6209410
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)
4242739
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
true
6948
threshold
0.0
6949
C
155.10707988971012
6953
cache_size
200
6953
class_weight
null
6953
coef0
0.0
6953
decision_function_shape
null
6953
degree
3
6953
gamma
0.3865265019550319
6953
kernel
"rbf"
6953
max_iter
-1
6953
probability
true
6953
random_state
48091
6953
shrinking
false
6953
tol
0.0001989722680253024
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
13349291
description
https://api.openml.org/data/download/13349291/description.xml
-1
13349292
predictions
https://api.openml.org/data/download/13349292/predictions.arff
area_under_roc_curve
0.9961560921717171 [0.993568,1,1,1,0.999527,0.997041,0.999645,1,0.996686,0.999882,0.999092,1,0.999803,0.984848,0.999645,1,1,0.987019,0.981613,0.971117,0.997159,0.999763,0.995462,1,0.996804,0.976365,0.978851,0.998698,0.998935,1,0.999842,1,0.999645,0.988755,0.999803,0.999053,0.990096,0.980429,0.999921,1,0.99925,0.999803,1,0.998777,0.999408,0.999527,0.999803,0.99783,0.998146,0.997238,0.996646,0.998501,0.999014,0.988045,0.997869,0.981021,1,0.999763,0.994239,0.994989,0.99929,0.99925,0.995226,0.998816,0.999408,0.993726,0.988163,0.999921,0.994318,0.994081,0.994792,0.997909,0.993371,0.999961,0.987295,0.999684,0.999882,0.993174,1,0.999605,0.993568,0.997199,0.999171,0.996094,0.998816,0.999882,1,0.999645,0.999448,1,0.995028,0.999487,0.998856,0.998974,0.999487,0.997869,0.998737,0.998106,0.972143,0.996291]
average_cost
0
f_measure
0.8062979849386354 [0.722222,0.9375,1,1,0.9375,0.740741,0.9375,0.967742,0.848485,0.896552,0.903226,0.941176,0.967742,0.666667,1,0.9375,1,0.428571,0.424242,0.181818,0.75,0.967742,0.685714,1,0.848485,0.363636,0.368421,0.8125,0.903226,0.896552,0.969697,1,0.875,0.4375,0.941176,0.689655,0.470588,0.4375,0.909091,1,0.742857,0.909091,0.933333,0.8125,0.967742,0.903226,0.933333,0.9375,0.736842,0.83871,0.8,0.785714,0.903226,0.8,0.787879,0.322581,1,0.9375,0.685714,0.742857,0.8,0.9375,0.727273,0.882353,0.903226,0.606061,0.411765,1,0.727273,0.705882,0.714286,0.758621,0.545455,0.967742,0.764706,0.969697,0.933333,0.5625,1,0.9375,0.774194,0.903226,0.866667,0.625,0.83871,0.903226,0.967742,0.866667,0.9375,1,0.740741,0.827586,0.848485,0.83871,0.9375,0.823529,0.857143,0.810811,0.333333,0.827586]
kappa
0.8017676767676767
kb_relative_information_score
981.4783252397167
mean_absolute_error
0.01618822338337978
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
0.8151037942535614 [0.65,0.9375,1,1,0.9375,0.909091,0.9375,1,0.823529,1,0.933333,0.888889,1,0.714286,1,0.9375,1,0.5,0.411765,0.176471,0.75,1,0.631579,1,0.823529,0.352941,0.318182,0.8125,0.933333,1,0.941176,1,0.875,0.4375,0.888889,0.769231,0.444444,0.4375,0.882353,1,0.684211,0.882353,1,0.8125,1,0.933333,1,0.9375,0.636364,0.866667,0.736842,0.916667,0.933333,0.857143,0.764706,0.333333,1,0.9375,0.631579,0.684211,0.857143,0.9375,0.705882,0.833333,0.933333,0.588235,0.388889,1,0.705882,0.666667,0.833333,0.846154,0.529412,1,0.722222,0.941176,1,0.5625,1,0.9375,0.8,0.933333,0.928571,0.625,0.866667,0.933333,1,0.928571,0.9375,1,0.909091,0.923077,0.823529,0.866667,0.9375,0.777778,0.789474,0.714286,0.3,0.923077]
predictive_accuracy
0.80375
prior_entropy
6.6438561897747395
recall
0.80375 [0.8125,0.9375,1,1,0.9375,0.625,0.9375,0.9375,0.875,0.8125,0.875,1,0.9375,0.625,1,0.9375,1,0.375,0.4375,0.1875,0.75,0.9375,0.75,1,0.875,0.375,0.4375,0.8125,0.875,0.8125,1,1,0.875,0.4375,1,0.625,0.5,0.4375,0.9375,1,0.8125,0.9375,0.875,0.8125,0.9375,0.875,0.875,0.9375,0.875,0.8125,0.875,0.6875,0.875,0.75,0.8125,0.3125,1,0.9375,0.75,0.8125,0.75,0.9375,0.75,0.9375,0.875,0.625,0.4375,1,0.75,0.75,0.625,0.6875,0.5625,0.9375,0.8125,1,0.875,0.5625,1,0.9375,0.75,0.875,0.8125,0.625,0.8125,0.875,0.9375,0.8125,0.9375,1,0.625,0.75,0.875,0.8125,0.9375,0.875,0.9375,0.9375,0.375,0.75]
relative_absolute_error
0.817587039564634
root_mean_prior_squared_error
0.09949874371066209
root_mean_squared_error
0.08308285337528497
root_relative_squared_error
0.8350140944179779
total_cost
0
area_under_roc_curve
0.9958908028819362 [0.993711,1,1,1,1,1,1,1,1,1,1,1,1,0.987342,1,1,1,0.996835,0.968354,0.981132,0.993711,1,1,1,1,0.990506,1,1,1,1,1,1,0.993671,0.974684,0.996835,0.993711,1,0.993711,1,1,1,1,1,1,1,1,1,1,1,0.981013,1,1,1,1,1,0.993711,1,1,1,1,1,1,1,1,1,1,0.996835,1,1,0.930818,0.990506,1,1,1,1,1,1,0.981013,1,1,1,1,1,1,0.996835,1,1,1,0.996835,1,0.993671,1,1,1,1,0.987342,1,0.987342,0.911392,1]
area_under_roc_curve
0.9965242118461907 [1,1,1,1,1,1,1,1,0.996835,1,1,1,1,0.933544,1,1,1,0.981013,0.993671,0.993711,1,1,1,1,1,0.981013,0.984177,1,1,1,1,1,1,1,1,0.993711,0.993711,0.987421,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.974843,1,1,1,0.996835,1,1,0.996835,1,1,0.996835,0.996835,1,0.955975,1,0.993671,1,1,1,1,1,1,0.993671,1,0.993671,0.981013,1,0.993711,0.993711,0.996835,1,1,1,1,1,0.990506,1,1,0.993671,0.996835,1,1,0.993671,0.996835,0.981132]
area_under_roc_curve
0.9957756149988055 [1,1,1,1,1,1,0.993711,1,0.993671,1,1,1,1,0.996835,0.996835,1,1,0.968354,0.993711,0.946203,0.993711,1,0.981013,1,1,0.974684,0.990506,0.993711,1,1,1,1,1,0.987342,1,1,0.993711,0.937107,1,1,0.993671,0.993711,1,1,1,1,1,1,1,1,1,1,1,1,1,0.993671,1,1,0.974843,0.984177,1,1,1,0.968553,1,1,0.993671,1,0.987421,0.993671,0.990506,0.996835,1,1,1,1,1,0.993671,1,1,1,1,1,0.996835,1,1,1,1,1,1,1,1,1,1,0.993671,1,1,1,0.962264,1]
area_under_roc_curve
0.9956188798662529 [1,1,1,1,1,0.993671,1,1,0.993671,1,1,1,1,1,1,1,1,1,0.930818,0.962025,1,1,1,1,0.981132,0.981013,0.984177,1,1,1,1,1,1,0.990506,1,1,1,0.937107,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.977848,1,0.977848,1,1,0.993711,1,1,1,1,1,1,1,0.971519,1,1,0.993671,0.974684,0.993671,0.974843,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.993711,1,1,1,1,0.996835,0.943396,0.981013]
area_under_roc_curve
0.9959306086298861 [1,1,1,1,1,1,1,1,1,1,0.993671,1,1,0.949686,1,1,1,0.993671,1,0.984177,1,1,1,1,0.990506,0.996835,0.974684,1,1,1,1,1,1,0.974684,1,1,0.993671,0.971519,1,1,1,1,1,1,1,1,1,1,1,1,0.987421,0.981132,1,0.993711,0.990506,0.984177,1,0.996835,1,1,1,1,1,1,1,1,0.981132,1,0.993671,1,1,1,1,1,0.933544,1,0.996835,0.984177,1,1,1,1,1,0.990506,0.987421,1,1,1,1,1,1,0.996835,1,1,0.996835,0.993711,1,1,1,1]
area_under_roc_curve
0.9958885638086139 [0.955696,1,1,1,1,0.996835,1,1,1,1,1,1,1,1,1,1,1,0.990506,0.993711,0.943038,1,1,0.993671,1,0.993671,0.987342,0.977848,1,1,1,1,1,1,0.993671,1,0.996835,0.993671,0.984177,1,1,1,1,1,1,1,1,1,1,0.996835,1,1,1,1,1,1,0.974684,1,1,0.996835,1,0.993671,1,0.987421,1,1,0.990506,1,1,1,1,1,0.987342,1,1,0.987342,1,1,0.990506,1,1,0.987421,0.990506,1,0.993671,1,1,1,1,1,1,0.987421,1,1,1,1,1,1,1,0.981132,0.993671]
area_under_roc_curve
0.9957397898256506 [1,1,1,1,1,1,1,1,0.993711,1,1,1,1,1,1,1,1,1,0.987342,0.968354,0.996835,1,1,1,1,0.855346,0.90566,0.996835,1,1,0.996835,1,1,0.993711,1,1,0.96519,0.987342,1,1,1,0.996835,1,1,0.987421,0.996835,1,1,1,1,0.993711,1,1,1,0.993671,0.996835,1,1,1,1,1,1,1,0.996835,1,0.974843,1,1,0.996835,1,1,1,0.996835,1,1,1,1,0.993711,1,1,0.974684,1,1,1,1,1,1,1,1,1,1,1,0.990506,1,1,1,1,1,0.971519,1]
area_under_roc_curve
0.9972762916965209 [1,1,1,1,1,1,1,1,1,1,0.993711,1,1,1,1,1,1,0.987421,0.974684,0.993671,0.993671,1,0.996835,1,0.993671,0.981132,0.993711,1,0.993711,1,1,1,1,1,1,1,0.984177,0.993671,1,1,1,1,1,1,1,1,1,0.987342,1,1,0.974843,0.996835,1,1,1,0.971519,1,1,0.993671,1,1,1,1,1,1,0.981132,0.949686,1,0.996835,1,1,1,0.996835,1,1,1,1,1,1,1,0.993671,1,0.993671,1,1,1,1,1,1,1,1,1,1,1,1,0.993671,1,1,1,1]
area_under_roc_curve
0.9968406675423932 [1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.981132,1,0.987421,1,1,1,1,1,0.993711,1,1,1,1,1,1,1,0.993711,1,1,0.990506,0.971519,1,1,1,1,1,0.990506,1,0.990506,1,0.996835,0.993711,1,0.993671,1,1,0.936709,0.996835,0.949686,1,1,0.996835,1,0.996835,1,1,1,1,1,0.996835,1,0.993671,1,1,0.987421,0.968354,1,1,1,1,0.993711,1,0.996835,1,0.993711,1,0.993711,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.996835,1]
area_under_roc_curve
0.9975536880025475 [0.993711,1,1,1,1,1,1,1,1,1,1,1,1,0.990506,1,1,1,0.962264,0.974684,0.974843,0.996835,1,1,1,1,0.987421,0.993711,1,0.996835,1,1,1,1,1,1,1,0.996835,1,1,1,1,1,1,1,1,1,1,1,0.993711,1,1,1,1,0.996835,1,0.993711,1,1,0.993671,0.990506,1,1,0.984177,1,0.993711,0.993711,0.987342,1,1,0.993711,1,1,0.987342,1,0.996835,0.993671,1,1,1,1,1,0.974843,1,0.993711,1,1,1,1,1,1,0.996835,1,1,1,1,1,0.993711,1,1,1]
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
0.8041924914136829
kappa
0.8167890705204138
kappa
0.8357354392892399
kappa
0.7789444597955236
kappa
0.7662204320183233
kappa
0.7725387987205308
kappa
0.8041461006910168
kappa
0.8167601295316326
kappa
0.8104714522624971
kappa
0.810501381760758
kb_relative_information_score
98.86875849602791
kb_relative_information_score
97.46089679835808
kb_relative_information_score
98.20769399301449
kb_relative_information_score
97.2240126985506
kb_relative_information_score
97.2792383178784
kb_relative_information_score
96.11070833767552
kb_relative_information_score
100.10298764788894
kb_relative_information_score
98.46246328339294
kb_relative_information_score
99.10459737813534
kb_relative_information_score
98.65696828879338
mean_absolute_error
0.016077159813129738
mean_absolute_error
0.016276570057601858
mean_absolute_error
0.01618702289649725
mean_absolute_error
0.016269352045485217
mean_absolute_error
0.016311394424904823
mean_absolute_error
0.016427722047338132
mean_absolute_error
0.015936669585311338
mean_absolute_error
0.01618058588186205
mean_absolute_error
0.016076945695416244
mean_absolute_error
0.016138811386251197
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
0.80625
predictive_accuracy
0.81875
predictive_accuracy
0.8375
predictive_accuracy
0.78125
predictive_accuracy
0.76875
predictive_accuracy
0.775
predictive_accuracy
0.80625
predictive_accuracy
0.81875
predictive_accuracy
0.8125
predictive_accuracy
0.8125
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
0.80625 [1,0.5,1,1,1,1,1,1,1,1,0.5,1,1,0,1,1,1,0,0.5,1,1,1,1,1,1,0.5,0.5,1,1,0,1,1,0.5,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0.5,1,0,1,1,1,1,1,1,1,1,1,1,0.5,1,1,0,0.5,1,0.5,1,1,1,0.5,0.5,1,1,1,1,1,1,1,0.5,0.5,1,0.5,1,0.5,1,1,0.5,1,0.5,1,1,0,1]
recall
0.81875 [1,1,1,1,1,1,0.5,1,1,1,0.5,1,1,0.5,1,1,1,0.5,0.5,0,1,1,1,1,1,0.5,0,0.5,1,1,1,1,1,1,1,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0,1,1,1,0.5,1,1,1,1,1,0.5,0.5,1,0,1,0.5,1,0.5,1,1,1,0.5,1,1,0.5,0.5,1,1,0,0.5,1,1,1,1,1,0.5,1,1,1,1,1,1,1,0,0]
recall
0.8375 [1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,0,0,0,1,0.5,1,1,0.5,0.5,1,1,1,1,1,1,0,1,1,1,0,1,1,0,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,0.5,1,1,1,0,1,1,0.5,0,1,1,1,1,1,0.5,0.5,1,1,1,1,1,1,0,1,1,1,1,1,0.5,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0,1]
recall
0.78125 [1,1,1,1,0.5,0,1,1,0.5,0.5,1,1,1,0.5,1,1,1,0.5,0,0,0,1,1,1,0,0.5,0.5,1,1,1,1,1,1,0.5,1,1,1,0,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,0.5,1,0.5,1,1,1,1,1,1,1,1,0.5,0,0.5,1,1,0.5,0,0.5,0,0.5,1,1,1,1,1,1,1,1,0.5,0.5,1,1,1,1,1,1,0.5,1,1,1,1,1,0.5,1,0,0.5]
recall
0.76875 [0.5,1,1,1,1,0.5,1,1,1,0.5,1,1,0,0,1,1,1,0,1,0.5,1,1,0,1,1,1,0,1,1,0.5,1,1,0.5,0,1,1,0.5,0.5,1,1,1,1,1,0,1,0,1,1,1,1,0,0,0.5,1,0.5,0,1,1,0.5,1,1,1,1,1,0.5,1,0,1,0.5,0.5,1,1,1,1,0.5,1,1,0.5,1,1,1,1,0.5,1,1,1,1,1,1,1,1,0.5,1,0,0.5,1,1,1,1,1]
recall
0.775 [0.5,1,1,1,1,0.5,1,0.5,1,0.5,1,1,1,1,1,1,1,0.5,0,0.5,1,0.5,1,1,1,0,1,0,1,0.5,1,1,1,0.5,1,0,0.5,0.5,1,1,1,1,1,1,1,1,1,1,0.5,0.5,1,1,1,1,1,0.5,1,1,0.5,1,0.5,1,0,1,1,0.5,1,1,1,1,1,0,1,1,0.5,1,1,0.5,1,1,0,0.5,1,1,0,1,1,1,1,1,0,0.5,1,1,1,1,1,1,0,0]
recall
0.80625 [1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,0.5,1,1,0,0,1,1,1,1,1,0,0,0.5,1,1,1,1,1,1,1,1,0,0.5,1,1,1,0.5,1,1,0,0.5,0.5,1,1,1,1,1,1,1,0.5,0,1,1,0,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,0,1,1,0.5,1,1,1,1,1,1,0,1,1,1,1,0,1,1,1,1,1,0,1]
recall
0.81875 [0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,0,0.5,1,0.5,1,0.5,0,1,1,0,1,1,1,1,1,1,1,0,0.5,1,1,1,1,1,1,1,1,1,0.5,1,0,0,0.5,0.5,1,1,0.5,1,1,1,1,1,0.5,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,0,1,1,0.5,1,0.5,0.5,0.5,0.5,1,0,1,1,0,1,1,1,1,1,1,1,1,1]
recall
0.8125 [1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,0,1,0,1,1,1,1,1,0,1,1,1,1,1,1,1,0,1,1,0.5,0,0.5,1,0,1,0.5,0,1,1,1,1,1,1,1,0.5,1,0.5,0.5,0,1,0,1,1,0,1,1,1,1,1,0.5,1,0.5,1,1,0,0,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0.5,0.5,1,1,1,0.5,1,1,0.5,1]
recall
0.8125 [1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0,0.5,0,0.5,1,1,1,1,0,0,1,0.5,1,1,1,1,1,1,0,0.5,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,0.5,1,0.5,1,1,1,1,1,1,0.5,1,0,1,1,1,0,1,0.5,1,0,0,0,1,0.5,1,1,1,1,1,1,0,1,0,1,1,1,0.5,1,1,1,1,1,0.5,1,1,1,0.5,1,1]
relative_absolute_error
0.8119777683398844
relative_absolute_error
0.8220489928081733
relative_absolute_error
0.8175264089140012
relative_absolute_error
0.8216844467416763
relative_absolute_error
0.8238077992376159
relative_absolute_error
0.8296829316837426
relative_absolute_error
0.8048823022884501
relative_absolute_error
0.8172013071647486
relative_absolute_error
0.8119669543139504
relative_absolute_error
0.8150914841540995
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
0.08262138235556568
root_mean_squared_error
0.08334258228037993
root_mean_squared_error
0.08305408372971168
root_mean_squared_error
0.08352998717271498
root_mean_squared_error
0.0836440114378643
root_mean_squared_error
0.08434016987941088
root_mean_squared_error
0.08194380101971507
root_mean_squared_error
0.08294328132313965
root_mean_squared_error
0.08251802419342216
root_mean_squared_error
0.08286677960032483
root_relative_squared_error
0.830376136163337
root_relative_squared_error
0.8376244681313411
root_relative_squared_error
0.8347249486006505
root_relative_squared_error
0.8395079581669543
root_relative_squared_error
0.8406539451502764
root_relative_squared_error
0.8476506007419387
root_relative_squared_error
0.8235661875088998
root_relative_squared_error
0.8336113425143843
root_relative_squared_error
0.8293373475486376
root_relative_squared_error
0.8328424712707705
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
1706.9395089999944
usercpu_time_millis
1581.5613540000015
usercpu_time_millis
1594.6333989999957
usercpu_time_millis
1580.672761999999
usercpu_time_millis
1593.0368409999999
usercpu_time_millis
1580.2663370000046
usercpu_time_millis
1591.1264969999977
usercpu_time_millis
1590.205300000001
usercpu_time_millis
1590.5536559999973
usercpu_time_millis
1589.4287109999896
usercpu_time_millis_testing
158.3774269999978
usercpu_time_millis_testing
158.79840699999903
usercpu_time_millis_testing
157.68878000000086
usercpu_time_millis_testing
159.02230100000025
usercpu_time_millis_testing
162.47511899999978
usercpu_time_millis_testing
158.86027300000194
usercpu_time_millis_testing
157.87137899999948
usercpu_time_millis_testing
157.84556199999855
usercpu_time_millis_testing
157.95049500000147
usercpu_time_millis_testing
157.92118399999566
usercpu_time_millis_training
1548.5620819999965
usercpu_time_millis_training
1422.7629470000024
usercpu_time_millis_training
1436.9446189999949
usercpu_time_millis_training
1421.6504609999988
usercpu_time_millis_training
1430.5617220000001
usercpu_time_millis_training
1421.4060640000027
usercpu_time_millis_training
1433.2551179999982
usercpu_time_millis_training
1432.3597380000024
usercpu_time_millis_training
1432.603160999996
usercpu_time_millis_training
1431.5075269999938