6001851
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)
4036583
bootstrap
false
6902
class_weight
null
6902
criterion
"entropy"
6902
max_depth
null
6902
max_features
0.3724528793077694
6902
max_leaf_nodes
null
6902
min_impurity_split
1e-07
6902
min_samples_leaf
1
6902
min_samples_split
6
6902
min_weight_fraction_leaf
0.0
6902
n_estimators
100
6902
n_jobs
1
6902
oob_score
false
6902
random_state
3854
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
"mean"
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
12926815
description
https://api.openml.org/data/download/12926815/description.xml
-1
12926816
predictions
https://api.openml.org/data/download/12926816/predictions.arff
area_under_roc_curve
0.9960327888257575 [0.992227,0.999842,1,1,0.999842,0.995048,0.999921,0.999684,0.998264,0.999803,0.999448,1,0.999211,0.986959,1,0.999882,0.999921,0.984612,0.9869,0.98183,0.999605,1,0.997751,1,0.998974,0.973248,0.991221,0.998619,0.99925,0.999842,0.999961,1,0.999684,0.987433,0.999211,0.999132,0.990866,0.989149,0.997948,0.999921,0.999132,0.999763,1,0.999487,0.999566,0.999566,0.999566,0.998698,0.995147,0.996449,0.997633,0.996173,0.997869,0.989189,0.997711,0.983862,1,0.999842,0.996607,0.990747,1,0.999566,0.995423,0.99779,0.999448,0.99637,0.982659,0.999961,0.991477,0.990787,0.994949,0.998619,0.994555,0.999724,0.95492,0.999527,1,0.994022,1,0.999842,0.99562,0.996646,0.998501,0.995896,0.997988,0.998343,1,0.994121,0.999132,1,0.999882,0.999605,0.998698,0.996962,0.999684,0.999645,0.997948,0.996488,0.967448,0.998816]
average_cost
0
f_measure
0.8199075247674662 [0.709677,0.864865,1,1,0.967742,0.740741,0.969697,0.9375,0.909091,0.967742,0.866667,0.969697,0.823529,0.709677,1,0.933333,0.941176,0.709677,0.611111,0.26087,0.882353,1,0.875,1,0.810811,0.357143,0.421053,0.833333,0.875,0.941176,0.9375,1,0.909091,0.666667,0.9375,0.909091,0.451613,0.564103,0.857143,0.969697,0.75,0.9375,1,0.888889,0.941176,0.866667,0.827586,0.866667,0.8,0.903226,0.8,0.689655,0.787879,0.62069,0.8125,0.375,1,0.969697,0.648649,0.666667,0.969697,0.857143,0.666667,0.857143,0.848485,0.882353,0.518519,0.914286,0.709677,0.615385,0.642857,0.774194,0.628571,0.941176,0.8125,0.967742,0.969697,0.692308,1,0.967742,0.733333,0.709677,0.866667,0.709677,0.848485,0.933333,0.969697,0.764706,0.787879,1,0.914286,0.823529,0.9375,0.72,0.9375,0.8125,0.823529,0.764706,0.615385,0.83871]
kappa
0.8219696969696969
kb_relative_information_score
1237.1687578128126
mean_absolute_error
0.01145354583333299
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
0.8269917673130922 [0.733333,0.761905,1,1,1,0.909091,0.941176,0.9375,0.882353,1,0.928571,0.941176,0.777778,0.733333,1,1,0.888889,0.733333,0.55,0.428571,0.833333,1,0.875,1,0.714286,0.416667,0.363636,0.75,0.875,0.888889,0.9375,1,0.882353,0.714286,0.9375,0.882353,0.466667,0.478261,0.789474,0.941176,0.75,0.9375,1,0.8,0.888889,0.928571,0.923077,0.928571,0.736842,0.933333,0.857143,0.769231,0.764706,0.692308,0.8125,0.375,1,0.941176,0.571429,0.714286,0.941176,0.789474,0.714286,0.789474,0.823529,0.833333,0.636364,0.842105,0.733333,0.8,0.75,0.8,0.578947,0.888889,0.8125,1,0.941176,0.9,1,1,0.785714,0.733333,0.928571,0.733333,0.823529,1,0.941176,0.722222,0.764706,1,0.842105,0.777778,0.9375,1,0.9375,0.8125,0.777778,0.722222,0.8,0.866667]
predictive_accuracy
0.82375
prior_entropy
6.6438561897747395
recall
0.82375 [0.6875,1,1,1,0.9375,0.625,1,0.9375,0.9375,0.9375,0.8125,1,0.875,0.6875,1,0.875,1,0.6875,0.6875,0.1875,0.9375,1,0.875,1,0.9375,0.3125,0.5,0.9375,0.875,1,0.9375,1,0.9375,0.625,0.9375,0.9375,0.4375,0.6875,0.9375,1,0.75,0.9375,1,1,1,0.8125,0.75,0.8125,0.875,0.875,0.75,0.625,0.8125,0.5625,0.8125,0.375,1,1,0.75,0.625,1,0.9375,0.625,0.9375,0.875,0.9375,0.4375,1,0.6875,0.5,0.5625,0.75,0.6875,1,0.8125,0.9375,1,0.5625,1,0.9375,0.6875,0.6875,0.8125,0.6875,0.875,0.875,1,0.8125,0.8125,1,1,0.875,0.9375,0.5625,0.9375,0.8125,0.875,0.8125,0.5,0.8125]
relative_absolute_error
0.5784619107743924
root_mean_prior_squared_error
0.09949874371066209
root_mean_squared_error
0.06573324174372441
root_relative_squared_error
0.6606439367201837
total_cost
0
area_under_roc_curve
0.9954932429742858 [1,1,1,1,1,1,1,1,0.996835,1,1,1,1,1,1,1,1,0.974684,0.987342,0.987421,1,1,0.993711,1,0.993711,0.990506,0.993671,1,1,1,0.996835,1,1,0.987342,1,0.993711,1,0.993711,1,1,1,1,1,1,1,1,1,1,1,0.987342,0.981013,1,1,0.993671,1,1,1,1,1,0.996835,1,1,1,1,1,1,0.990506,1,1,0.968553,0.990506,1,0.993671,1,1,1,1,0.996835,1,1,1,1,1,1,0.996835,0.990506,1,0.996835,1,1,1,1,1,0.990506,1,1,1,0.996835,0.844937,1]
area_under_roc_curve
0.9964055409601146 [1,1,1,1,1,1,1,1,1,1,1,1,0.996835,0.984177,1,1,1,0.96519,1,0.993711,1,1,1,1,1,0.958861,0.990506,0.993671,1,1,1,1,1,1,1,1,0.981132,1,1,1,1,1,1,1,1,1,1,1,0.993671,1,1,0.977848,1,0.996835,1,0.974843,1,1,1,0.96519,1,1,1,0.996835,1,1,1,1,0.937107,1,1,1,1,1,1,1,1,0.981013,1,0.996835,0.993671,1,0.987421,0.993711,1,1,1,0.996835,1,1,1,1,1,0.993671,1,1,1,0.996835,1,1]
area_under_roc_curve
0.99642544383409 [1,1,1,1,1,0.993671,1,1,0.996835,1,1,1,1,1,1,1,1,0.993671,1,0.955696,1,1,0.990506,1,1,0.977848,1,1,1,1,1,1,1,0.968354,1,1,0.993711,0.974843,1,1,1,1,1,1,1,1,1,1,0.976266,1,1,1,1,0.996835,1,0.996835,1,1,0.987421,0.981013,1,1,1,1,1,1,0.987342,1,0.962264,0.990506,1,1,0.993711,1,1,1,1,0.985759,1,1,1,0.996835,1,1,1,1,1,1,1,1,1,1,1,0.996835,1,1,1,0.996835,0.95283,1]
area_under_roc_curve
0.9958111913860364 [1,0.996835,1,1,1,0.984177,1,1,0.996835,1,1,1,1,1,1,1,1,0.987342,0.930818,0.984177,1,1,1,1,1,0.974684,0.977848,1,1,1,1,1,1,0.984177,1,0.993711,1,1,1,1,1,1,1,1,1,1,1,1,0.996835,1,1,1,1,0.981013,1,0.990506,1,1,1,0.984177,1,1,0.996835,1,0.996835,0.996835,0.955696,1,1,0.974684,0.984177,0.996835,0.981132,1,1,1,1,1,1,1,0.993711,1,1,0.993671,1,1,1,1,1,1,1,1,0.993711,1,1,1,0.990506,0.996835,1,0.996835]
area_under_roc_curve
0.9911081422657432 [0.993671,1,1,1,1,0.996835,1,1,1,1,1,1,1,0.899371,1,1,1,1,1,0.990506,0.996835,1,1,1,1,0.977848,0.990506,1,1,1,1,1,1,0.962025,1,1,0.996835,0.962025,1,1,1,1,1,1,1,1,1,1,1,1,0.993711,0.981132,0.993671,0.993711,0.974684,0.971519,1,0.996835,1,1,1,1,1,1,0.996835,1,0.962264,1,0.977848,0.977848,1,1,1,1,0.677215,1,1,0.981013,1,1,1,1,1,0.993671,0.981132,1,1,1,1,1,1,0.996835,1,0.993711,0.996835,1,0.996835,1,0.981132,0.996835]
area_under_roc_curve
0.9964421124910438 [0.955696,1,1,1,1,0.993671,1,1,1,1,1,1,1,1,1,1,1,1,1,0.952532,1,1,0.993671,1,0.996835,0.996835,0.981013,0.993711,1,1,1,1,0.993671,0.993671,0.993711,1,0.977848,0.996835,1,1,1,1,1,1,1,1,1,1,1,0.981013,1,1,1,1,1,0.984177,1,1,0.990506,1,1,1,0.987421,1,1,1,1,1,1,1,0.990506,1,1,1,0.981013,1,1,1,1,1,1,0.993671,1,0.993671,1,1,1,0.993711,1,1,1,1,1,1,1,1,1,0.981132,0.993711,0.996835]
area_under_roc_curve
0.9971198053498925 [1,1,1,1,1,1,1,1,1,1,1,1,0.996835,0.993711,1,1,1,0.993711,0.993671,0.977848,1,1,1,1,0.996835,0.90566,0.993711,0.993671,1,1,1,1,1,1,1,1,0.993671,1,1,1,1,1,1,1,1,0.993671,1,0.990506,1,1,1,1,1,1,0.996835,0.990506,1,1,0.993671,0.993711,1,1,1,0.971519,1,1,0.987421,1,1,1,1,1,1,1,1,1,1,1,1,1,0.990506,1,1,1,1,1,1,0.943396,1,1,1,1,0.996835,1,1,1,1,1,0.987342,1]
area_under_roc_curve
0.9966866690550112 [1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.996835,1,0.993711,0.987342,0.996835,1,1,1,1,1,0.924528,0.993711,1,0.987421,0.996835,1,1,1,1,1,1,0.981013,1,1,1,1,1,1,1,1,1,1,1,1,1,0.993711,1,0.993671,1,1,0.971519,1,1,1,0.993711,1,0.996835,1,1,1,0.949686,0.955975,1,0.993671,0.993671,1,1,1,1,0.996835,1,1,1,1,1,0.981013,0.993711,0.996835,1,0.993671,0.990506,1,0.987421,1,1,1,1,1,0.987421,1,1,0.993671,1,0.993671,1]
area_under_roc_curve
0.9973544104768728 [0.968553,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.993711,0.993711,1,1,1,1,1,1,1,1,1,1,0.962025,1,1,0.993711,1,1,0.996835,1,1,1,1,0.987421,1,1,1,1,0.971519,0.996835,0.981132,1,1,1,1,1,1,0.993671,1,1,1,0.990506,1,1,0.993711,1,0.987421,0.984177,1,1,0.996835,1,1,1,0.996835,1,1,1,1,1,1,1,1,0.993711,1,1,0.996835,1,1,1,1,0.987421,1,0.962025,1]
area_under_roc_curve
0.9977489849534271 [0.993711,1,1,1,1,1,1,0.993711,1,1,1,1,1,0.96519,1,1,1,1,0.977848,1,1,1,1,1,1,0.974843,1,1,1,1,1,1,1,0.993711,1,1,0.990506,1,0.993671,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.984177,1,1,1,1,0.996835,1,1,1,0.981013,1,1,1,0.993671,1,1,0.993711,1,1,0.987342,1,1,0.996835,1,1,1,1,1,0.968553,1,0.987421,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1]
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
0.8104864181933038
kappa
0.8736426456071076
kappa
0.7978681405448086
kappa
0.8168107702633345
kappa
0.7915021323645554
kappa
0.7978362157466635
kappa
0.8357094901465187
kappa
0.8294243070362474
kappa
0.842040832444813
kappa
0.8231066887783305
kb_relative_information_score
123.5235652696856
kb_relative_information_score
123.47692862400726
kb_relative_information_score
122.89584286913203
kb_relative_information_score
123.21073899539357
kb_relative_information_score
122.12856548767799
kb_relative_information_score
122.24959082847076
kb_relative_information_score
125.67805011137783
kb_relative_information_score
123.80090584049866
kb_relative_information_score
124.56329269078996
kb_relative_information_score
125.64127709577728
mean_absolute_error
0.011380979166666097
mean_absolute_error
0.011587604166666134
mean_absolute_error
0.011633083333333584
mean_absolute_error
0.011499958333332597
mean_absolute_error
0.011467999999999761
mean_absolute_error
0.011822666666666395
mean_absolute_error
0.011093458333332928
mean_absolute_error
0.011346458333333123
mean_absolute_error
0.011476895833332581
mean_absolute_error
0.011226354166666628
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
0.8125
predictive_accuracy
0.875
predictive_accuracy
0.8
predictive_accuracy
0.81875
predictive_accuracy
0.79375
predictive_accuracy
0.8
predictive_accuracy
0.8375
predictive_accuracy
0.83125
predictive_accuracy
0.84375
predictive_accuracy
0.825
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
0.8125 [1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,0,0.5,0,1,1,1,1,1,0.5,0,1,0.5,1,1,1,1,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,0.5,0.5,0.5,1,0.5,1,1,1,1,1,1,1,1,0.5,1,1,1,0.5,1,1,0,0.5,1,0.5,1,1,1,1,0.5,1,1,1,1,0,1,1,0.5,1,1,0.5,1,1,1,1,0.5,1,0,1,1,0,1]
recall
0.875 [1,1,1,1,1,1,1,1,1,1,1,1,0.5,0.5,1,1,1,0,0.5,1,1,1,1,1,1,0.5,0.5,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,0,1,1,1,0.5,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,0.5,1,0.5,0.5,0.5,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,0.5,1]
recall
0.8 [0.5,1,1,1,0.5,0.5,1,1,1,1,0.5,1,1,1,1,1,1,1,1,0,1,1,0.5,1,1,0.5,0.5,1,1,1,1,1,1,0.5,1,1,1,0,1,1,0,1,1,1,1,1,0.5,1,0.5,1,1,1,1,0.5,1,0.5,1,1,1,0,1,1,0.5,1,1,1,0.5,1,0,0.5,0.5,1,0,1,1,1,1,0.5,1,1,1,0.5,1,0.5,1,1,1,0.5,1,1,1,1,1,0.5,1,1,1,0.5,0,1]
recall
0.81875 [1,1,1,1,1,0,1,1,0.5,1,0.5,1,1,1,1,1,1,0.5,0,0,1,1,1,1,1,0,0.5,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0.5,1,1,0,1,1,1,1,1,0.5,1,1,1,1,0.5,1,0,1,1,0.5,0,0.5,1,1,1,1,1,0.5,1,1,1,0.5,1,0.5,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,0.5]
recall
0.79375 [0.5,1,1,1,1,0.5,1,1,1,1,1,1,0,0,1,1,1,1,1,0,0.5,1,1,1,1,0.5,0.5,1,1,1,1,1,1,0.5,1,1,1,0.5,1,1,0.5,1,1,1,1,1,1,0.5,1,1,0,0,0.5,0,0.5,0,1,1,1,1,1,1,1,1,0.5,1,0,1,0.5,0.5,1,1,1,1,0.5,1,1,0,1,1,1,1,1,0.5,1,1,1,1,1,1,1,0.5,1,0,0.5,1,1,1,0,0.5]
recall
0.8 [0.5,1,1,1,1,0.5,1,1,1,0.5,1,1,1,1,1,1,1,1,1,0,1,1,0.5,1,1,0.5,0.5,1,1,1,1,1,0.5,0.5,0,0.5,0.5,1,1,1,1,1,1,1,1,1,1,0.5,1,0.5,1,1,1,1,1,0,1,1,0,1,1,0.5,0,1,1,1,1,1,1,0.5,0.5,0.5,1,1,0.5,1,1,0.5,1,1,1,0.5,1,0.5,0,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0.5]
recall
0.8375 [1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0.5,1,1,1,0.5,1,1,1,1,1,0,0,0.5,1,1,0.5,1,1,1,1,1,0.5,1,1,1,1,0.5,1,1,1,0.5,0,0.5,1,1,1,1,1,1,1,0.5,1,1,0,1,1,1,1,0.5,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,0.5,1,1,1,1,0,0,1,1,1,0.5,0,1,1,1,0,0.5,1]
recall
0.83125 [1,1,1,1,1,0.5,1,1,1,1,1,1,1,0,1,0.5,1,1,0.5,0.5,1,1,1,1,0.5,0,1,1,0,1,1,1,1,1,1,1,0,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,0,1,1,0.5,1,1,1,1,1,1,1,1,1,0,0,1,0.5,1,0,1,1,1,1,1,1,1,1,1,0,1,0.5,1,0.5,0.5,1,0,1,1,1,1,1,0,1,1,0.5,1,1,1]
recall
0.84375 [0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,0.5,0,1,1,0,1,1,1,1,0.5,1,1,0,1,1,1,1,0.5,0.5,0,1,1,1,0,1,1,0.5,1,1,1,0.5,1,1,0,1,0,0.5,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,0,1,1,0.5,1,0.5,1,1,0,1,0.5,1]
recall
0.825 [0,1,1,1,1,1,1,0,1,1,1,1,1,0.5,1,1,1,1,0.5,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,0,1,0.5,1,1,1,1,1,1,0.5,1,1,1,1,0.5,0.5,1,0.5,0.5,0,1,1,1,1,1,1,0,1,1,1,0.5,1,0.5,0,0,0,0,1,0.5,0.5,1,1,1,1,1,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1]
relative_absolute_error
0.5747969276093978
relative_absolute_error
0.5852325336700058
relative_absolute_error
0.5875294612794729
relative_absolute_error
0.5808059764309382
relative_absolute_error
0.5791919191919062
relative_absolute_error
0.5971043771043624
relative_absolute_error
0.560275673400652
relative_absolute_error
0.5730534511784395
relative_absolute_error
0.5796412037036647
relative_absolute_error
0.5669875841750812
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
0.06560189222795897
root_mean_squared_error
0.0658921417977452
root_mean_squared_error
0.06665449216961475
root_mean_squared_error
0.06598296447337272
root_mean_squared_error
0.0662458860357876
root_mean_squared_error
0.06731252989270099
root_mean_squared_error
0.0642321775972843
root_mean_squared_error
0.06562223531213449
root_mean_squared_error
0.06532985263899772
root_mean_squared_error
0.06439798917991862
root_relative_squared_error
0.6593238244165812
root_relative_squared_error
0.6622409423515602
root_relative_squared_error
0.6699028518736182
root_relative_squared_error
0.6631537445864468
root_relative_squared_error
0.6657962057131868
root_relative_squared_error
0.6765163798293057
root_relative_squared_error
0.6455576744171628
root_relative_squared_error
0.6595282801053353
root_relative_squared_error
0.6565897236750451
root_relative_squared_error
0.6472241435247176
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
7384.132007000062
usercpu_time_millis
7239.262049999979
usercpu_time_millis
7193.729832999907
usercpu_time_millis
7206.641981999383
usercpu_time_millis
7193.551054999716
usercpu_time_millis
7218.138082999758
usercpu_time_millis
7252.92459100001
usercpu_time_millis
7203.076040000269
usercpu_time_millis
7212.611003999882
usercpu_time_millis
7221.537007999814
usercpu_time_millis_testing
40.839753999989625
usercpu_time_millis_testing
35.938399999849935
usercpu_time_millis_testing
36.04726699995808
usercpu_time_millis_testing
35.77982199976759
usercpu_time_millis_testing
36.66761099975702
usercpu_time_millis_testing
38.33827700009351
usercpu_time_millis_testing
35.796468000171444
usercpu_time_millis_testing
36.6238980000162
usercpu_time_millis_testing
36.06063099960011
usercpu_time_millis_testing
35.865714000010485
usercpu_time_millis_training
7343.292253000072
usercpu_time_millis_training
7203.323650000129
usercpu_time_millis_training
7157.682565999949
usercpu_time_millis_training
7170.862159999615
usercpu_time_millis_training
7156.883443999959
usercpu_time_millis_training
7179.799805999664
usercpu_time_millis_training
7217.1281229998385
usercpu_time_millis_training
7166.452142000253
usercpu_time_millis_training
7176.550373000282
usercpu_time_millis_training
7185.671293999803