5958264
1
Jan van Rijn
9954
Supervised Classification
6952
sklearn.pipeline.Pipeline(imputation=openmlstudy14.preprocessing.ConditionalImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,variencethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,classifier=sklearn.svm.classes.SVC)(1)
3993005
axis
0
6947
categorical_features
[]
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copy
true
6947
fill_empty
0
6947
missing_values
"NaN"
6947
strategy
"most_frequent"
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
C
239.32272488507502
6953
cache_size
200
6953
class_weight
null
6953
coef0
0.7876609335325613
6953
decision_function_shape
null
6953
degree
3
6953
gamma
6.4707107254612195
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kernel
"sigmoid"
6953
max_iter
-1
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probability
true
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random_state
17745
6953
shrinking
false
6953
tol
1.3090148769668182e-05
6953
verbose
false
6953
openml-pimp
openml-python
Sklearn_0.18.1.
1491
one-hundred-plants-margin
https://www.openml.org/data/download/1592283/phpCsX3fx
-1
12839958
description
https://api.openml.org/data/download/12839958/description.xml
-1
12839957
predictions
https://api.openml.org/data/download/12839957/predictions.arff
area_under_roc_curve
0.9963517992424245 [0.994279,1,1,1,0.999605,0.997001,0.999566,0.999961,0.997238,0.999961,0.999014,1,0.999803,0.985677,0.999527,1,1,0.991635,0.979088,0.972854,0.997672,0.999763,0.99633,1,0.994949,0.972656,0.982836,0.998658,0.999092,1,0.999882,1,0.999921,0.98986,0.999724,0.99929,0.993292,0.980903,0.999961,1,0.999211,1,1,0.999132,0.999369,0.999487,0.999803,0.996212,0.998224,0.99783,0.99637,0.998974,0.999132,0.988676,0.997514,0.988755,1,0.999803,0.993805,0.994397,0.999211,0.999645,0.996252,0.998658,0.999448,0.992819,0.987255,0.999921,0.994042,0.994397,0.995186,0.99858,0.993766,0.999921,0.988557,0.999803,0.999882,0.991596,1,0.999724,0.991517,0.998303,0.999211,0.995739,0.998619,0.999921,1,0.999527,0.999487,1,0.996173,0.999448,0.999132,0.998698,0.999527,0.997435,0.99929,0.998501,0.972972,0.99633]
average_cost
0
f_measure
0.8236378372710488 [0.756757,0.967742,1,1,0.967742,0.827586,0.969697,0.967742,0.875,0.896552,0.875,0.941176,0.967742,0.714286,1,0.967742,1,0.4,0.352941,0.166667,0.83871,0.967742,0.727273,1,0.848485,0.4,0.411765,0.8125,0.903226,0.896552,0.969697,1,0.909091,0.533333,0.941176,0.848485,0.466667,0.457143,0.903226,1,0.833333,0.941176,0.967742,0.848485,0.967742,0.903226,0.9375,0.75,0.722222,0.903226,0.848485,0.814815,0.909091,0.758621,0.8125,0.5,1,0.969697,0.647059,0.705882,0.875,0.969697,0.777778,0.9375,0.903226,0.625,0.424242,1,0.8125,0.787879,0.758621,0.857143,0.484848,0.967742,0.764706,0.969697,0.933333,0.516129,1,0.9375,0.727273,0.903226,0.903226,0.645161,0.83871,0.866667,0.967742,0.848485,0.9375,1,0.774194,0.866667,0.909091,0.967742,0.967742,0.777778,0.882353,0.857143,0.363636,0.866667]
kappa
0.8200757575757576
kb_relative_information_score
978.1231335845224
mean_absolute_error
0.01624905620579826
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
0.8304893847552515 [0.666667,1,1,1,1,0.923077,0.941176,1,0.875,1,0.875,0.888889,1,0.833333,1,1,1,0.428571,0.333333,0.15,0.866667,1,0.705882,1,0.823529,0.428571,0.388889,0.8125,0.933333,1,0.941176,1,0.882353,0.571429,0.888889,0.823529,0.5,0.421053,0.933333,1,0.75,0.888889,1,0.823529,1,0.933333,0.9375,0.75,0.65,0.933333,0.823529,1,0.882353,0.846154,0.8125,0.5,1,0.941176,0.611111,0.666667,0.875,0.941176,0.7,0.9375,0.933333,0.625,0.411765,1,0.8125,0.764706,0.846154,1,0.470588,1,0.722222,0.941176,1,0.533333,1,0.9375,0.705882,0.933333,0.933333,0.666667,0.866667,0.928571,1,0.823529,0.9375,1,0.8,0.928571,0.882353,1,1,0.7,0.833333,0.789474,0.352941,0.928571]
predictive_accuracy
0.821875
prior_entropy
6.6438561897747395
recall
0.821875 [0.875,0.9375,1,1,0.9375,0.75,1,0.9375,0.875,0.8125,0.875,1,0.9375,0.625,1,0.9375,1,0.375,0.375,0.1875,0.8125,0.9375,0.75,1,0.875,0.375,0.4375,0.8125,0.875,0.8125,1,1,0.9375,0.5,1,0.875,0.4375,0.5,0.875,1,0.9375,1,0.9375,0.875,0.9375,0.875,0.9375,0.75,0.8125,0.875,0.875,0.6875,0.9375,0.6875,0.8125,0.5,1,1,0.6875,0.75,0.875,1,0.875,0.9375,0.875,0.625,0.4375,1,0.8125,0.8125,0.6875,0.75,0.5,0.9375,0.8125,1,0.875,0.5,1,0.9375,0.75,0.875,0.875,0.625,0.8125,0.8125,0.9375,0.875,0.9375,1,0.75,0.8125,0.9375,0.9375,0.9375,0.875,0.9375,0.9375,0.375,0.8125]
relative_absolute_error
0.8206594043332441
root_mean_prior_squared_error
0.09949874371066209
root_mean_squared_error
0.08326585154189667
root_relative_squared_error
0.8368532951936565
total_cost
0
area_under_roc_curve
0.9962861237162649 [0.993711,1,1,1,1,1,1,1,1,1,1,1,1,0.987342,1,1,1,1,0.96519,0.987421,0.993711,1,1,1,0.993711,0.990506,1,1,1,1,1,1,1,0.977848,1,0.993711,1,0.993711,1,1,1,1,1,1,1,1,1,1,1,0.984177,1,1,1,1,1,0.993711,1,1,1,1,1,1,1,1,1,1,0.987342,1,1,0.937107,0.993671,1,1,1,1,1,1,0.977848,1,1,1,1,1,1,1,1,1,1,0.996835,1,0.996835,1,1,1,1,0.984177,1,0.990506,0.927215,1]
area_under_roc_curve
0.9966023306265421 [1,1,1,1,1,1,1,1,1,1,1,1,1,0.933544,1,1,1,0.984177,0.993671,0.993711,1,1,1,1,1,0.984177,0.981013,1,1,1,1,1,1,1,1,1,0.993711,0.993711,1,1,1,1,1,1,1,1,1,1,1,1,1,0.996835,1,1,1,0.993711,1,1,1,0.993671,1,1,1,1,1,0.996835,0.993671,1,0.949686,1,0.993671,1,1,1,1,1,1,0.993671,1,0.996835,0.974684,1,0.993711,0.987421,0.996835,1,1,1,1,1,0.987342,1,1,0.990506,1,1,1,0.993671,0.996835,0.987421]
area_under_roc_curve
0.9967229918000159 [1,1,1,1,1,1,0.993711,1,0.996835,1,1,1,1,1,0.996835,1,1,0.993671,0.981132,0.949367,1,1,0.987342,1,1,0.955696,0.996835,0.993711,1,1,1,1,1,0.987342,1,1,0.987421,0.968553,1,1,0.990506,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.974843,0.984177,1,1,1,0.974843,0.996835,1,1,1,0.987421,0.996835,0.993671,0.996835,1,1,0.993711,1,1,0.996835,1,1,1,1,1,0.996835,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.987421,1]
area_under_roc_curve
0.9953812893081763 [1,1,1,1,1,0.993671,1,1,0.993671,1,0.996835,1,1,1,1,1,1,0.993671,0.91195,0.955696,1,1,1,1,0.981132,0.977848,0.984177,1,1,1,1,1,1,0.987342,1,1,1,0.949686,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.981013,1,0.987342,1,1,0.993711,0.993671,1,1,1,1,1,0.993671,0.974684,1,1,0.987342,0.974684,0.996835,0.981132,1,1,1,1,1,1,1,1,1,1,0.996835,1,1,1,1,1,1,1,1,0.993711,1,1,1,1,0.996835,0.949686,0.984177]
area_under_roc_curve
0.9963652376403154 [1,1,1,1,1,1,1,1,1,1,0.993671,1,1,0.949686,1,1,1,0.996835,1,0.990506,1,1,1,1,0.987342,0.993671,0.977848,1,1,1,1,1,1,0.974684,1,1,0.993671,0.981013,1,1,1,1,1,1,1,1,1,1,1,1,0.987421,0.981132,1,1,0.990506,0.993671,1,0.996835,1,1,1,1,1,1,1,1,0.993711,1,0.993671,1,1,1,1,1,0.939873,1,0.996835,0.981013,1,1,1,1,1,0.990506,0.987421,1,1,1,1,1,1,0.996835,1,1,0.996835,0.993711,1,1,0.993711,1]
area_under_roc_curve
0.996284133428867 [0.958861,1,1,1,1,0.996835,1,1,1,1,1,1,1,1,1,1,1,0.996835,0.993711,0.955696,1,1,0.993671,1,0.993671,0.984177,0.990506,1,1,1,1,1,1,0.993671,1,1,0.993671,0.977848,1,1,1,1,1,1,1,1,1,1,0.996835,1,1,1,1,1,1,0.974684,1,1,0.996835,1,0.993671,1,0.987421,1,1,0.987342,1,1,1,1,1,0.990506,1,1,0.984177,1,1,0.993671,1,1,0.981132,0.990506,1,0.996835,1,1,1,1,1,1,0.987421,1,1,1,1,1,1,1,0.987421,0.993671]
area_under_roc_curve
0.9960139519146562 [1,1,1,1,1,1,1,1,0.993711,1,1,1,1,1,1,1,1,1,0.987342,0.96519,0.996835,1,1,1,1,0.886792,0.930818,0.996835,1,1,0.996835,1,1,1,1,1,0.974684,0.990506,1,1,1,1,1,1,0.987421,1,1,0.993671,1,1,0.993711,1,1,1,0.993671,1,1,1,1,1,1,1,1,1,1,0.981132,1,1,1,1,1,1,0.996835,1,1,1,1,0.993711,1,1,0.971519,1,1,1,1,1,1,1,1,1,1,1,0.996835,1,1,0.996835,1,1,0.939873,1]
area_under_roc_curve
0.9973163462303957 [1,1,1,1,1,1,1,1,1,1,0.993711,1,1,1,1,1,1,0.993711,0.974684,1,0.996835,1,1,1,0.993671,0.962264,0.993711,1,0.993711,1,1,1,1,1,1,1,0.987342,0.990506,1,1,1,1,1,1,1,1,1,0.984177,1,1,0.974843,1,1,1,1,0.974684,1,1,0.993671,1,1,1,1,1,1,0.981132,0.949686,1,0.993671,1,1,1,1,1,1,1,1,1,1,1,0.987342,1,0.993671,1,1,1,1,1,1,1,1,1,1,1,1,0.993671,1,1,1,1]
area_under_roc_curve
0.9969986466045697 [1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.974843,1,0.993711,1,1,1,1,0.996835,0.993711,1,1,1,1,1,1,1,0.993711,1,1,0.996835,0.955696,1,1,1,1,1,0.993671,1,0.990506,1,1,0.993711,1,0.993671,1,1,0.936709,0.996835,0.949686,1,1,1,1,1,1,1,1,1,1,0.996835,1,0.996835,1,1,0.987421,0.974684,1,1,1,1,0.987421,1,0.996835,1,1,1,1,1,1,1,1,1,1,0.996835,1,1,1,1,1,1,1,1,1]
area_under_roc_curve
0.9978293428071014 [0.987421,1,1,1,1,1,1,1,1,1,1,1,1,0.990506,1,1,1,0.981132,0.971519,0.968553,0.996835,1,1,1,1,0.993711,0.993711,1,0.996835,1,1,1,1,1,1,1,0.996835,1,1,1,1,1,1,1,1,1,1,1,0.993711,1,1,1,1,0.996835,1,1,1,1,0.990506,0.990506,1,1,0.987342,1,0.993711,0.993711,0.993671,1,1,0.993711,1,1,0.993671,1,0.996835,0.996835,1,1,1,1,1,0.987421,1,0.993711,1,1,1,0.996835,1,1,0.996835,1,1,0.996835,1,1,0.993711,1,1,1]
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
0.8231555678364189
kappa
0.8231066887783305
kappa
0.8673352548663482
kappa
0.7978920775273359
kappa
0.78520097923083
kappa
0.7915103652517275
kappa
0.8041538340045803
kappa
0.8483591991470205
kappa
0.8357224657426056
kappa
0.8231416051478425
kb_relative_information_score
98.39121534575699
kb_relative_information_score
96.88988109487464
kb_relative_information_score
97.98894123451154
kb_relative_information_score
96.65566606291962
kb_relative_information_score
96.82273336444406
kb_relative_information_score
95.88744006954865
kb_relative_information_score
99.99322195086573
kb_relative_information_score
98.37124964639008
kb_relative_information_score
98.69507819455917
kb_relative_information_score
98.42770662065236
mean_absolute_error
0.01614855681354238
mean_absolute_error
0.016347424327254105
mean_absolute_error
0.016247465482642644
mean_absolute_error
0.016357837237370217
mean_absolute_error
0.016382474383441013
mean_absolute_error
0.016467932126510806
mean_absolute_error
0.015990778624482956
mean_absolute_error
0.01621486097106999
mean_absolute_error
0.016141529897960125
mean_absolute_error
0.016191702193708447
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
0.825
predictive_accuracy
0.825
predictive_accuracy
0.86875
predictive_accuracy
0.8
predictive_accuracy
0.7875
predictive_accuracy
0.79375
predictive_accuracy
0.80625
predictive_accuracy
0.85
predictive_accuracy
0.8375
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
0.825 [1,0.5,1,1,1,1,1,1,1,1,0.5,1,1,0,1,1,1,0,0.5,1,1,1,1,1,1,0.5,0.5,1,1,0,1,1,0.5,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,0,0.5,1,1,1,1,1,0.5,0,1,1,1,1,1,1,1,0.5,0.5,1,0.5,1,1,1,1,1,1,0.5,1,1,0,1]
recall
0.825 [1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0.5,0,0,1,1,1,1,1,0.5,0,0.5,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,0.5,1,0,1,1,1,0.5,1,1,1,1,1,0.5,0.5,1,0,1,0.5,1,0,1,1,1,0.5,1,1,0.5,0.5,1,1,0,0.5,1,1,1,1,1,0.5,1,1,1,1,1,1,1,0.5,0]
recall
0.86875 [1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,0,0,0,1,0.5,1,1,0.5,1,1,1,1,1,1,1,0,1,1,1,0,1,1,0.5,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,0,1,1,1,0,1,1,1,1,1,0.5,0.5,1,1,1,1,1,1,0.5,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1]
recall
0.8 [1,1,1,1,0.5,0.5,1,1,0.5,0.5,1,1,1,0.5,1,1,1,0.5,0,0,1,1,1,1,0,0.5,0.5,1,1,1,1,1,1,0.5,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,0.5,1,1,1,1,0.5,0,0.5,1,1,0.5,0,0.5,0,0.5,1,1,1,1,1,1,1,1,0.5,0.5,1,1,1,1,1,1,0.5,1,1,1,1,1,0.5,1,0,0.5]
recall
0.7875 [1,1,1,1,1,0.5,1,1,1,0.5,1,1,0,0,1,1,1,0,1,0.5,1,1,0,1,1,1,0,1,1,0.5,1,1,1,0,1,1,0,0.5,1,1,1,1,1,0,1,0,1,0.5,1,1,0,0,1,1,0.5,0,1,1,0,1,1,1,1,1,0.5,1,0,1,1,1,1,1,1,1,0.5,1,1,0.5,1,1,1,1,1,1,1,0,1,1,1,1,1,0.5,1,1,0.5,1,1,1,1,1]
recall
0.79375 [0.5,1,1,1,1,0.5,1,0.5,1,0.5,1,1,1,1,1,1,1,0.5,1,0.5,1,0.5,1,1,1,0,0.5,0,1,0.5,1,1,1,0.5,1,0.5,0,0.5,1,1,1,1,1,1,1,1,1,1,0.5,0.5,1,1,1,1,1,0,1,1,0.5,1,0.5,1,1,1,1,0.5,1,1,1,1,1,0.5,1,1,0.5,1,1,0.5,1,1,0,0.5,1,1,0,1,1,1,1,1,0,1,1,1,1,1,1,1,0,0.5]
recall
0.80625 [1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,0.5,1,1,0,0,1,1,1,1,1,0,0,0.5,1,1,1,1,1,1,1,1,0,0.5,1,1,1,1,1,1,0,0.5,0.5,0,1,1,1,1,1,1,0.5,0.5,1,1,0,1,1,1,1,1,1,0,0,1,1,1,1,1,0.5,1,1,1,1,0,1,1,0.5,1,1,1,1,1,1,0,1,1,1,1,0.5,1,1,0.5,1,1,0,1]
recall
0.85 [0.5,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,0.5,0,0.5,1,0.5,1,0.5,0,1,1,0,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0.5,0.5,1,1,0.5,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,0,1,1,0.5,1,0.5,1,0.5,0.5,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1]
recall
0.8375 [1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,0,1,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,0.5,0,0,1,1,1,1,0.5,1,1,1,1,0,1,0.5,0.5,1,0.5,0.5,0,1,1,1,1,1,1,1,1,1,1,0.5,1,0.5,1,1,0,0,1,1,1,1,0,1,1,1,1,1,0,1,1,1,1,1,1,0.5,0.5,1,1,1,1,1,1,0.5,1]
recall
0.825 [1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0,0,0,0.5,1,1,1,1,0,0,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,0.5,1,0.5,1,1,1,1,1,1,0.5,1,0,1,1,1,0,1,0.5,1,1,0,0,1,0.5,1,1,1,1,1,1,0,1,0,1,1,1,0.5,1,1,1,1,1,0.5,1,1,1,0.5,0.5,1]
relative_absolute_error
0.8155836774516341
relative_absolute_error
0.8256274912754584
relative_absolute_error
0.8205790647799301
relative_absolute_error
0.8261533958267772
relative_absolute_error
0.8273976961333831
relative_absolute_error
0.8317137437631708
relative_absolute_error
0.8076150820445923
relative_absolute_error
0.8189323722762607
relative_absolute_error
0.8152287827252575
relative_absolute_error
0.8177627370559809
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
0.08282349598750935
root_mean_squared_error
0.08361172874961299
root_mean_squared_error
0.08321558038696084
root_mean_squared_error
0.0838398814738061
root_mean_squared_error
0.08392140178034466
root_mean_squared_error
0.08436525315645162
root_mean_squared_error
0.0820910562752519
root_mean_squared_error
0.08301271047607231
root_mean_squared_error
0.08272813993796123
root_mean_squared_error
0.0830247838762835
root_relative_squared_error
0.8324074545941645
root_relative_squared_error
0.8403294919255684
root_relative_squared_error
0.8363480510763841
root_relative_squared_error
0.8426225130802532
root_relative_squared_error
0.8434418229880808
root_relative_squared_error
0.8479026971615042
root_relative_squared_error
0.8250461585120016
root_relative_squared_error
0.8343091317561718
root_relative_squared_error
0.8314490902370686
root_relative_squared_error
0.8344304739938816
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
1447.9941379999996
usercpu_time_millis
1449.9395399999996
usercpu_time_millis
1452.4993089999994
usercpu_time_millis
1458.7143750000005
usercpu_time_millis
1451.1835069999997
usercpu_time_millis
1445.731010000001
usercpu_time_millis
1446.9266679999996
usercpu_time_millis
1457.9320669999997
usercpu_time_millis
1465.8537609999998
usercpu_time_millis
1443.8201360000012
usercpu_time_millis_testing
162.2043259999999
usercpu_time_millis_testing
157.01114999999976
usercpu_time_millis_testing
154.5305569999993
usercpu_time_millis_testing
159.2038330000003
usercpu_time_millis_testing
158.97818100000018
usercpu_time_millis_testing
159.3702300000004
usercpu_time_millis_testing
163.9355069999997
usercpu_time_millis_testing
158.4522790000005
usercpu_time_millis_testing
159.5819469999995
usercpu_time_millis_testing
158.93166600000086
usercpu_time_millis_training
1285.7898119999998
usercpu_time_millis_training
1292.9283899999998
usercpu_time_millis_training
1297.968752
usercpu_time_millis_training
1299.5105420000002
usercpu_time_millis_training
1292.2053259999996
usercpu_time_millis_training
1286.3607800000007
usercpu_time_millis_training
1282.991161
usercpu_time_millis_training
1299.4797879999992
usercpu_time_millis_training
1306.2718140000004
usercpu_time_millis_training
1284.8884700000003