5876838
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)
3911588
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
C
9294.65234652209
6953
cache_size
200
6953
class_weight
null
6953
coef0
-0.8016618214933062
6953
decision_function_shape
null
6953
degree
3
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gamma
3.6781084402190243
6953
kernel
"sigmoid"
6953
max_iter
-1
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probability
true
6953
random_state
6117
6953
shrinking
true
6953
tol
0.09442707828419063
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
12677490
description
https://api.openml.org/data/download/12677490/description.xml
-1
12677491
predictions
https://api.openml.org/data/download/12677491/predictions.arff
area_under_roc_curve
0.9964082228535354 [0.993924,1,1,1,0.999605,0.996607,0.999605,0.999961,0.997435,0.999803,0.998895,1,0.999882,0.985085,0.999724,1,1,0.993016,0.980035,0.976484,0.997396,0.999842,0.996252,1,0.995186,0.973603,0.984059,0.998698,0.999014,1,0.999842,1,0.999842,0.988005,0.999763,0.999171,0.992661,0.982994,0.999961,1,0.999527,0.999921,1,0.998777,0.999487,0.999645,0.999763,0.997475,0.998264,0.997948,0.996686,0.998816,0.999092,0.988557,0.997711,0.989741,1,0.999763,0.992188,0.994081,0.999014,0.999487,0.995699,0.998777,0.999408,0.993095,0.989031,0.999921,0.9942,0.995028,0.994989,0.998224,0.993884,0.999961,0.988242,0.999763,0.999882,0.991635,1,0.999645,0.992819,0.997277,0.999171,0.994397,0.998422,1,1,0.999605,0.999448,1,0.996765,0.999448,0.999092,0.99858,0.999487,0.997593,0.99929,0.998422,0.970249,0.99708]
average_cost
0
f_measure
0.8239727198796882 [0.722222,0.9375,1,1,0.967742,0.8,0.969697,0.967742,0.875,0.857143,0.9375,0.941176,0.967742,0.758621,1,0.967742,1,0.533333,0.352941,0.277778,0.8125,0.967742,0.727273,1,0.8,0.322581,0.461538,0.8125,0.866667,0.896552,0.969697,1,0.875,0.451613,0.941176,0.827586,0.5,0.545455,0.933333,0.967742,0.810811,0.969697,0.933333,0.8125,0.967742,0.903226,0.9375,0.903226,0.722222,0.875,0.8,0.785714,0.909091,0.758621,0.787879,0.516129,1,0.969697,0.684211,0.742857,0.8,0.9375,0.777778,0.909091,0.903226,0.571429,0.451613,1,0.75,0.787879,0.709677,0.857143,0.5,0.967742,0.8,0.969697,0.933333,0.516129,1,0.9375,0.774194,0.903226,0.903226,0.592593,0.83871,0.933333,0.967742,0.875,0.9375,1,0.896552,0.866667,0.909091,0.909091,0.9375,0.857143,0.848485,0.823529,0.375,0.866667]
kappa
0.8200757575757576
kb_relative_information_score
982.3701707081484
mean_absolute_error
0.016159950900628422
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
0.832251963502165 [0.65,0.9375,1,1,1,0.857143,0.941176,1,0.875,1,0.9375,0.888889,1,0.846154,1,1,1,0.571429,0.333333,0.25,0.8125,1,0.705882,1,0.736842,0.333333,0.391304,0.8125,0.928571,1,0.941176,1,0.875,0.466667,0.888889,0.923077,0.5,0.529412,1,1,0.714286,0.941176,1,0.8125,1,0.933333,0.9375,0.933333,0.65,0.875,0.736842,0.916667,0.882353,0.846154,0.764706,0.533333,1,0.941176,0.590909,0.684211,0.857143,0.9375,0.7,0.882353,0.933333,0.526316,0.466667,1,0.75,0.764706,0.733333,1,0.5,1,0.736842,0.941176,1,0.533333,1,0.9375,0.8,0.933333,0.933333,0.727273,0.866667,1,1,0.875,0.9375,1,1,0.928571,0.882353,0.882353,0.9375,0.789474,0.823529,0.777778,0.375,0.928571]
predictive_accuracy
0.821875
prior_entropy
6.6438561897747395
recall
0.821875 [0.8125,0.9375,1,1,0.9375,0.75,1,0.9375,0.875,0.75,0.9375,1,0.9375,0.6875,1,0.9375,1,0.5,0.375,0.3125,0.8125,0.9375,0.75,1,0.875,0.3125,0.5625,0.8125,0.8125,0.8125,1,1,0.875,0.4375,1,0.75,0.5,0.5625,0.875,0.9375,0.9375,1,0.875,0.8125,0.9375,0.875,0.9375,0.875,0.8125,0.875,0.875,0.6875,0.9375,0.6875,0.8125,0.5,1,1,0.8125,0.8125,0.75,0.9375,0.875,0.9375,0.875,0.625,0.4375,1,0.75,0.8125,0.6875,0.75,0.5,0.9375,0.875,1,0.875,0.5,1,0.9375,0.75,0.875,0.875,0.5,0.8125,0.875,0.9375,0.875,0.9375,1,0.8125,0.8125,0.9375,0.9375,0.9375,0.9375,0.875,0.875,0.375,0.8125]
relative_absolute_error
0.8161591363953733
root_mean_prior_squared_error
0.09949874371066209
root_mean_squared_error
0.08293001858403524
root_relative_squared_error
0.8334780469710457
total_cost
0
area_under_roc_curve
0.9964831621686171 [0.993711,1,1,1,1,1,1,1,1,1,1,1,1,0.990506,1,1,1,0.996835,0.96519,0.987421,0.993711,1,1,1,1,0.993671,1,1,1,1,1,1,1,0.981013,1,0.993711,1,0.993711,1,1,1,1,1,1,1,1,1,1,1,0.987342,1,1,1,1,1,0.993711,1,1,1,1,1,1,1,1,1,0.996835,0.987342,1,1,0.949686,0.996835,1,1,1,1,1,1,0.981013,1,1,1,1,1,1,1,1,1,1,0.996835,1,1,1,1,1,1,0.984177,1,0.987342,0.920886,1]
area_under_roc_curve
0.9965632712363662 [1,1,1,1,1,1,1,1,1,1,1,1,1,0.936709,1,1,1,0.987342,1,0.993711,1,1,1,1,1,0.974684,0.993671,1,1,1,1,1,1,0.996835,1,0.993711,0.993711,0.993711,1,1,1,1,1,1,1,1,1,1,1,1,1,0.993671,1,1,1,0.993711,1,1,1,0.993671,1,1,0.996835,1,1,0.996835,0.993671,1,0.949686,1,0.996835,1,0.996835,1,1,1,1,0.993671,1,0.993671,0.974684,0.996835,0.993711,0.981132,0.993671,1,1,1,1,1,0.993671,1,1,0.990506,1,1,1,0.993671,0.996835,0.987421]
area_under_roc_curve
0.996999144176419 [1,1,1,1,1,0.993671,0.993711,1,0.993671,1,1,1,1,1,1,1,1,0.993671,0.993711,0.962025,0.993711,1,0.987342,1,1,0.96519,0.996835,0.993711,1,1,1,1,1,0.987342,1,1,0.993711,0.968553,1,1,0.993671,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.974843,0.984177,1,1,1,0.974843,0.996835,0.996835,0.996835,1,0.987421,0.996835,0.993671,0.996835,1,1,0.993711,1,1,0.996835,1,1,1,1,1,0.996835,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.993711,1]
area_under_roc_curve
0.9958169134623039 [1,1,1,1,1,0.993671,1,1,0.993671,1,1,1,1,1,1,1,1,1,0.90566,0.974684,1,1,1,1,0.974843,0.987342,0.977848,1,1,1,1,1,1,0.987342,1,1,1,0.937107,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.981013,1,0.984177,1,1,0.993711,0.993671,1,1,1,1,1,0.996835,0.974684,1,1,0.990506,0.981013,0.993671,0.987421,1,1,1,1,1,1,1,1,1,1,0.987342,1,1,1,1,1,1,1,1,0.993711,1,1,1,1,1,0.955975,0.993671]
area_under_roc_curve
0.9963264270360638 [1,1,1,1,1,1,1,1,1,1,0.993671,1,1,0.949686,1,1,1,0.993671,1,0.984177,1,1,1,1,0.993671,1,0.981013,1,1,1,1,1,1,0.974684,1,1,0.993671,0.977848,1,1,1,1,1,1,1,1,1,1,1,1,0.987421,0.981132,1,1,0.990506,0.993671,1,0.996835,1,0.993711,1,1,1,1,1,1,0.987421,1,0.993671,1,1,1,1,1,0.939873,1,0.996835,0.984177,1,1,1,1,1,0.993671,0.987421,1,1,1,1,1,1,0.996835,1,1,0.993671,0.993711,1,1,0.987421,1]
area_under_roc_curve
0.996718264867447 [0.958861,1,1,1,1,0.996835,1,1,1,1,1,1,1,1,1,1,1,1,0.993711,0.955696,1,1,1,1,0.993671,0.990506,0.993671,1,1,1,1,1,1,0.993671,1,1,0.993671,0.987342,1,1,1,1,1,1,1,1,1,1,0.996835,1,1,1,1,1,1,0.981013,1,1,0.993671,1,0.993671,1,0.987421,1,1,0.990506,1,1,1,1,1,0.987342,1,1,0.984177,1,1,0.990506,1,1,0.993711,0.984177,1,0.996835,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.987421,0.993671]
area_under_roc_curve
0.9958161671045298 [1,1,1,1,1,0.996835,1,1,0.993711,1,1,1,1,1,1,1,1,1,0.987342,0.968354,0.996835,1,1,1,1,0.886792,0.937107,0.993671,1,1,0.996835,1,1,0.987421,1,1,0.974684,0.990506,1,1,1,1,1,1,0.993711,1,1,0.996835,1,1,0.993711,1,1,1,0.993671,1,1,1,0.993671,1,1,1,1,0.996835,1,0.981132,1,1,0.996835,1,1,1,0.993671,1,1,1,1,0.993711,1,1,0.974684,1,1,1,1,1,1,1,1,1,1,1,0.996835,1,1,0.996835,1,1,0.936709,1]
area_under_roc_curve
0.9973959577262956 [1,1,1,1,1,1,1,1,1,1,0.993711,1,1,1,1,1,1,0.993711,0.974684,1,1,1,1,1,0.993671,0.974843,0.987421,1,0.993711,1,1,1,1,0.993711,1,1,0.987342,0.993671,1,1,1,1,1,1,1,1,1,0.984177,1,1,0.974843,1,1,1,1,0.981013,1,1,0.993671,1,1,1,0.993711,1,1,0.974843,0.949686,1,0.993671,1,1,1,0.996835,1,1,1,1,1,1,1,0.993671,1,0.990506,1,1,1,1,1,1,1,1,1,1,1,1,0.993671,1,1,1,1]
area_under_roc_curve
0.997078009314545 [1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.987421,1,0.993711,1,1,1,1,1,1,0.993711,1,1,1,1,1,1,0.987421,1,1,0.996835,0.962025,1,1,1,1,1,0.990506,1,0.993671,1,1,0.993711,1,0.993671,1,1,0.936709,0.996835,0.949686,1,1,1,1,1,1,1,1,1,1,0.996835,1,0.996835,1,1,0.987421,0.974684,1,1,1,1,0.993711,1,0.996835,1,0.993711,1,0.987421,1,1,1,1,1,1,0.996835,1,1,1,1,1,1,1,1,1]
area_under_roc_curve
0.9979084567311519 [0.987421,1,1,1,1,1,1,1,1,1,1,1,1,0.993671,1,1,1,0.981132,0.974684,0.968553,0.996835,1,1,1,1,1,0.993711,1,0.996835,1,1,1,1,1,1,1,0.996835,1,1,1,1,1,1,1,1,1,1,1,0.993711,1,1,1,1,0.996835,1,1,1,1,0.990506,0.987342,1,1,0.984177,1,0.993711,0.993711,0.993671,1,1,0.993711,1,1,0.993671,1,1,1,1,1,1,1,1,0.981132,1,0.993711,1,1,1,1,1,1,0.993671,1,1,0.996835,1,1,0.993711,1,1,1]
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
0.8231625483539906
kappa
0.8357224657426056
kappa
0.8610123983258312
kappa
0.7789270064348032
kappa
0.7915103652517275
kappa
0.8104564839677776
kappa
0.8294108355709999
kappa
0.8231066887783305
kappa
0.8230997038499506
kappa
0.8231485867677246
kb_relative_information_score
98.97625983468761
kb_relative_information_score
97.08742698536517
kb_relative_information_score
98.7924361533756
kb_relative_information_score
97.247320978975
kb_relative_information_score
97.24197406350622
kb_relative_information_score
96.15907112481385
kb_relative_information_score
100.58219192672087
kb_relative_information_score
98.5980940024345
kb_relative_information_score
98.72182363262958
kb_relative_information_score
98.96357200564017
mean_absolute_error
0.016061107053866944
mean_absolute_error
0.016294138749693026
mean_absolute_error
0.016121521561805095
mean_absolute_error
0.016250965022324655
mean_absolute_error
0.016288667954255286
mean_absolute_error
0.016402953430089857
mean_absolute_error
0.01585066697262113
mean_absolute_error
0.016131349185400743
mean_absolute_error
0.016100095362381328
mean_absolute_error
0.016098043713846138
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
0.8375
predictive_accuracy
0.8625
predictive_accuracy
0.78125
predictive_accuracy
0.79375
predictive_accuracy
0.8125
predictive_accuracy
0.83125
predictive_accuracy
0.825
predictive_accuracy
0.825
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 [1,0.5,1,1,1,1,1,1,1,1,0.5,1,1,0.5,1,1,1,0,0.5,1,1,1,1,1,1,0.5,0,1,1,0,1,1,0.5,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,0,0.5,1,1,1,1,1,0.5,0,1,1,1,1,1,1,1,0.5,0.5,1,0.5,1,1,1,1,1,1,0.5,1,1,0,1]
recall
0.8375 [1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0.5,0.5,1,1,1,1,1,1,0.5,0.5,0.5,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,0.5,1,0,1,1,1,0.5,0,1,1,1,1,0.5,0.5,1,0,1,0.5,1,0,1,1,1,0.5,1,1,0.5,0.5,1,1,0,0.5,1,1,1,1,1,0.5,1,1,1,1,1,1,0.5,1,0]
recall
0.8625 [1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,0,0,0,1,0.5,1,1,0.5,1,1,1,1,1,1,1,0.5,1,1,1,0,1,0.5,0.5,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,0,1,1,1,0,1,1,1,1,0,0.5,0.5,1,1,1,1,1,1,0.5,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1]
recall
0.78125 [1,1,1,1,0.5,0.5,1,1,0.5,0.5,1,1,1,0.5,1,1,1,0.5,0,0,1,1,1,1,0,0,0.5,1,1,1,1,1,1,0.5,1,1,1,0,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,0.5,1,0.5,1,1,1,1,1,1,1,1,0.5,0,0.5,1,1,0.5,0,0.5,0,0.5,1,1,1,0.5,1,1,1,1,0.5,0.5,1,1,1,1,1,1,0.5,1,1,1,1,1,0.5,1,0,0.5]
recall
0.79375 [0.5,1,1,1,1,0.5,1,1,1,0.5,1,1,0,0,1,1,1,0.5,1,0.5,1,1,0,1,1,1,1,1,0,0.5,1,1,0.5,0,1,1,0,0.5,1,1,1,1,1,0,1,0,1,0.5,1,1,0,0,1,1,0.5,0,1,1,1,1,1,1,1,1,0.5,1,0,1,1,1,1,1,1,1,0.5,1,1,0.5,1,1,1,1,1,0.5,1,1,1,1,1,1,1,0.5,1,1,0.5,1,1,1,0,1]
recall
0.8125 [0.5,1,1,1,1,0.5,1,0.5,1,0.5,1,1,1,1,1,1,1,1,1,0.5,1,0.5,1,1,1,0,1,0,1,0.5,1,1,1,0.5,1,0,0,0.5,1,1,1,1,1,1,1,1,1,1,0.5,0.5,1,1,1,1,1,0.5,1,1,0.5,1,0.5,1,1,1,1,0.5,1,1,1,1,1,0.5,1,1,0.5,1,1,0.5,1,1,0,0.5,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0.5]
recall
0.83125 [1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,0.5,1,1,0,0,1,1,1,1,1,0,0,0.5,1,1,1,1,1,0,1,1,0.5,0.5,1,1,1,1,1,1,0,0.5,1,1,1,1,1,1,1,1,0.5,0.5,1,1,0,1,1,1,1,1,1,0,0,1,1,1,1,1,0.5,1,1,1,1,0,1,1,0.5,1,1,1,1,1,1,0,1,1,1,1,0.5,1,1,1,1,1,0,1]
recall
0.825 [0.5,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,0.5,0,0.5,1,0.5,1,0.5,0,1,1,0,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,0.5,1,1,0,0.5,0.5,1,1,0.5,1,1,1,1,1,0.5,1,1,1,0,0,1,1,1,1,0.5,1,1,1,1,1,0,1,1,0.5,1,0.5,0.5,0.5,0.5,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1]
recall
0.825 [1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0.5,1,1,1,1,1,1,0,0,1,1,1,1,1,1,0,1,1,1,0,0,1,1,1,0.5,0,1,1,1,1,0,1,1,0.5,1,0.5,0.5,0,1,1,1,1,0.5,1,1,1,1,1,0.5,1,0.5,1,1,0,0,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0.5,0.5,1,1,1,1,0,1,0.5,1]
recall
0.825 [1,1,1,1,1,1,1,1,0.5,1,1,1,1,0.5,1,1,1,0,0,0,0.5,1,1,1,1,0,0,1,0.5,1,1,1,1,1,1,1,0.5,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,0.5,1,0.5,1,1,1,1,1,1,0.5,1,0,1,1,1,0,1,0.5,1,1,1,0,1,1,1,1,1,1,1,1,0,1,0,1,1,1,0.5,1,1,1,1,1,0.5,1,1,1,0.5,0.5,1]
relative_absolute_error
0.8111670229225716
relative_absolute_error
0.8229363004895454
relative_absolute_error
0.8142182606972257
relative_absolute_error
0.8207558092083146
relative_absolute_error
0.8226599976896596
relative_absolute_error
0.8284319914186783
relative_absolute_error
0.8005387359909648
relative_absolute_error
0.8147146053232684
relative_absolute_error
0.813136129413197
relative_absolute_error
0.8130325108003086
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
0.08249703924169421
root_mean_squared_error
0.08342208367011751
root_mean_squared_error
0.08268086532629883
root_mean_squared_error
0.08341715157428038
root_mean_squared_error
0.0835188684065196
root_mean_squared_error
0.08417026388483848
root_mean_squared_error
0.08154872396313936
root_mean_squared_error
0.08272955842919087
root_mean_squared_error
0.08263444632322385
root_mean_squared_error
0.0826526889381268
root_relative_squared_error
0.829126440848258
root_relative_squared_error
0.8384234871618605
root_relative_squared_error
0.8309739625128446
root_relative_squared_error
0.8383739177336124
root_relative_squared_error
0.8393962103621004
root_relative_squared_error
0.8459429812460937
root_relative_squared_error
0.8195955136909008
root_relative_squared_error
0.8314633466103328
root_relative_squared_error
0.8305074339784747
root_relative_squared_error
0.8306907791567414
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
1284.0182060000002
usercpu_time_millis
1283.5551219999993
usercpu_time_millis
1330.255961999999
usercpu_time_millis
1294.640844999999
usercpu_time_millis
1319.973847000001
usercpu_time_millis
1321.8789130000007
usercpu_time_millis
1342.8699599999998
usercpu_time_millis
1322.8587369999989
usercpu_time_millis
1298.2727880000002
usercpu_time_millis
1305.8072650000022
usercpu_time_millis_testing
170.34218200000018
usercpu_time_millis_testing
171.14495299999976
usercpu_time_millis_testing
177.54582699999943
usercpu_time_millis_testing
170.94691199999977
usercpu_time_millis_testing
179.19597500000071
usercpu_time_millis_testing
181.99763199999984
usercpu_time_millis_testing
181.96273700000097
usercpu_time_millis_testing
178.07514499999934
usercpu_time_millis_testing
173.8831130000005
usercpu_time_millis_testing
176.52197100000143
usercpu_time_millis_training
1113.676024
usercpu_time_millis_training
1112.4101689999995
usercpu_time_millis_training
1152.7101349999996
usercpu_time_millis_training
1123.6939329999993
usercpu_time_millis_training
1140.7778720000001
usercpu_time_millis_training
1139.8812810000009
usercpu_time_millis_training
1160.9072229999988
usercpu_time_millis_training
1144.7835919999995
usercpu_time_millis_training
1124.3896749999997
usercpu_time_millis_training
1129.2852940000007