8958749
1935
Hilde Weerts
9954
Supervised Classification
8317
sklearn.pipeline.Pipeline(imputation=hyperimp.utils.preprocessing.ConditionalImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,scaling=sklearn.preprocessing.data.StandardScaler,variencethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,clf=sklearn.svm.classes.SVC)(1)
6894353
categorical_features
[]
7644
dtype
{"oml-python:serialized_object": "type", "value": "np.float64"}
7644
handle_unknown
"ignore"
7644
n_values
"auto"
7644
sparse
true
7644
threshold
0.0
7645
copy
true
7646
with_mean
false
7646
with_std
true
7646
C
1.2136730352049339
7650
cache_size
200
7650
class_weight
null
7650
coef0
0.2639689905186281
7650
decision_function_shape
"ovr"
7650
degree
3
7650
gamma
0.0008220090109015657
7650
kernel
"rbf"
7650
max_iter
-1
7650
probability
false
7650
random_state
1
7650
shrinking
true
7650
tol
0.00011373024169029215
7650
verbose
false
7650
axis
0
8316
categorical_features
[]
8316
copy
true
8316
fill_empty
0
8316
missing_values
"NaN"
8316
strategy
"mean"
8316
strategy_nominal
"most_frequent"
8316
verbose
0
8316
memory
null
8317
openml-python
Sklearn_0.19.1.
study_98
1491
one-hundred-plants-margin
https://www.openml.org/data/download/1592283/phpCsX3fx
-1
18832760
description
https://api.openml.org/data/download/18832760/description.xml
-1
18832761
predictions
https://api.openml.org/data/download/18832761/predictions.arff
area_under_roc_curve
0.6546717171717172 [0.553662,0.620265,0.905303,1,0.623106,0.684659,0.654987,0.77904,0.684975,0.90625,0.623422,0.621843,0.619318,0.561553,0.96875,0.592172,0.625,0.585543,0.612058,0.557765,0.560606,0.6875,0.589015,1,0.561553,0.528725,0.525253,0.62279,0.59154,0.589331,0.623106,0.998737,0.622159,0.619634,0.617109,0.651831,0.620896,0.585859,0.809659,0.749053,0.588384,0.620896,0.717172,0.621843,0.6875,0.622159,0.841225,0.621528,0.618056,0.585859,0.558396,0.590593,0.619949,0.622475,0.621212,0.525568,1,0.622159,0.617109,0.620581,0.619634,0.591225,0.618056,0.590909,0.620265,0.588068,0.585227,0.999369,0.592172,0.589646,0.623422,0.591856,0.619949,0.71875,0.558081,0.623106,0.71654,0.589015,0.842487,0.717487,0.529672,0.591856,0.620581,0.62279,0.621528,0.620896,0.9375,0.555871,0.592487,0.588699,0.589331,0.967487,0.62279,0.616793,0.619318,0.623737,0.613952,0.623106,0.497475,0.559343]
average_cost
0
f_measure
0.32660139226398044 [0.086957,0.228571,0.8125,1,0.307692,0.387097,0.4,0.5625,0.4,0.896552,0.32,0.266667,0.210526,0.190476,0.967742,0.25,0.4,0.133333,0.131148,0.121212,0.166667,0.545455,0.176471,1,0.190476,0.08,0.055556,0.296296,0.230769,0.181818,0.307692,0.888889,0.275862,0.216216,0.177778,0.285714,0.242424,0.136364,0.571429,0.592593,0.166667,0.242424,0.5,0.266667,0.545455,0.275862,0.628571,0.258065,0.190476,0.136364,0.129032,0.206897,0.222222,0.285714,0.25,0.057143,1,0.275862,0.177778,0.235294,0.216216,0.222222,0.190476,0.214286,0.228571,0.162162,0.130435,0.941176,0.25,0.1875,0.32,0.24,0.222222,0.608696,0.125,0.307692,0.466667,0.176471,0.709677,0.518519,0.090909,0.24,0.235294,0.296296,0.258065,0.242424,0.933333,0.102564,0.26087,0.171429,0.181818,0.857143,0.296296,0.173913,0.210526,0.333333,0.145455,0.307692,0,0.142857]
kappa
0.3093434343434343
kb_relative_information_score
503.61245144486406
mean_absolute_error
0.013674999999999764
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
0.3686916723846862 [0.066667,0.210526,0.8125,1,0.4,0.4,0.555556,0.5625,0.428571,1,0.444444,0.285714,0.181818,0.4,1,0.375,1,0.103448,0.088889,0.117647,0.25,1,0.166667,1,0.4,0.111111,0.05,0.363636,0.3,0.176471,0.4,0.8,0.307692,0.190476,0.137931,0.263158,0.235294,0.107143,0.526316,0.727273,0.15,0.235294,0.583333,0.285714,1,0.307692,0.578947,0.266667,0.153846,0.107143,0.133333,0.230769,0.2,0.333333,0.25,0.052632,1,0.307692,0.137931,0.222222,0.190476,0.272727,0.153846,0.25,0.210526,0.142857,0.1,0.888889,0.375,0.1875,0.444444,0.333333,0.2,1,0.125,0.4,0.5,0.166667,0.733333,0.636364,0.166667,0.333333,0.222222,0.363636,0.266667,0.235294,1,0.086957,0.428571,0.157895,0.176471,0.789474,0.363636,0.133333,0.181818,0.5,0.102564,0.4,0,0.166667]
predictive_accuracy
0.31625
prior_entropy
6.6438561897747395
recall
0.31625 [0.125,0.25,0.8125,1,0.25,0.375,0.3125,0.5625,0.375,0.8125,0.25,0.25,0.25,0.125,0.9375,0.1875,0.25,0.1875,0.25,0.125,0.125,0.375,0.1875,1,0.125,0.0625,0.0625,0.25,0.1875,0.1875,0.25,1,0.25,0.25,0.25,0.3125,0.25,0.1875,0.625,0.5,0.1875,0.25,0.4375,0.25,0.375,0.25,0.6875,0.25,0.25,0.1875,0.125,0.1875,0.25,0.25,0.25,0.0625,1,0.25,0.25,0.25,0.25,0.1875,0.25,0.1875,0.25,0.1875,0.1875,1,0.1875,0.1875,0.25,0.1875,0.25,0.4375,0.125,0.25,0.4375,0.1875,0.6875,0.4375,0.0625,0.1875,0.25,0.25,0.25,0.25,0.875,0.125,0.1875,0.1875,0.1875,0.9375,0.25,0.25,0.25,0.25,0.25,0.25,0,0.125]
relative_absolute_error
0.6906565656565524
root_mean_prior_squared_error
0.09949874371066209
root_mean_squared_error
0.11694015563526398
root_relative_squared_error
1.1752927853573787
total_cost
0
area_under_roc_curve
0.6352201257861633 [0.465409,0.5,0.75,1,0.5,0.990566,0.5,0.996855,0.5,1,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,0.977987,0.496855,0.5,0.977987,1,0.496855,0.5,0.5,0.5,0.5,0.481132,0.5,1,0.5,0.5,0.5,0.987421,0.996855,0.987421,0.993711,0.5,0.981132,0.987421,1,0.5,0.5,0.5,0.993711,0.990566,0.5,0.5,0.5,0.5,0.987421,0.5,0.993711,0.484277,1,0.990566,0.993711,0.5,0.993711,0.987421,0.5,0.5,0.990566,0.5,0.5,1,0.993711,0.493711,0.5,0.993711,0.5,0.5,0.487421,0.5,0.5,0.5,1,0.75,0.5,0.5,0.990566,0.996855,0.5,0.5,0.75,0.5,0.5,0.987421,0.5,1,0.5,0.5,0.5,0.5,0.974843,0.5,0.5,0.993711]
area_under_roc_curve
0.6540681474404901 [0.974843,0.5,0.75,1,0.5,0.993711,0.5,0.996855,0.5,1,0.5,0.5,0.5,0.5,1,0.996855,0.5,0.5,0.5,0.981132,0.996855,0.5,0.987421,1,0.996855,0.5,0.5,0.5,0.5,0.987421,0.5,0.996835,0.5,0.5,0.5,0.990566,0.996855,0.984277,0.996855,0.5,0.984277,0.990566,0.75,0.5,0.75,0.5,0.996855,0.990566,0.5,0.5,0.5,0.5,0.974843,0.5,0.996855,0.481132,1,0.981132,0.984277,0.5,0.987421,0.990566,0.5,0.5,0.987421,0.5,0.5,1,0.5,0.987421,0.5,1,0.5,0.75,0.493711,0.5,0.5,0.5,1,0.75,0.5,0.5,0.990566,1,0.5,0.5,1,0.5,0.5,0.987421,0.5,1,0.5,0.5,0.5,0.5,0.984277,0.5,0.5,0.487421]
area_under_roc_curve
0.660337552742616 [0.5,0.5,1,1,0.5,1,0.996855,0.5,0.996835,1,0.5,0.5,0.981132,0.5,1,0.5,0.5,0.5,0.993711,0.5,0.996855,0.5,0.5,1,1,0.5,0.5,0.993711,0.5,0.5,1,1,0.5,0.5,0.981132,0.993711,0.974843,0.981132,0.990566,0.5,0.5,0.993711,0.996855,0.984277,0.75,0.987421,0.5,0.990566,0.5,0.5,0.5,0.996855,0.996855,0.5,0.987421,0.5,1,0.5,0.971698,0.5,0.987421,0.496855,0.5,0.487421,0.5,0.5,0.5,1,0.993711,0.5,0.5,0.746835,0.968553,0.75,0.987421,0.5,0.5,0.5,0.75,0.5,0.496855,0.5,0.5,0.5,0.990566,0.987421,1,0.5,0.5,0.490566,0.5,0.996855,0.996855,0.5,0.5,1,0.5,0.5,0.496855,0.5]
area_under_roc_curve
0.6477589363904147 [0.5,0.5,0.75,1,0.5,0.5,1,0.5,0.746835,0.75,0.5,0.5,0.977987,0.5,1,0.5,0.5,0.5,0.987421,0.5,0.490566,1,0.5,1,0.496855,0.5,0.5,0.990566,0.5,0.5,0.996855,0.996835,0.5,0.5,0.987421,0.984277,0.990566,0.468553,0.990566,0.5,0.5,0.987421,0.990566,0.993711,0.75,0.993711,0.5,0.993711,0.5,0.5,0.5,0.993711,0.990566,0.5,0.987421,0.5,1,0.5,0.971698,0.5,0.977987,1,0.5,0.996855,0.5,0.5,0.5,1,0.996855,0.5,0.5,0.5,0.990566,0.5,0.987421,0.5,0.5,0.5,1,0.75,0.496855,0.5,0.5,0.5,0.984277,0.990566,1,0.5,0.5,0.984277,0.5,1,0.993711,0.5,0.5,0.996855,0.5,0.5,0.493711,0.5]
area_under_roc_curve
0.6665671522967911 [0.5,0.990566,0.996835,1,0.993711,0.5,0.996855,0.996835,0.496855,0.75,0.5,0.5,0.993711,0.496855,0.5,0.5,0.5,0.5,0.943396,0.5,0.5,1,0.5,1,0.5,0.5,0.5,0.996855,0.996855,0.5,0.993711,1,0.5,0.5,0.977987,0.75,0.5,0.5,0.75,0.996835,0.5,0.5,1,0.996855,1,0.996855,1,0.5,0.5,0.5,0.496855,0.490566,0.5,0.993711,0.5,0.5,1,0.5,0.5,0.993711,0.5,0.5,0.974843,0.996855,0.5,0.5,0.468553,1,0.5,0.5,0.5,0.5,0.990566,1,0.5,1,0.746835,0.5,0.5,0.993711,0.993711,0.5,0.5,0.5,0.993711,0.990566,1,0.981132,0.5,0.5,0.987421,0.746835,0.990566,0.993711,0.5,0.993711,0.5,0.990566,0.496855,0.5]
area_under_roc_curve
0.6792253801448929 [0.5,0.993711,1,1,0.993711,0.5,0.993711,1,1,0.75,0.5,0.5,0.990566,0.996855,1,0.5,0.5,0.5,0.946541,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,0.996855,1,0.5,0.990566,1,0.5,0.5,0.974843,0.5,0.5,0.5,0.5,1,0.5,0.5,0.996855,0.993711,1,0.993711,1,0.5,0.5,0.5,1,0.987421,0.5,0.990566,0.496835,0.5,1,0.5,0.5,0.996855,0.5,0.5,0.977987,0.990566,0.5,0.5,0.971698,1,0.5,0.5,0.5,0.5,1,1,0.5,0.996855,1,0.5,0.5,0.993711,0.496855,0.5,0.5,0.75,0.996855,0.990566,1,0.990566,0.5,0.5,0.981132,1,0.996855,0.987421,0.5,0.996855,0.5,0.990566,0.487421,0.5]
area_under_roc_curve
0.6572327044025157 [0.5,0.987421,1,1,0.996855,0.5,0.5,0.5,0.993711,1,1,0.984277,0.5,0.996855,1,0.5,1,0.974843,0.5,0.5,0.5,0.5,0.5,1,0.5,0.496855,0.481132,0.5,0.993711,0.5,0.5,1,0.990566,0.981132,0.5,0.5,0.5,0.5,1,0.996855,0.5,0.5,0.5,0.5,0.5,0.5,0.75,0.5,0.987421,0.987421,0.484277,0.5,0.5,0.993711,0.5,0.5,1,0.5,0.5,0.977987,0.5,0.5,0.987421,0.5,0.5,0.984277,0.990566,1,0.5,0.5,0.996855,0.5,0.5,1,0.5,0.993711,0.993711,0.987421,1,1,0.5,0.993711,0.5,0.5,0.5,0.5,1,0.484277,0.496855,0.5,0.990566,1,0.5,0.962264,0.990566,0.5,0.5,1,0.5,0.5]
area_under_roc_curve
0.6540482445665152 [0.5,0.981132,1,1,0.996855,0.5,0.5,0.75,0.993711,1,1,0.993711,0.5,0.5,1,0.5,1,0.977987,0.5,0.5,0.5,0.75,0.5,1,0.5,0.990566,0.484277,0.5,0.487421,0.5,0.5,1,0.993711,0.987421,0.5,0.5,0.5,0.5,1,0.996855,0.5,0.5,0.5,0.5,0.5,0.5,0.996835,0.5,0.990566,0.481132,0.977987,0.5,0.5,0.996855,0.5,0.5,1,0.5,0.5,0.987421,0.5,0.5,0.990566,0.5,0.5,0.471698,0.984277,1,0.5,0.5,1,0.5,0.5,0.5,0.5,0.990566,0.993711,0.481132,1,1,0.5,0.993711,0.5,0.5,0.5,0.5,1,0.477987,1,0.5,0.496855,0.996835,0.5,0.974843,0.987421,0.5,0.5,1,0.5,0.5]
area_under_roc_curve
0.6603375527426156 [0.474843,0.5,1,1,0.5,0.990566,0.75,0.996855,0.496835,1,0.990566,0.993711,0.5,0.5,1,0.996855,1,0.987421,0.5,0.496855,0.5,1,0.493711,1,0.5,0.490566,0.984277,0.5,0.5,0.996855,0.5,0.996835,0.990566,0.987421,0.5,0.5,0.5,0.5,0.75,1,0.496855,0.5,0.5,0.5,0.75,0.5,0.996855,0.5,0.971698,0.974843,0.5,0.5,0.5,0.5,0.5,0.493711,1,1,0.5,0.5,0.5,0.5,0.5,0.5,0.990566,0.993711,0.5,0.996855,0.5,0.990566,0.993711,0.493711,0.5,0.75,0.5,0.5,1,0.990566,0.993711,0.5,0.5,1,0.990566,0.990566,0.5,0.5,1,0.5,0.993711,0.5,0.5,1,0.5,0.5,0.977987,0.5,0.968553,0.5,0.5,0.496855]
area_under_roc_curve
0.6446142823023642 [0.996855,0.5,0.993711,1,0.5,0.996855,0.5,0.990566,0.5,1,0.993711,0.996855,0.5,0.5,1,0.990566,1,0.477987,0.5,0.496855,0.5,0.5,0.993711,1,0.5,0.496855,0.490566,0.5,0.5,0.990566,0.5,0.996835,0.996855,0.990566,0.5,0.5,0.5,0.5,0.5,1,0.984277,0.5,0.5,0.5,0.5,0.5,0.990566,0.5,0.981132,0.977987,0.5,0.5,0.5,0.5,0.5,0.984277,1,1,0.5,0.5,0.5,0.5,0.5,0.5,0.984277,0.993711,0.5,0.996855,0.5,0.987421,0.993711,0.496855,0.5,0.75,0.5,0.5,0.993711,0.993711,0.993711,0.5,0.5,0.493711,0.984277,0.490566,0.5,0.5,0.75,0.5,0.996855,0.5,0.5,0.996835,0.5,0.5,0.987421,0.5,0.962264,0.5,0.5,0.990566]
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
0.27006725134699333
kappa
0.3077407174323474
kappa
0.32022029897718335
kappa
0.2951819075712881
kappa
0.33265129456205245
kappa
0.35796058066800424
kappa
0.314007001534044
kappa
0.30757730741993866
kappa
0.3201668109213943
kappa
0.28886091881686593
kb_relative_information_score
43.74684128665788
kb_relative_information_score
49.75993570286525
kb_relative_information_score
51.76430050826775
kb_relative_information_score
47.755570897462825
kb_relative_information_score
53.76866531367023
kb_relative_information_score
57.77739492447514
kb_relative_information_score
50.76211810556649
kb_relative_information_score
49.75993570286524
kb_relative_information_score
51.76430050826776
kb_relative_information_score
46.753388494761595
mean_absolute_error
0.01450000000000001
mean_absolute_error
0.013750000000000009
mean_absolute_error
0.013500000000000009
mean_absolute_error
0.014000000000000009
mean_absolute_error
0.013250000000000008
mean_absolute_error
0.012750000000000008
mean_absolute_error
0.013625000000000009
mean_absolute_error
0.013750000000000009
mean_absolute_error
0.013500000000000009
mean_absolute_error
0.014125000000000009
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
0.275
predictive_accuracy
0.3125
predictive_accuracy
0.325
predictive_accuracy
0.3
predictive_accuracy
0.3375
predictive_accuracy
0.3625
predictive_accuracy
0.31875
predictive_accuracy
0.3125
predictive_accuracy
0.325
predictive_accuracy
0.29375
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
0.275 [0,0,0.5,1,0,1,0,1,0,1,0,0,0,0,1,0,0,0,0,1,0,0,1,1,0,0,0,0,0,0,0,1,0,0,0,1,1,1,1,0,1,1,1,0,0,0,1,1,0,0,0,0,1,0,1,0,1,1,1,0,1,1,0,0,1,0,0,1,1,0,0,1,0,0,0,0,0,0,1,0.5,0,0,1,1,0,0,0.5,0,0,1,0,1,0,0,0,0,1,0,0,1]
recall
0.3125 [1,0,0.5,1,0,1,0,1,0,1,0,0,0,0,1,1,0,0,0,1,1,0,1,1,1,0,0,0,0,1,0,1,0,0,0,1,1,1,1,0,1,1,0.5,0,0.5,0,1,1,0,0,0,0,1,0,1,0,1,1,1,0,1,1,0,0,1,0,0,1,0,1,0,1,0,0.5,0,0,0,0,1,0.5,0,0,1,1,0,0,1,0,0,1,0,1,0,0,0,0,1,0,0,0]
recall
0.325 [0,0,1,1,0,1,1,0,1,1,0,0,1,0,1,0,0,0,1,0,1,0,0,1,1,0,0,1,0,0,1,1,0,0,1,1,1,1,1,0,0,1,1,1,0.5,1,0,1,0,0,0,1,1,0,1,0,1,0,1,0,1,0,0,0,0,0,0,1,1,0,0,0.5,1,0.5,1,0,0,0,0.5,0,0,0,0,0,1,1,1,0,0,0,0,1,1,0,0,1,0,0,0,0]
recall
0.3 [0,0,0.5,1,0,0,1,0,0.5,0.5,0,0,1,0,1,0,0,0,1,0,0,1,0,1,0,0,0,1,0,0,1,1,0,0,1,1,1,0,1,0,0,1,1,1,0.5,1,0,1,0,0,0,1,1,0,1,0,1,0,1,0,1,1,0,1,0,0,0,1,1,0,0,0,1,0,1,0,0,0,1,0.5,0,0,0,0,1,1,1,0,0,1,0,1,1,0,0,1,0,0,0,0]
recall
0.3375 [0,1,1,1,1,0,1,1,0,0.5,0,0,1,0,0,0,0,0,1,0,0,1,0,1,0,0,0,1,1,0,1,1,0,0,1,0.5,0,0,0.5,1,0,0,1,1,1,1,1,0,0,0,0,0,0,1,0,0,1,0,0,1,0,0,1,1,0,0,0,1,0,0,0,0,1,1,0,1,0.5,0,0,1,1,0,0,0,1,1,1,1,0,0,1,0.5,1,1,0,1,0,1,0,0]
recall
0.3625 [0,1,1,1,1,0,1,1,1,0.5,0,0,1,1,1,0,0,0,1,0,0,0,0,1,0,0,0,1,1,0,1,1,0,0,1,0,0,0,0,1,0,0,1,1,1,1,1,0,0,0,1,1,0,1,0,0,1,0,0,1,0,0,1,1,0,0,1,1,0,0,0,0,1,1,0,1,1,0,0,1,0,0,0,0.5,1,1,1,1,0,0,1,1,1,1,0,1,0,1,0,0]
recall
0.31875 [0,1,1,1,1,0,0,0,1,1,1,1,0,1,1,0,1,1,0,0,0,0,0,1,0,0,0,0,1,0,0,1,1,1,0,0,0,0,1,1,0,0,0,0,0,0,0.5,0,1,1,0,0,0,1,0,0,1,0,0,1,0,0,1,0,0,1,1,1,0,0,1,0,0,1,0,1,1,1,1,1,0,1,0,0,0,0,1,0,0,0,1,1,0,1,1,0,0,1,0,0]
recall
0.3125 [0,1,1,1,1,0,0,0.5,1,1,1,1,0,0,1,0,1,1,0,0,0,0.5,0,1,0,1,0,0,0,0,0,1,1,1,0,0,0,0,1,1,0,0,0,0,0,0,1,0,1,0,1,0,0,1,0,0,1,0,0,1,0,0,1,0,0,0,1,1,0,0,1,0,0,0,0,1,1,0,1,1,0,1,0,0,0,0,1,0,1,0,0,1,0,1,1,0,0,1,0,0]
recall
0.325 [0,0,1,1,0,1,0.5,1,0,1,1,1,0,0,1,1,1,1,0,0,0,1,0,1,0,0,1,0,0,1,0,1,1,1,0,0,0,0,0.5,1,0,0,0,0,0.5,0,1,0,1,1,0,0,0,0,0,0,1,1,0,0,0,0,0,0,1,1,0,1,0,1,1,0,0,0.5,0,0,1,1,1,0,0,1,1,1,0,0,1,0,1,0,0,1,0,0,1,0,1,0,0,0]
recall
0.29375 [1,0,1,1,0,1,0,1,0,1,1,1,0,0,1,1,1,0,0,0,0,0,1,1,0,0,0,0,0,1,0,1,1,1,0,0,0,0,0,1,1,0,0,0,0,0,1,0,1,1,0,0,0,0,0,1,1,1,0,0,0,0,0,0,1,1,0,1,0,1,1,0,0,0.5,0,0,1,1,1,0,0,0,1,0,0,0,0.5,0,1,0,0,1,0,0,1,0,1,0,0,1]
relative_absolute_error
0.7323232323232315
relative_absolute_error
0.6944444444444438
relative_absolute_error
0.681818181818181
relative_absolute_error
0.7070707070707063
relative_absolute_error
0.6691919191919184
relative_absolute_error
0.6439393939393934
relative_absolute_error
0.6881313131313125
relative_absolute_error
0.6944444444444438
relative_absolute_error
0.681818181818181
relative_absolute_error
0.7133838383838377
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
0.12041594578792299
root_mean_squared_error
0.11726039399558577
root_mean_squared_error
0.11618950038622254
root_mean_squared_error
0.11832159566199237
root_mean_squared_error
0.11510864433221342
root_mean_squared_error
0.11291589790636218
root_mean_squared_error
0.11672617529928755
root_mean_squared_error
0.11726039399558577
root_mean_squared_error
0.11618950038622254
root_mean_squared_error
0.11884864324004717
root_relative_squared_error
1.2102257907706577
root_relative_squared_error
1.1785113019775786
root_relative_squared_error
1.167748416242284
root_relative_squared_error
1.189176780021126
root_relative_squared_error
1.156885404170974
root_relative_squared_error
1.1348474733984242
root_relative_squared_error
1.1731422020635969
root_relative_squared_error
1.1785113019775786
root_relative_squared_error
1.167748416242284
root_relative_squared_error
1.1944738074849846
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
597.5887040001453
usercpu_time_millis
593.9489520001189
usercpu_time_millis
594.9822049999511
usercpu_time_millis
601.1737960000119
usercpu_time_millis
607.7681399999619
usercpu_time_millis
608.1638260000091
usercpu_time_millis
602.5770279998142
usercpu_time_millis
619.2365790002441
usercpu_time_millis
607.8662599998097
usercpu_time_millis
607.7176520000194
usercpu_time_millis_testing
53.7093420000474
usercpu_time_millis_testing
53.61752600015279
usercpu_time_millis_testing
53.4915609998734
usercpu_time_millis_testing
55.00770300000113
usercpu_time_millis_testing
54.20897099998001
usercpu_time_millis_testing
55.079527000089
usercpu_time_millis_testing
53.162237999913486
usercpu_time_millis_testing
53.91060000010839
usercpu_time_millis_testing
55.526181000004726
usercpu_time_millis_testing
56.92479000003914
usercpu_time_millis_training
543.8793620000979
usercpu_time_millis_training
540.3314259999661
usercpu_time_millis_training
541.4906440000777
usercpu_time_millis_training
546.1660930000107
usercpu_time_millis_training
553.5591689999819
usercpu_time_millis_training
553.0842989999201
usercpu_time_millis_training
549.4147899999007
usercpu_time_millis_training
565.3259790001357
usercpu_time_millis_training
552.340078999805
usercpu_time_millis_training
550.7928619999802