10012757
6892
Scikit-learn Bot
9954
Supervised Classification
8918
sklearn.pipeline.Pipeline(columntransformer=sklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,standardscaler=sklearn.preprocessing.data.StandardScaler),nominal=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)),variancethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,randomforestclassifier=sklearn.ensemble.forest.RandomForestClassifier)(2)
7937478
n_jobs
null
8891
remainder
"passthrough"
8891
sparse_threshold
0.3
8891
transformer_weights
null
8891
memory
null
8892
axis
0
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copy
true
8893
missing_values
"NaN"
8893
strategy
"most_frequent"
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verbose
0
8893
copy
true
8894
with_mean
true
8894
with_std
true
8894
memory
null
8895
copy
true
8896
fill_value
-1
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missing_values
NaN
8896
strategy
"constant"
8896
verbose
0
8896
categorical_features
null
8897
categories
null
8897
dtype
{"oml-python:serialized_object": "type", "value": "np.float64"}
8897
handle_unknown
"ignore"
8897
n_values
null
8897
sparse
true
8897
threshold
0.0
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memory
null
8918
bootstrap
false
8919
class_weight
null
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criterion
"gini"
8919
max_depth
null
8919
max_features
0.6187760943501224
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max_leaf_nodes
null
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min_impurity_decrease
0.0
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min_impurity_split
null
8919
min_samples_leaf
20
8919
min_samples_split
6
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min_weight_fraction_leaf
0.0
8919
n_estimators
100
8919
n_jobs
null
8919
oob_score
false
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random_state
45362
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verbose
0
8919
warm_start
false
8919
openml-python
Sklearn_0.20.2.
1491
one-hundred-plants-margin
https://www.openml.org/data/download/1592283/phpCsX3fx
-1
20946037
description
https://api.openml.org/data/download/20946037/description.xml
-1
20946038
predictions
https://api.openml.org/data/download/20946038/predictions.arff
area_under_roc_curve
0.9876481613005049 [0.975892,0.99637,0.996173,0.999211,0.997633,0.992424,0.994515,0.992069,0.993529,0.999527,0.990294,0.995818,0.995541,0.976444,0.994081,0.990254,0.998067,0.970999,0.981376,0.970052,0.998658,0.996488,0.990925,0.999882,0.995305,0.950324,0.960109,0.991319,0.987176,0.996252,0.995857,0.997554,0.9927,0.984099,0.995226,0.992227,0.984809,0.977194,0.992109,0.996883,0.998224,0.995423,0.996409,0.989978,0.99203,0.998935,0.991753,0.993292,0.990609,0.993332,0.990372,0.983625,0.99128,0.973485,0.983902,0.975458,0.999448,0.988913,0.985993,0.972617,0.99929,0.9942,0.948686,0.990136,0.992385,0.992977,0.969894,0.985361,0.939157,0.976089,0.973445,0.996173,0.98907,0.996528,0.951389,0.98544,0.996173,0.968711,0.997711,0.992622,0.971985,0.991241,0.994318,0.994634,0.988163,0.99274,0.998185,0.98256,0.994003,0.997909,0.99633,0.996607,0.988755,0.973603,0.987098,0.991832,0.987453,0.981771,0.96512,0.994634]
average_cost
0
kappa
0.5593434343434344
kb_relative_information_score
1001.5393799105361
mean_absolute_error
0.015522115299989625
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]
predictive_accuracy
0.56375
prior_entropy
6.6438561897747395
recall
0.56375 [0.3125,0.9375,0.875,0.875,0.8125,0.375,0.8125,0.5,0.4375,1,0.625,0.875,0.75,0.4375,0.75,0.625,0.9375,0.375,0.125,0.125,1,0.625,0.5,1,0.5,0,0,0.3125,0.75,0.625,0.875,0.9375,0.8125,0.375,0.75,0.75,0.625,0.25,0.25,0.8125,0.875,0.75,0.8125,0.3125,0.4375,0.9375,0.875,0.5625,0.625,0.6875,0.625,0.5,0.5625,0.25,0.625,0.125,1,0.6875,0,0.25,1,0.9375,0.5625,0.6875,0.8125,0.875,0.125,0.1875,0,0.25,0,0.5,0.5625,0.8125,0.0625,0,0.8125,0.125,0.9375,0.125,0.0625,0.6875,0.4375,0.8125,0.625,0.625,0.875,0.5625,0.75,0.875,0.8125,0.8125,0.375,0.1875,0.625,0.625,0.375,0.0625,0.1875,0.8125]
relative_absolute_error
0.7839452171711918
root_mean_prior_squared_error
0.09949874371066209
root_mean_squared_error
0.08350070248344807
root_relative_squared_error
0.8392136359657404
total_cost
0
area_under_roc_curve
0.9866760210174352 [0.993711,0.987342,1,1,0.993671,1,1,1,0.990506,1,0.981013,0.993671,0.987342,0.949367,0.993671,0.974843,1,0.962025,0.968354,0.981132,1,1,0.987421,1,0.993711,0.987342,0.889241,1,0.968354,1,0.968354,0.993671,0.974684,0.96519,1,0.962264,1,0.993711,1,1,1,1,0.996835,0.977848,1,1,0.993711,1,1,0.96519,0.990506,1,0.987421,0.974684,1,1,1,1,0.981132,0.981013,1,1,0.990506,0.990506,1,1,0.984177,0.993711,1,1,0.949367,1,0.981013,1,1,0.990506,1,0.974684,1,1,0.962025,0.996835,0.993711,1,0.974684,0.990506,1,1,0.996835,0.993711,0.993671,1,0.990506,0.984177,1,0.981013,1,0.993671,0.85443,1]
area_under_roc_curve
0.9859010528620333 [0.974843,1,1,1,1,0.987421,0.990506,1,1,1,1,0.996835,1,0.984177,1,1,0.993671,0.920886,0.977848,0.981132,1,0.993711,1,1,1,0.927215,0.974684,0.981013,1,0.981132,1,1,1,0.990506,0.993671,0.974843,0.968553,1,0.987421,1,1,1,1,0.987342,0.996835,1,1,1,0.996835,1,1,0.927215,1,1,0.987421,0.974843,1,1,1,0.914557,1,0.968553,1,0.977848,1,0.990506,0.996835,1,0.698113,0.981132,0.955696,1,1,0.996835,1,0.993671,0.990506,0.927215,1,0.984177,0.939873,0.987342,0.974843,0.993711,0.981013,1,0.993671,1,1,1,0.993671,1,0.993671,0.958861,1,1,0.993711,0.955696,0.990506,1]
area_under_roc_curve
0.9903165054533873 [1,1,1,1,0.990506,1,1,0.996835,0.990506,1,1,1,1,0.990506,1,1,1,0.977848,0.968553,0.920886,1,0.981132,0.987342,1,1,0.990506,0.987342,1,1,1,1,1,0.987342,0.974684,1,1,0.993711,0.937107,1,1,0.990506,1,1,0.993711,0.993671,1,0.971519,1,0.971519,1,1,1,1,0.996835,1,1,1,1,0.968553,0.974684,1,0.987421,0.996835,1,0.984177,0.981013,0.990506,0.996835,0.987421,0.962025,0.949367,1,1,1,1,0.993671,1,0.93038,0.987342,0.996835,0.993711,1,0.996835,1,1,1,1,0.981013,1,1,1,1,1,0.962025,0.987342,1,0.984177,0.977848,0.987421,0.974684]
area_under_roc_curve
0.9926498686410316 [0.977848,1,0.996835,1,0.996835,0.993671,1,0.996835,0.993671,1,0.984177,1,1,0.981013,0.996835,1,1,0.993671,0.949686,0.984177,1,1,0.996835,1,0.981132,0.974684,0.971519,1,1,1,1,1,1,0.987342,0.993711,1,1,1,1,1,0.996835,1,1,1,1,1,0.993671,1,0.993671,1,0.990506,1,0.993711,0.927215,1,0.990506,1,1,1,0.996835,1,0.993711,0.990506,1,0.993671,1,0.96519,0.971519,0.993711,0.987342,0.990506,0.996835,0.981132,1,0.993711,0.987342,0.996835,0.971519,1,0.993671,0.949686,0.990506,1,0.993671,1,1,1,1,1,1,0.993671,1,0.987421,0.984177,1,0.993711,0.990506,0.993671,1,1]
area_under_roc_curve
0.9854201496696119 [0.981013,1,1,1,1,0.993671,1,0.996835,1,1,0.993671,0.984177,1,0.886792,1,0.987342,1,0.993671,1,0.987342,0.996835,1,1,1,0.993671,0.968354,0.96519,1,1,0.996835,1,1,1,0.968354,1,1,0.993671,0.914557,0.990506,1,1,1,1,1,0.987421,1,1,1,0.993671,1,1,0.962264,0.996835,0.993711,0.943038,0.962025,1,0.977848,0.990506,0.974843,0.996835,1,0.987421,1,0.984177,1,0.937107,0.933544,0.870253,0.974684,0.990506,1,1,0.993711,0.870253,0.993711,0.993671,0.977848,1,0.987421,1,1,0.987342,1,0.955975,0.974843,1,1,1,0.993671,1,0.993671,0.955975,1,0.924051,1,0.993671,1,0.987421,0.990506]
area_under_roc_curve
0.9913089125069657 [0.952532,1,1,1,1,0.984177,1,0.984177,1,1,0.981013,1,1,0.993711,0.993711,1,1,0.987342,0.993711,0.958861,1,1,0.993671,1,0.996835,0.984177,0.981013,1,1,0.993671,1,1,0.981013,0.996835,0.993711,0.993671,0.971519,0.993671,0.993671,0.993671,1,0.990506,0.993711,0.993711,0.993711,1,0.996835,0.996835,0.996835,0.990506,1,1,0.987342,1,0.993671,0.977848,1,1,0.993671,0.993711,1,1,0.987421,1,1,1,0.993711,1,0.977848,1,0.984177,0.984177,1,1,0.943038,0.962264,1,0.968354,1,0.987421,0.955975,0.981013,1,0.996835,0.962264,1,1,0.993711,0.977848,1,1,0.996835,0.943396,1,1,1,1,0.974843,1,0.993671]
area_under_roc_curve
0.9927837154685136 [1,0.993711,0.987421,1,1,1,0.993671,1,1,1,1,1,1,1,1,0.981013,1,1,0.990506,0.968354,0.990506,1,0.987342,1,0.990506,0.899371,0.955975,0.993671,0.993711,0.996835,1,0.981132,1,0.974843,1,1,0.990506,0.993671,1,1,1,1,1,0.987342,0.968553,0.993671,0.990506,0.990506,0.993711,1,0.955975,1,1,1,0.990506,1,1,0.990506,0.987342,0.987421,1,1,1,0.993671,0.996835,1,0.943396,1,0.987342,0.974684,1,1,1,1,1,0.974843,1,0.993711,1,0.993711,0.981013,1,1,1,1,0.990506,1,0.90566,1,1,1,1,0.984177,0.943396,0.987421,0.993671,1,0.993711,1,1]
area_under_roc_curve
0.9887929404506007 [1,1,1,0.993671,1,0.990506,1,1,0.993711,1,0.981132,1,0.993671,1,0.974843,0.990506,1,0.968553,0.968354,0.984177,1,1,1,1,0.996835,0.981132,0.968553,0.971519,0.874214,0.987342,1,1,1,0.993711,1,1,0.981013,0.977848,0.993671,1,1,1,1,0.993671,0.993711,0.996835,1,0.996835,0.993711,1,0.968553,0.993671,0.981013,1,0.996835,0.949367,1,1,0.974684,0.943396,1,0.993671,0.987421,0.993671,0.996835,0.949686,0.974843,0.977848,0.955696,0.974684,0.981132,1,1,1,0.981013,1,1,0.968553,1,1,0.977848,0.962264,0.984177,1,1,0.984177,1,0.943396,1,1,1,0.990506,1,0.930818,1,0.977848,0.974684,0.981132,0.971519,1]
area_under_roc_curve
0.9887071093065837 [0.968553,0.996835,1,1,1,0.993711,0.977848,0.962264,0.990506,1,0.981132,1,1,1,0.990506,0.962264,1,1,1,1,1,0.984177,0.943396,0.996835,1,0.855346,0.968553,1,0.996835,1,0.981013,1,1,1,0.996835,1,1,0.971519,0.993671,0.974843,0.993711,0.984177,0.996835,0.984177,0.987342,1,1,0.990506,0.981132,1,1,0.981013,1,0.943038,0.996835,0.968553,0.996835,0.993711,1,0.968354,1,1,1,0.984177,1,1,0.968354,1,0.952532,1,1,0.981132,0.971519,0.984177,0.93038,0.974684,1,1,1,0.993671,0.984177,1,1,0.993711,1,1,1,0.987342,0.987421,0.996835,1,0.996835,1,0.968354,0.981132,0.990506,0.993711,0.993671,0.971519,1]
area_under_roc_curve
0.9852372920149669 [0.886792,1,0.955975,1,1,0.993711,1,0.968553,0.996835,1,1,1,1,0.993671,1,0.987421,1,0.962264,0.993671,1,1,1,1,1,1,0.880503,0.993711,0.987342,0.996835,1,1,0.996835,1,1,0.984177,1,0.981013,0.987342,0.981013,1,1,1,0.984177,0.993671,0.993671,1,1,0.977848,0.993711,0.993711,0.981013,0.996835,0.993671,0.974684,1,0.949686,1,0.90566,0.990506,0.984177,1,1,0.727848,0.981013,1,1,0.993671,0.974843,0.949367,0.949686,0.943396,0.993711,0.96519,1,0.924051,0.987342,1,0.981132,0.987421,0.993671,0.996835,0.987421,1,0.968553,0.993671,0.996835,0.984177,0.984177,1,0.996835,1,1,0.987342,0.990506,1,1,0.943396,1,0.996835,1]
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
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average_cost
0
kappa
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kappa
0.595895816890292
kappa
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kappa
0.5768866435112094
kappa
0.5830207305034552
kappa
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kappa
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kappa
0.5831688639772638
kappa
0.4633838383838384
kappa
0.5201830880321983
kb_relative_information_score
99.07748761130955
kb_relative_information_score
99.3136244219044
kb_relative_information_score
100.93677541799377
kb_relative_information_score
101.94017225603221
kb_relative_information_score
98.54652484480135
kb_relative_information_score
100.79989019571696
kb_relative_information_score
102.61830414745894
kb_relative_information_score
99.69593068492155
kb_relative_information_score
99.8544322527512
kb_relative_information_score
98.75623807764391
mean_absolute_error
0.015610576812441651
mean_absolute_error
0.015466778032531703
mean_absolute_error
0.015461333767641552
mean_absolute_error
0.01554187243838349
mean_absolute_error
0.015519721574568454
mean_absolute_error
0.015547212414316055
mean_absolute_error
0.015294674364841207
mean_absolute_error
0.015562526288337814
mean_absolute_error
0.015631122944982152
mean_absolute_error
0.015585334361852313
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
0.54375
predictive_accuracy
0.6
predictive_accuracy
0.58125
predictive_accuracy
0.58125
predictive_accuracy
0.5875
predictive_accuracy
0.59375
predictive_accuracy
0.56875
predictive_accuracy
0.5875
predictive_accuracy
0.46875
predictive_accuracy
0.525
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
0.54375 [1,1,1,1,0.5,1,1,1,0,1,0.5,0.5,0.5,0,1,0,1,0,0,0,1,0,0,1,0,0,0,1,0.5,0,0.5,1,0.5,0,1,0,1,1,0,0.5,1,1,1,0,0,1,1,1,1,0.5,1,0,1,0,1,0,1,1,0,0,1,1,0.5,0.5,1,1,0,0,0,1,0,1,0,1,0,0,0.5,0.5,1,0,0,1,0,1,0.5,0.5,1,1,0.5,1,0.5,1,1,0.5,1,0.5,1,0,0,1]
recall
0.6 [1,1,1,1,1,1,0.5,1,0.5,1,1,1,0.5,0.5,1,1,0.5,0,0,0,1,1,1,1,1,0,0,0.5,1,0,1,1,0.5,0,0,0,0,1,0,1,1,1,1,0.5,1,1,1,0,0.5,1,1,0,0,0.5,1,0,1,1,0,0.5,1,1,1,0.5,1,0.5,0,1,0,0,0,1,1,0.5,0,0,0.5,0.5,1,0,0,0.5,0,1,0.5,1,0.5,1,1,1,1,1,0.5,0,0.5,0.5,0,0.5,0.5,1]
recall
0.58125 [0,1,1,1,0.5,0.5,1,0,1,1,1,1,1,0.5,1,1,1,0,0,0,1,0,0,1,1,0,0,1,1,1,1,1,1,0,1,1,1,0,1,1,0.5,0,1,1,0,1,0.5,1,0.5,0.5,1,1,1,0,1,0,1,1,0,0,1,1,0.5,1,0.5,1,0.5,0,0,0,0,1,1,0.5,0,0,1,0,0.5,0.5,0,1,0.5,1,1,1,1,0.5,1,1,1,1,0,0,0.5,1,0,0,0,0.5]
recall
0.58125 [0,1,1,1,1,0,1,0.5,0.5,1,0.5,1,1,0.5,1,0.5,1,0.5,0,0,1,1,1,1,0,0,0,0,1,0.5,1,1,1,0.5,1,1,1,0,1,1,0.5,1,1,1,1,1,1,1,0.5,0,0,1,0,0,1,0.5,1,0.5,0,1,1,0,0.5,1,1,1,0,0.5,0,0.5,0,0.5,1,1,0,0,1,0,1,0,0,0.5,1,1,1,0,1,1,0.5,1,0,1,0,0,1,0,0,0,0,0.5]
recall
0.5875 [0.5,0,1,1,1,1,1,0.5,0,1,1,0.5,0,0,1,0.5,1,0.5,0,0.5,1,1,0.5,1,0,0,0,0,1,1,1,1,1,0,1,1,0.5,0,0.5,1,1,1,1,1,1,1,1,0.5,0.5,1,1,0,0.5,0,0,0,1,0.5,0,1,1,1,1,1,0.5,1,0,0,0,0.5,0,0.5,1,1,0,0,0.5,0,1,0,1,1,0,1,0,0,1,0,1,1,1,1,0,0,0,1,0.5,0,0,1]
recall
0.59375 [0,1,1,1,1,0,1,0,1,1,0,1,0,1,1,1,1,0.5,0,0,1,1,0.5,1,1,0,0,0,0,1,1,1,0.5,0.5,1,0.5,0.5,0.5,0,0.5,1,0.5,0,1,1,1,1,0,0.5,0.5,1,1,0.5,1,0.5,0.5,1,1,0,0,1,1,0,1,1,1,1,0,0,0,0,0.5,1,1,0.5,0,1,0,1,0,0,0.5,0.5,0.5,0,1,1,1,0.5,1,1,0.5,0,1,1,1,1,0,0,1]
recall
0.56875 [0.5,1,0,0.5,1,0,0.5,1,1,1,1,1,1,1,1,1,1,1,0,0,1,0.5,0.5,1,0.5,0,0,0,0,0.5,1,0,1,1,1,1,0.5,0.5,0,1,1,0.5,1,0,0,0.5,0.5,0.5,1,1,0,1,1,0,0.5,0,1,0.5,0,0,1,1,1,0.5,0.5,1,0,0.5,0,0,0,0,0.5,1,0,0,1,0,1,0,0,1,0.5,1,1,0.5,1,0,1,1,1,1,0.5,0,0,0.5,1,0,0,1]
recall
0.5875 [0.5,1,1,0.5,1,0,1,1,1,1,0,1,1,0,0,0.5,1,1,0,0,1,0.5,0.5,1,0.5,0,0,0.5,0,0.5,1,1,1,1,1,1,1,0,0.5,1,1,1,1,0,0,1,1,0.5,1,1,0,0.5,0.5,1,1,0,1,1,0,0,1,1,1,1,1,0,0,0,0,0.5,0,0.5,0.5,1,0,0,1,0,1,1,0,0,0,1,0,0.5,1,0,1,1,1,0.5,1,0,1,0.5,0,0,0.5,0.5]
recall
0.46875 [0,1,1,1,0.5,0,0.5,0,0,1,0,1,1,0.5,0.5,0,1,1,1,1,1,0,0,1,0.5,0,0,0,1,1,0.5,1,1,1,0.5,0.5,0.5,0,0,0,1,0.5,0.5,0,0,1,1,1,0,1,0.5,0.5,0.5,0.5,0,0,1,0,0,0,1,1,0.5,0.5,1,1,0,0,0,0,0,0,0,0.5,0,0,1,0,1,0,0,1,1,0,1,1,1,0.5,0,0.5,1,0.5,0,0,0,0.5,0,0,0,1]
recall
0.525 [0,1,0,1,1,1,1,0,0,1,1,1,1,0.5,0,0,1,0,0,0,1,1,1,1,0.5,0,0,0,1,0,1,1,1,1,0.5,1,0.5,0,0,1,1,1,0.5,0,0.5,1,1,0.5,1,1,0.5,0.5,0.5,0,1,0,1,0,0,0,1,1,0,0.5,1,1,0,0,0,0,0,0,0.5,1,0,0,1,0,1,0,0,0,1,0,1,0.5,0.5,0,1,0.5,1,1,0,0.5,1,1,0,0,0.5,1]
relative_absolute_error
0.7884129703253346
relative_absolute_error
0.781150405683418
relative_absolute_error
0.7808754428101782
relative_absolute_error
0.7849430524436092
relative_absolute_error
0.7838243219479004
relative_absolute_error
0.7852127481977792
relative_absolute_error
0.7724583012546051
relative_absolute_error
0.7859861761786762
relative_absolute_error
0.7894506537869761
relative_absolute_error
0.7871380990834489
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
0.08414249535706407
root_mean_squared_error
0.08333648644211775
root_mean_squared_error
0.08280067637166075
root_mean_squared_error
0.08312388523081848
root_mean_squared_error
0.08353760766549144
root_mean_squared_error
0.08344979210918092
root_mean_squared_error
0.08238616488243461
root_mean_squared_error
0.08338646669777439
root_mean_squared_error
0.08436671808707281
root_mean_squared_error
0.0844528598727954
root_relative_squared_error
0.8456638970412201
root_relative_squared_error
0.8375632026516491
root_relative_squared_error
0.8321781088255894
root_relative_squared_error
0.8354264800823924
root_relative_squared_error
0.8395845470010667
root_relative_squared_error
0.8387019674524657
root_relative_squared_error
0.8280121116102724
root_relative_squared_error
0.8380655231211617
root_relative_squared_error
0.8479174202682145
root_relative_squared_error
0.8487831777894661
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
2172.017302000313
usercpu_time_millis
2178.7210019974736
usercpu_time_millis
2221.4590159928775
usercpu_time_millis
2167.2233319986844
usercpu_time_millis
2212.205746996915
usercpu_time_millis
2156.113565994019
usercpu_time_millis
2172.904360006214
usercpu_time_millis
2176.9417250034166
usercpu_time_millis
2179.642208000587
usercpu_time_millis
2252.253820995975
usercpu_time_millis_testing
37.79978599777678
usercpu_time_millis_testing
37.551556997641455
usercpu_time_millis_testing
37.60833299747901
usercpu_time_millis_testing
37.558080002781935
usercpu_time_millis_testing
38.3263559997431
usercpu_time_millis_testing
37.842792000446934
usercpu_time_millis_testing
37.57642400159966
usercpu_time_millis_testing
37.576430004264694
usercpu_time_millis_testing
37.567617000604514
usercpu_time_millis_testing
37.70575799717335
usercpu_time_millis_training
2134.2175160025363
usercpu_time_millis_training
2141.169444999832
usercpu_time_millis_training
2183.8506829953985
usercpu_time_millis_training
2129.6652519959025
usercpu_time_millis_training
2173.879390997172
usercpu_time_millis_training
2118.270773993572
usercpu_time_millis_training
2135.3279360046145
usercpu_time_millis_training
2139.365294999152
usercpu_time_millis_training
2142.0745909999823
usercpu_time_millis_training
2214.5480629988015