialized_object": "type", "value": "np.float64"}
6948
handle_unknown
"ignore"
6948
n_values
"auto"
6948
sparse
false
6948
threshold
0.0
6949
openml-pimp
openml-python
Sklearn_0.18.1.
study_71
1491
one-hundred-plants-margin
https://www.openml.org/data/download/1592283/phpCsX3fx
-1
12966933
description
https://api.openml.org/data/download/12966933/description.xml
-1
12966934
predictions
https://api.openml.org/data/download/12966934/predictions.arff
area_under_roc_curve
0.9789855587121213 [0.970683,0.993332,0.999724,0.998264,0.993174,0.978378,0.993371,0.960602,0.992898,0.997475,0.995818,0.993411,0.992306,0.961529,0.993411,0.983507,0.999053,0.960069,0.96583,0.9491,0.995107,0.993687,0.974195,1,0.984454,0.9506,0.956084,0.93604,0.994003,0.997909,0.99712,0.999053,0.988479,0.969934,0.991438,0.997238,0.968434,0.971275,0.997475,0.998737,0.96804,0.98907,0.997317,0.990017,0.986742,0.96149,0.998106,0.99053,0.958373,0.986427,0.976997,0.968947,0.991201,0.94334,0.945885,0.944642,1,0.995344,0.984848,0.937382,0.995778,0.985914,0.990491,0.985164,0.995344,0.989702,0.966343,0.998974,0.901772,0.945115,0.959576,0.964173,0.985717,0.986387,0.95782,0.956577,0.996962,0.948153,0.995147,0.996804,0.952671,0.977786,0.982876,0.982086,0.977865,0.951862,0.992582,0.974905,0.988242,0.992266,0.99779,0.997633,0.98331,0.971749,0.952967,0.990688,0.985322,0.982757,0.938881,0.974511]
average_cost
0
f_measure
0.4979321555449976 [0.387097,0.648649,0.903226,0.608696,0.685714,0.322581,0.5625,0.647059,0.387097,0.758621,0.526316,0.611111,0.470588,0.148148,0.628571,0.333333,0.722222,0.4,0.375,0.095238,0.645161,0.666667,0.461538,1,0.5,0.173913,0.342857,0.5,0.666667,0.685714,0.514286,0.8,0.5625,0.242424,0.727273,0.742857,0.322581,0.294118,0.8125,0.722222,0.5,0.473684,0.727273,0.5625,0.6875,0.357143,0.8,0.666667,0.222222,0.625,0.439024,0.277778,0.514286,0.153846,0.5,0.176471,0.888889,0.619048,0.285714,0.451613,0.451613,0.424242,0.432432,0.285714,0.606061,0.388889,0.193548,0.756757,0.222222,0.266667,0.129032,0.666667,0.411765,0.606061,0.153846,0.611111,0.75,0.181818,0.857143,0.666667,0.642857,0.258065,0.4375,0.375,0.457143,0.6875,0.521739,0.424242,0.272727,0.526316,0.666667,0.717949,0.482759,0.25,0.5,0.540541,0.588235,0.296296,0,0.551724]
kappa
0.5037878787878788
kb_relative_information_score
1060.2946945342048
mean_absolute_error
0.013220679549402732
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]
precision
0.5060289193348791 [0.4,0.571429,0.933333,1,0.631579,0.333333,0.5625,0.611111,0.4,0.846154,0.454545,0.55,0.444444,0.181818,0.578947,0.5,0.65,0.333333,0.375,0.2,0.666667,0.647059,0.391304,1,0.5,0.285714,0.315789,0.45,0.818182,0.631579,0.473684,0.736842,0.5625,0.235294,0.705882,0.684211,0.333333,0.277778,0.8125,0.65,0.5,0.409091,0.705882,0.5625,0.6875,0.416667,0.857143,0.714286,0.272727,0.625,0.36,0.25,0.473684,0.2,0.5,0.166667,0.8,0.5,0.333333,0.466667,0.466667,0.411765,0.380952,0.333333,0.588235,0.35,0.2,0.666667,0.2,0.285714,0.133333,0.647059,0.388889,0.588235,0.2,0.55,0.75,0.333333,1,0.714286,0.75,0.266667,0.4375,0.375,0.421053,0.6875,0.857143,0.411765,0.5,0.454545,0.6,0.608696,0.538462,0.375,0.583333,0.47619,0.555556,0.363636,0,0.615385]
predictive_accuracy
0.50875
prior_entropy
6.6438561897747395
recall
0.50875 [0.375,0.75,0.875,0.4375,0.75,0.3125,0.5625,0.6875,0.375,0.6875,0.625,0.6875,0.5,0.125,0.6875,0.25,0.8125,0.5,0.375,0.0625,0.625,0.6875,0.5625,1,0.5,0.125,0.375,0.5625,0.5625,0.75,0.5625,0.875,0.5625,0.25,0.75,0.8125,0.3125,0.3125,0.8125,0.8125,0.5,0.5625,0.75,0.5625,0.6875,0.3125,0.75,0.625,0.1875,0.625,0.5625,0.3125,0.5625,0.125,0.5,0.1875,1,0.8125,0.25,0.4375,0.4375,0.4375,0.5,0.25,0.625,0.4375,0.1875,0.875,0.25,0.25,0.125,0.6875,0.4375,0.625,0.125,0.6875,0.75,0.125,0.75,0.625,0.5625,0.25,0.4375,0.375,0.5,0.6875,0.375,0.4375,0.1875,0.625,0.75,0.875,0.4375,0.1875,0.4375,0.625,0.625,0.25,0,0.5]
relative_absolute_error
0.6677110883536721
root_mean_prior_squared_error
0.09949874371066209
root_mean_squared_error
0.0788504464677573
root_relative_squared_error
0.7924768045016818
total_cost
0
area_under_roc_curve
0.9822664148953107 [0.993711,0.996835,1,1,0.996835,1,1,1,1,1,0.996835,0.984177,0.987342,0.974684,1,1,1,0.939873,0.955696,0.962264,1,0.993711,0.993711,1,1,0.977848,0.990506,0.993671,1,1,0.996835,1,1,0.96519,1,0.993711,1,0.993711,1,1,1,1,1,1,1,0.993671,1,1,0.946203,0.981013,0.901899,1,1,0.943038,1,0.981132,1,1,0.981132,0.949367,0.993711,1,0.974684,0.962025,1,1,0.993671,1,0.981132,0.981132,0.933544,1,0.990506,0.981013,1,1,1,0.990506,1,1,1,0.977848,1,1,0.977848,0.697785,1,0.984177,1,0.955975,0.990506,1,1,0.974684,0.993671,0.981013,1,0.987342,0.816456,1]
area_under_roc_curve
0.9804441823899369 [0.981132,1,1,1,0.993671,1,0.977848,1,0.993671,1,1,0.996835,0.993671,0.878165,1,1,1,0.924051,0.990506,0.987421,1,0.968553,0.987421,1,1,0.917722,0.981013,0.656646,1,1,1,1,1,0.977848,1,1,0.899371,1,0.993711,1,0.981132,1,1,1,1,0.987342,0.993711,0.993711,0.977848,1,0.996835,0.958861,1,0.990506,1,0.90566,1,1,0.987421,0.908228,1,0.993711,1,0.990506,1,0.993671,0.984177,0.993711,0.81761,0.987421,0.981013,1,0.981013,1,0.993711,1,1,0.933544,1,1,0.987342,0.984177,0.968553,0.949686,0.987342,0.990506,0.968354,0.990506,0.974684,0.987421,0.996835,1,1,0.981013,0.984177,0.993671,1,0.968354,0.977848,1]
area_under_roc_curve
0.9781889379826453 [0.971519,0.996835,1,1,0.990506,0.968354,0.993711,1,0.990506,1,0.984177,1,1,0.987342,0.981013,0.955696,1,0.958861,0.855346,0.89557,1,0.981132,0.927215,1,0.893082,1,0.990506,0.993711,1,1,1,1,1,0.933544,0.937107,1,1,0.930818,1,1,0.977848,1,1,1,0.990506,0.924528,0.996835,1,0.85443,0.990506,0.987342,1,1,0.952532,1,0.990506,1,0.996835,0.987421,0.658228,1,0.987421,0.996835,1,0.990506,0.977848,0.977848,0.996835,0.968553,0.939873,0.993671,0.996835,0.987421,0.987342,0.962264,1,1,0.917722,0.974684,1,0.993711,0.996835,0.996835,0.990506,1,1,1,0.996835,0.996835,1,0.996835,1,0.993711,0.96519,0.996835,1,0.987342,0.977848,0.993711,0.984177]
area_under_roc_curve
0.9718170328795479 [1,1,1,1,0.990506,0.933544,1,0.996835,0.987342,0.993671,0.996835,0.996835,1,0.993671,1,1,0.996835,0.968354,0.874214,0.952532,0.987421,1,0.990506,1,0.930818,0.974684,0.893987,1,0.996835,0.996835,1,1,1,0.984177,1,0.974843,1,0.974843,1,1,0.971519,1,1,0.993711,1,1,1,1,0.971519,1,0.996835,1,0.987421,0.867089,1,0.993671,1,1,1,0.993671,1,0.993711,0.971519,1,0.990506,0.987342,0.943038,1,0.987421,0.946203,0.949367,0.732595,0.993711,1,0.968553,0.705696,1,0.911392,1,0.987342,0.40566,0.949367,1,0.949367,1,1,1,1,0.987342,0.993711,1,1,0.949686,0.962025,1,0.981132,0.981013,0.984177,0.968553,0.886076]
area_under_roc_curve
0.9715082895470104 [0.974684,1,1,1,0.993711,0.968354,0.968553,1,0.987421,0.996835,0.987342,0.984177,1,0.861635,1,0.990506,1,1,0.993711,0.996835,0.974684,0.977848,1,1,0.996835,0.924051,0.968354,1,1,0.993671,1,1,0.987342,0.924051,1,1,0.981013,0.927215,0.987342,1,1,0.993671,0.981132,1,1,0.974843,1,0.987342,0.993671,0.968354,0.974843,0.861635,1,0.968553,0.691456,0.908228,1,0.984177,0.993671,0.981132,1,0.996835,1,1,0.993671,0.993671,0.90566,1,0.648734,0.917722,0.990506,1,1,0.974843,0.955696,1,0.996835,0.917722,1,0.993711,0.993711,1,0.987342,0.987342,0.981132,1,1,1,1,1,1,0.990506,0.937107,0.993711,0.688291,1,0.977848,0.993711,0.949686,0.981013]
area_under_roc_curve
0.980971732943237 [0.924051,1,1,1,1,0.990506,1,1,0.993711,0.993671,0.996835,1,1,0.955975,1,0.996835,1,0.996835,0.993711,0.89557,1,0.996835,0.927215,1,0.987342,0.987342,0.958861,1,1,1,1,1,0.93038,0.987342,0.937107,1,0.911392,0.977848,1,1,1,0.968354,1,1,1,0.987421,1,0.996835,0.96519,0.974684,1,1,1,1,0.96519,0.914557,1,1,1,1,0.990506,0.987342,0.962264,1,0.996835,0.993671,0.955975,1,0.949367,1,0.887658,0.990506,1,1,0.876582,1,0.993671,0.968354,1,0.981132,1,0.971519,1,0.949367,0.924528,1,0.993711,0.949686,0.971519,1,1,1,0.968553,1,0.993671,1,0.984177,0.974843,0.955975,0.962025]
area_under_roc_curve
0.9837266638802641 [0.987342,0.993711,1,0.990506,1,1,1,1,0.987421,0.996835,1,1,0.974684,0.981132,1,0.987342,0.987421,0.91195,0.936709,0.987342,0.987342,0.996835,0.990506,1,0.984177,0.867925,0.987421,0.908228,1,1,1,1,1,0.987421,1,1,0.990506,0.984177,1,0.987421,0.984177,0.987342,0.996835,1,1,0.996835,0.993671,0.981013,0.993711,1,1,0.981013,0.993671,0.955975,0.987342,0.96519,1,0.990506,0.990506,0.981132,0.993671,0.96519,1,0.971519,0.993671,0.987421,0.91195,1,0.892405,0.908228,0.993711,1,0.981013,1,0.968354,0.993711,1,0.993711,1,1,0.990506,1,0.949367,1,1,1,0.987342,0.930818,1,0.996835,1,1,0.987342,0.993711,0.968553,0.971519,1,0.993711,0.89557,1]
area_under_roc_curve
0.9819941187007402 [1,1,1,1,1,0.984177,1,1,1,1,0.993711,0.993711,0.993671,0.987421,0.993711,0.955696,1,0.924528,0.987342,0.914557,0.993671,0.996835,0.977848,1,1,0.937107,0.811321,0.971519,1,0.990506,0.981013,1,1,1,0.993671,1,0.958861,0.984177,1,1,1,0.987342,1,0.977848,1,0.981013,1,1,0.974843,1,0.981132,0.952532,0.977848,1,0.971519,0.939873,1,1,0.971519,1,1,0.962025,0.987421,0.993671,1,0.974843,0.987421,1,0.946203,0.911392,0.955975,1,1,0.836478,0.971519,1,1,0.962264,1,1,0.977848,1,0.958861,1,0.943038,0.952532,1,0.937107,1,0.990506,1,1,1,0.962264,0.987421,1,0.987342,1,0.949367,0.977848]
area_under_roc_curve
0.9864212642305548 [0.918239,1,1,1,1,0.993711,0.987342,0.993711,0.993671,1,0.993711,1,0.990506,0.996835,1,0.993711,1,0.993711,1,1,1,1,1,1,1,0.962264,0.893082,1,0.981013,1,1,1,0.993711,0.993711,1,1,0.984177,0.971519,1,1,0.81761,0.977848,1,0.981013,0.936709,0.933544,1,0.987342,0.91195,1,1,0.993671,1,0.876582,0.987342,0.968553,1,0.993711,0.977848,0.987342,1,1,0.996835,1,1,1,0.984177,1,0.936709,0.987421,1,0.987421,0.977848,1,0.977848,0.968354,1,0.993711,1,0.993671,1,0.987421,0.974843,0.974843,0.996835,1,1,0.981013,0.987421,1,1,0.993671,1,0.958861,1,0.981013,0.955975,1,0.987342,1]
area_under_roc_curve
0.9839873915293367 [0.974843,0.952532,0.993711,1,1,0.993711,1,0.389937,0.990506,1,1,1,0.993671,0.987342,0.996835,1,1,1,0.990506,1,1,1,1,1,1,0.886792,1,0.987342,0.993671,1,0.996835,1,1,0.981132,0.996835,0.993671,0.962025,1,1,1,0.968553,0.996835,1,0.974684,1,0.898734,1,0.984177,1,0.993711,0.996835,0.962025,1,0.971519,0.962025,0.90566,1,0.993711,0.962025,1,1,0.977848,0.987342,0.981013,1,1,0.984177,1,0.990506,0.949686,0.930818,1,0.96519,1,0.952532,0.996835,1,0.987421,0.955975,0.996835,1,0.962264,1,0.955975,0.993671,1,0.984177,0.990506,0.974843,0.996835,1,1,1,0.977848,1,1,1,1,0.993671,1]
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
0.5136586136112428
kappa
0.5454007339883983
kappa
0.48837392917768746
kappa
0.4820166607446011
kappa
0.5010263698089372
kappa
0.4759687475337385
kappa
0.4442909578876742
kappa
0.46312963840202115
kappa
0.5452751243388333
kappa
0.5767195767195767
kb_relative_information_score
107.93161355764991
kb_relative_information_score
107.45255656851482
kb_relative_information_score
103.87913635593623
kb_relative_information_score
102.77406205945545
kb_relative_information_score
103.11024527157612
kb_relative_information_score
104.07397356272449
kb_relative_information_score
105.58206332505355
kb_relative_information_score
104.39623993962401
kb_relative_information_score
110.29872474329716
kb_relative_information_score
110.79607915037542
mean_absolute_error
0.012928159060812797
mean_absolute_error
0.013057474809251377
mean_absolute_error
0.013248130359121571
mean_absolute_error
0.013522513199379962
mean_absolute_error
0.013527254903641896
mean_absolute_error
0.01328684203830445
mean_absolute_error
0.013581407876174244
mean_absolute_error
0.013462378842509327
mean_absolute_error
0.012826588443204234
mean_absolute_error
0.012766045961627781
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
0.51875
predictive_accuracy
0.55
predictive_accuracy
0.49375
predictive_accuracy
0.4875
predictive_accuracy
0.50625
predictive_accuracy
0.48125
predictive_accuracy
0.45
predictive_accuracy
0.46875
predictive_accuracy
0.55
predictive_accuracy
0.58125
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
0.51875 [1,1,1,0,0.5,1,0.5,1,0,1,1,0.5,0,0,1,1,1,0,0,0,1,0,1,1,0,0,0.5,0.5,0.5,0,1,1,0.5,0,1,0,0,1,0,1,1,0,1,1,1,0.5,1,1,0,0.5,0.5,0.5,1,0,1,0,1,1,0,0.5,0,1,0,0,1,0.5,0,1,0,0,0,1,0.5,0.5,1,1,0.5,0.5,0.5,0.5,1,0,1,1,0.5,0.5,0,0.5,0,0,1,1,1,0,0.5,0.5,1,0,0,1]
recall
0.55 [1,1,1,1,1,1,0.5,1,0.5,1,1,1,0.5,0.5,1,1,1,0,0.5,0,1,0,0,1,1,0.5,0.5,0,0.5,1,0.5,1,0.5,0.5,1,1,0,0,0,1,0,1,1,0.5,0.5,0,1,1,0,1,0,0.5,1,0.5,1,0,1,1,0,0.5,1,1,1,0.5,1,0.5,0.5,1,0,0,0,1,0.5,0.5,0,1,0.5,0,1,0.5,0.5,0,0,0,0.5,0.5,0.5,0.5,0,0,0.5,1,0.5,0,0,0.5,1,0,0,1]
recall
0.49375 [0,0.5,1,1,0.5,0,0,1,0.5,0.5,0.5,0.5,1,0,0,0,1,0.5,0,0,1,0,0,1,0,0.5,0,1,1,1,0,1,1,0,0,1,1,0,1,1,0,1,1,1,0,0,0.5,1,0.5,0.5,1,1,0,0,1,0.5,1,1,0,0,0,0,0.5,1,0.5,0.5,0,1,0,0,0.5,1,0,0.5,0,0.5,1,0,0.5,1,0,0,1,0.5,1,0,1,1,0.5,1,0.5,1,0,0,0.5,1,0.5,0.5,0,0.5]
recall
0.4875 [0.5,1,1,1,0.5,0,1,0.5,0,0,1,0.5,0,0,1,0,0.5,0.5,0,0,0,1,0.5,1,0,0,0.5,0,0.5,0.5,1,1,0.5,0.5,1,0,1,0,1,1,0.5,0,1,1,1,1,0.5,1,0,1,0,1,0,0,1,1,1,1,0,0.5,1,0,1,0,0.5,0.5,0.5,1,0,0.5,0,0,0,1,0,0.5,1,0,1,0.5,0,0,1,0,0,0,1,0.5,0,1,1,1,0,0,1,0,0.5,0,0,0]
recall
0.50625 [0.5,1,0.5,1,0,0.5,0,0,0,1,0,0.5,1,0,1,0,0.5,1,1,0,0,0.5,1,1,0.5,0,0.5,1,1,0.5,1,1,0,0,0,1,0.5,0,0.5,1,1,0.5,0,1,1,0,1,0,0.5,0.5,0,0,0,0,0.5,0,1,0.5,1,0,1,1,1,0,0.5,0,0,1,0,0,0,0.5,1,0,0,1,0.5,0,0.5,1,1,1,0,0.5,0,1,1,1,1,1,1,1,0,1,0.5,1,0.5,1,0,0.5]
recall
0.48125 [0,1,1,0,1,0,1,0.5,1,0.5,0.5,1,1,0,1,0.5,1,1,0,0,1,0.5,0.5,1,0.5,0,0.5,1,1,1,0,1,0.5,0,0,1,0,0.5,1,0.5,1,0.5,1,1,1,0,1,0.5,0,0.5,1,0,0.5,0,0,0,1,1,0.5,1,0.5,0,0,0,0.5,0.5,0,1,0.5,0.5,0,1,1,1,0,0,0.5,0,1,0,1,0,0,0,0,1,0,0,0,1,1,0.5,0,0,0,0,0.5,0,0,0.5]
recall
0.45 [0.5,0,1,0,1,0,1,1,1,0.5,1,1,0.5,0,0,0,0,0,0,0,0.5,1,0.5,1,0.5,0,0,0.5,0,1,0.5,0,1,1,1,0.5,0,0.5,1,0,0,0.5,1,0,1,0,0,0.5,0,1,1,0,0.5,0,0.5,0,1,1,0.5,0,0,0,0,0,0,1,0,1,0.5,0,0,1,0,0,0,1,1,0,1,1,0.5,1,0.5,0.5,1,1,0,0,0,0,1,1,0.5,1,0,0.5,1,0,0,0.5]
recall
0.46875 [0.5,1,1,0,1,0.5,1,1,1,1,0,0,0,0,0,0,1,0,0,0,0,1,0.5,1,0.5,0,0,0.5,1,0.5,0,1,1,1,0.5,1,0.5,0,1,1,1,0.5,1,0,1,0.5,1,1,0,0,0,0,0.5,1,0.5,0,1,0.5,0,1,0,0.5,0,0.5,1,0,0,0.5,0,0.5,0,1,1,0,0,1,1,0,1,0,0,0,0,1,0,0.5,1,0,0,0.5,0,1,0,0,0,1,0.5,0,0,0.5]
recall
0.55 [0,1,1,0.5,1,1,0.5,1,0,1,0,1,0.5,0.5,1,0,1,1,1,0,1,1,1,1,0.5,0,0,1,0.5,1,1,1,0,0,1,1,0.5,0,1,0,0,0.5,0,0.5,0,0.5,1,0.5,0,1,1,0,1,0,0,0,1,0,0,0,0,1,1,0,1,1,0.5,0,0.5,1,1,0,0.5,1,0,0.5,1,1,1,0.5,1,1,0,0,0.5,1,0,0,0,1,1,0.5,0.5,0,1,0.5,0,0.5,0,1]
recall
0.58125 [0,0,0,0.5,1,0,0,0,0.5,1,1,1,1,0,0.5,1,1,1,1,1,1,1,1,1,1,0,1,0.5,0,1,0.5,0.5,1,0,1,1,0,1,1,1,0,1,0.5,0.5,1,0.5,1,0.5,1,0,1,0.5,1,0,0.5,0,1,1,0,1,1,0,0,0.5,1,0,0,1,0.5,0,0,0,0,1,0.5,0.5,1,0,0,1,0.5,0,1,0,1,1,0,0.5,0,0.5,0.5,1,1,0.5,1,1,1,0.5,0,0]
relative_absolute_error
0.6529373263036756
relative_absolute_error
0.6594684247096645
relative_absolute_error
0.6690974928849266
relative_absolute_error
0.682955212089896
relative_absolute_error
0.6831946921031249
relative_absolute_error
0.6710526281971932
relative_absolute_error
0.6859296907158697
relative_absolute_error
0.6799181233590558
relative_absolute_error
0.6478074971315259
relative_absolute_error
0.644749796041806
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
0.0776551747280369
root_mean_squared_error
0.07738071192688813
root_mean_squared_error
0.07972842375967955
root_mean_squared_error
0.08016698578304148
root_mean_squared_error
0.08023374528273587
root_mean_squared_error
0.08012756914249684
root_mean_squared_error
0.08071110480259011
root_mean_squared_error
0.07961445053828126
root_mean_squared_error
0.0765106233037278
root_mean_squared_error
0.07620998167221041
root_relative_squared_error
0.7804638715223854
root_relative_squared_error
0.7777054165820205
root_relative_squared_error
0.8013008082948894
root_relative_squared_error
0.8057085224730427
root_relative_squared_error
0.8063794806902491
root_relative_squared_error
0.8053123703300642
root_relative_squared_error
0.811177124379524
root_relative_squared_error
0.8001553343205674
root_relative_squared_error
0.768960696892991
root_relative_squared_error
0.7659391348078288
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
10216.971712000486
usercpu_time_millis
10148.971959000392
usercpu_time_millis
9979.357241999878
usercpu_time_millis
10009.477985000103
usercpu_time_millis
10058.693259999927
usercpu_time_millis
10101.40205000016
usercpu_time_millis
10024.835478000114
usercpu_time_millis
10093.906325999797
usercpu_time_millis
10118.166645000201
usercpu_time_millis
10103.89330199996
usercpu_time_millis_testing
37.83088900036091
usercpu_time_millis_testing
40.38142500030517
usercpu_time_millis_testing
36.458917999880214
usercpu_time_millis_testing
34.88248099984048
usercpu_time_millis_testing
35.191152000152215
usercpu_time_millis_testing
36.239484999896376
usercpu_time_millis_testing
35.069948000000295
usercpu_time_millis_testing
39.608910999959335
usercpu_time_millis_testing
35.98096799987616
usercpu_time_millis_testing
35.66412800000762
usercpu_time_millis_training
10179.140823000125
usercpu_time_millis_training
10108.590534000086
usercpu_time_millis_training
9942.898323999998
usercpu_time_millis_training
9974.595504000263
usercpu_time_millis_training
10023.502107999775
usercpu_time_millis_training
10065.162565000264
usercpu_time_millis_training
9989.765530000113
usercpu_time_millis_training
10054.297414999837
usercpu_time_millis_training
10082.185677000325
usercpu_time_millis_training
10068.229173999953