10417068
1140
Andreas Mueller
9956
Supervised Classification
17315
sklearn.pipeline.Pipeline(columntransformer=sklearn.compose._column_transformer.ColumnTransformer(cont=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,standardscaler=sklearn.preprocessing.data.StandardScaler)),decisiontreeclassifier=sklearn.tree.tree.DecisionTreeClassifier)(1)
8254316
copy
true
17283
with_mean
true
17283
with_std
true
17283
ccp_alpha
0.0
17313
class_weight
null
17313
criterion
"gini"
17313
max_depth
1
17313
max_features
null
17313
max_leaf_nodes
null
17313
min_impurity_decrease
0.0
17313
min_impurity_split
null
17313
min_samples_leaf
1
17313
min_samples_split
2
17313
min_weight_fraction_leaf
0.0
17313
presort
"deprecated"
17313
random_state
50158
17313
splitter
"best"
17313
memory
null
17315
steps
[{"oml-python:serialized_object": "component_reference", "value": {"key": "columntransformer", "step_name": "columntransformer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "decisiontreeclassifier", "step_name": "decisiontreeclassifier"}}]
17315
verbose
false
17315
n_jobs
null
17316
remainder
"drop"
17316
sparse_threshold
0.3
17316
transformer_weights
null
17316
transformers
[{"oml-python:serialized_object": "component_reference", "value": {"key": "cont", "step_name": "cont", "argument_1": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63]}}]
17316
verbose
false
17316
memory
null
17317
steps
[{"oml-python:serialized_object": "component_reference", "value": {"key": "simpleimputer", "step_name": "simpleimputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "standardscaler", "step_name": "standardscaler"}}]
17317
verbose
false
17317
add_indicator
false
17318
copy
true
17318
fill_value
null
17318
missing_values
NaN
17318
strategy
"median"
17318
verbose
0
17318
openml-python
Sklearn_0.22.dev0.
1493
one-hundred-plants-texture
https://www.openml.org/data/download/1592285/phpoOxxNn
-1
21756209
description
https://api.openml.org/data/download/21756209/description.xml
-1
21756210
predictions
https://api.openml.org/data/download/21756210/predictions.arff
area_under_roc_curve
0.45797554029116916 [0.435122,0.442751,0.439316,0.430512,0.443422,0.444232,0.443422,0.440027,0.444232,0.443422,0.439316,0.444232,0.443422,0.442534,0.373539,0.443422,0.442534,0.439316,0.442534,0.444232,0.44204,0.443422,0.442534,0.444232,0.444232,0.44204,0.442751,0.443422,0.442534,0.44204,0.443422,0.444232,0.439316,0.439316,0.439316,0.444232,0.442751,0.439316,0.444232,0.444232,0.442534,0.442751,0.442751,0.442534,0.390437,0.439316,0.442534,0.439316,0.444133,0.444232,0.442751,0.443837,0.439316,0.443422,0.440027,0.442534,0.442396,0.442751,0.549984,0.442751,0.852693,0.444232,0.71111,0.442751,0.443422,0.444133,0.710656,0.442751,0.442751,0.442534,0.441349,0.365564,0.733141,0.442751,0.442534,0.443422,0.443422,0.434953,0.439316,0.679051,0.442751,0.443837,0.442396,0.640122,0.442751,0.442534,0.442534,0.444232,0.40779,0.444232,0.482806,0.43144,0.439316,0.442396,0.444133,0.444232,0.440027,0.439316,0.442534,0.442751]
average_cost
0
kappa
0.00315855969677827
kb_relative_information_score
0.018568912140564886
mean_absolute_error
0.01966707876403231
mean_prior_absolute_error
0.019799992711748222
number_of_instances
1599 [15,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16]
predictive_accuracy
0.013133208255159474
prior_entropy
6.643827772868604
recall
0.013133208255159476 [0,0.25,0.125,0.1875,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.4375,0,0.3125,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]
relative_absolute_error
0.9932871718868337
root_mean_prior_squared_error
0.09949872432040595
root_mean_squared_error
0.09926128326527564
root_relative_squared_error
0.9976136271419351
total_cost
0
area_under_roc_curve
0.5061858132314314 [0.503165,0.503145,0.503145,0.496835,0.503165,0.503165,0.503165,0.503145,0.503165,0.503165,0.503145,0.503165,0.503165,0.503165,0.503165,0.503165,0.503165,0.503145,0.503165,0.503165,0.503145,0.503165,0.503165,0.503165,0.503165,0.503145,0.503145,0.503165,0.503165,0.503145,0.503165,0.503165,0.503145,0.503145,0.503145,0.503165,0.503145,0.503145,0.503165,0.503165,0.503165,0.503145,0.503145,0.503165,0.503145,0.503145,0.503165,0.503145,0.503165,0.503165,0.503145,0.503165,0.503145,0.503165,0.503145,0.503165,0.503165,0.503145,0.503145,0.503145,1,0.503165,0.503145,0.503145,0.503165,0.503165,0.503165,0.503145,0.503145,0.503165,0.503165,0.503165,0.503145,0.503145,0.503165,0.503165,0.503165,0.503165,0.503145,0.503145,0.503145,0.503165,0.503165,0.503165,0.503145,0.503165,0.503165,0.503165,0.503165,0.503165,0.503165,0.503165,0.503145,0.503165,0.503165,0.503165,0.503145,0.503145,0.503165,0.503145]
area_under_roc_curve
0.5061858132314312 [0.503165,0.503145,0.503145,0.496835,0.503165,0.503165,0.503165,0.503145,0.503165,0.503165,0.503145,0.503165,0.503165,0.503165,0.503165,0.503165,0.503165,0.503145,0.503165,0.503165,0.503165,0.503165,0.503165,0.503165,0.503165,0.503165,0.503145,0.503165,0.503165,0.503165,0.503165,0.503165,0.503145,0.503145,0.503145,0.503165,0.503145,0.503145,0.503165,0.503165,0.503165,0.503145,0.503145,0.503165,0.503145,0.503145,0.503165,0.503145,0.503165,0.503165,0.503145,0.503165,0.503145,0.503165,0.503145,0.503165,0.503145,0.503145,0.503145,0.503145,1,0.503165,0.503145,0.503145,0.503165,0.503165,0.503165,0.503145,0.503145,0.503165,0.503165,0.503165,0.503145,0.503145,0.503165,0.503165,0.503165,0.503165,0.503145,0.503145,0.503145,0.503165,0.503145,0.503165,0.503145,0.503165,0.503165,0.503165,0.503165,0.503165,0.503165,0.503165,0.503145,0.503145,0.503165,0.503165,0.503145,0.503145,0.503165,0.503145]
area_under_roc_curve
0.5121686171483166 [0.509494,0.509434,0.509494,0.490506,0.509494,0.509434,0.509494,0.509434,0.509434,0.509494,0.509494,0.509434,0.509494,0.509494,0.509494,0.509494,0.509494,0.509494,0.509494,0.509434,0.509494,0.509494,0.509494,0.509434,0.509434,0.509494,0.509434,0.509494,0.509494,0.509494,0.509494,0.509434,0.509494,0.509494,0.509494,0.509434,0.509434,0.509494,0.509434,0.509434,0.509494,0.509434,0.509434,0.509494,0.509494,0.509494,0.509494,0.509494,0.509494,0.509434,0.509434,0.509494,0.509494,0.509494,0.509434,0.509494,0.509434,0.509434,0.509434,0.509434,0.996835,0.509434,0.509434,0.509434,0.509494,0.509494,0.509494,0.509434,0.509434,0.509494,0.509494,0.509494,0.509494,0.509434,0.509494,0.509494,0.509494,0.509434,0.509494,0.509494,0.509434,0.509494,0.509434,0.509494,0.509434,0.509494,0.509494,0.509434,0.509494,0.509434,0.509434,0.256329,0.509494,0.509434,0.509494,0.509434,0.509434,0.509494,0.509494,0.509434]
area_under_roc_curve
0.5491735331581883 [0.541139,0.540881,0.541139,0.541139,0.541139,0.540881,0.541139,0.541139,0.540881,0.541139,0.541139,0.540881,0.541139,0.541139,0.03481,0.541139,0.541139,0.541139,0.541139,0.540881,0.541139,0.541139,0.541139,0.540881,0.540881,0.541139,0.540881,0.541139,0.541139,0.541139,0.541139,0.540881,0.541139,0.541139,0.541139,0.540881,0.540881,0.541139,0.540881,0.540881,0.541139,0.540881,0.540881,0.541139,0.287975,0.541139,0.541139,0.541139,0.540881,0.540881,0.540881,0.541139,0.541139,0.541139,0.541139,0.541139,0.540881,0.540881,0.459119,0.540881,0.541139,0.540881,0.962264,0.540881,0.541139,0.540881,0.96519,0.540881,0.540881,0.541139,0.458861,0.458861,0.96519,0.540881,0.541139,0.541139,0.541139,0.459119,0.541139,0.96519,0.540881,0.541139,0.540881,0.96519,0.540881,0.541139,0.541139,0.540881,0.287975,0.540881,0.540881,0.541139,0.541139,0.540881,0.540881,0.540881,0.541139,0.541139,0.541139,0.540881]
area_under_roc_curve
0.5 [0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5]
area_under_roc_curve
0.5515837711965604 [0.528302,0.528481,0.528481,0.528302,0.528302,0.528302,0.528302,0.528481,0.528302,0.528302,0.528481,0.528302,0.528302,0.528481,0.528302,0.528302,0.528481,0.528481,0.528481,0.528302,0.528481,0.528302,0.528481,0.528302,0.528302,0.528481,0.528481,0.528302,0.528481,0.528481,0.528302,0.528302,0.528481,0.528481,0.528481,0.528302,0.528481,0.528481,0.528302,0.528302,0.528481,0.528481,0.528481,0.528481,0.471519,0.528481,0.528481,0.528481,0.528302,0.528302,0.528481,0.528302,0.528481,0.528302,0.528481,0.528481,0.528481,0.528481,0.724684,0.528481,0.528481,0.528302,0.977848,0.528481,0.528302,0.528302,0.977848,0.528481,0.528481,0.528481,0.471698,0.471698,0.977848,0.528481,0.528481,0.528302,0.528302,0.528302,0.528481,0.977848,0.528481,0.528302,0.528481,0.471698,0.528481,0.528481,0.528481,0.528302,0.528481,0.528302,0.528302,0.528481,0.528481,0.528481,0.528302,0.528302,0.528481,0.528481,0.528481,0.528481]
area_under_roc_curve
0.5061808375129372 [0.506289,0.506329,0.506329,0.003145,0.506289,0.506329,0.506289,0.506329,0.506329,0.506289,0.506329,0.506329,0.506289,0.506289,0.506289,0.506289,0.506289,0.506329,0.506289,0.506329,0.506329,0.506289,0.506289,0.506329,0.506329,0.506329,0.506329,0.506289,0.506289,0.506329,0.506289,0.506329,0.506329,0.506329,0.506329,0.506329,0.506329,0.506329,0.506329,0.506329,0.506289,0.506329,0.506329,0.506289,0.506329,0.506329,0.506289,0.506329,0.506289,0.506329,0.506329,0.506289,0.506329,0.506289,0.506329,0.506289,0.506329,0.506329,0.506329,0.506329,0.746835,0.506329,0.506329,0.506329,0.506289,0.506289,0.506289,0.506329,0.506329,0.506289,0.506289,0.506289,0.506329,0.506329,0.506289,0.506289,0.506289,0.506329,0.506329,0.506329,0.506329,0.506289,0.506329,0.506289,0.506329,0.506289,0.506289,0.506329,0.506289,0.506329,0.506329,0.506289,0.506329,0.506329,0.506289,0.506329,0.506329,0.506329,0.506289,0.506329]
area_under_roc_curve
0.5459467797149906 [0.528302,0.528481,0.528481,0.528302,0.528302,0.528481,0.528302,0.528481,0.528481,0.528302,0.528481,0.528481,0.528302,0.528302,0.528302,0.528302,0.528302,0.528481,0.528302,0.528481,0.528302,0.528302,0.528302,0.528481,0.528481,0.528302,0.528481,0.528302,0.528302,0.528302,0.528302,0.528481,0.528481,0.528481,0.528481,0.528481,0.528481,0.528481,0.528481,0.528481,0.528302,0.528481,0.528481,0.528302,0.471519,0.528481,0.528302,0.528481,0.528481,0.528481,0.528481,0.528302,0.528481,0.528302,0.528481,0.528302,0.528481,0.528481,0.724684,0.528481,0.528481,0.528481,0.977848,0.528481,0.528302,0.528481,0.974843,0.528481,0.528481,0.528302,0.471698,0.025157,0.977848,0.528481,0.528302,0.528302,0.528302,0.528481,0.528481,0.724684,0.528481,0.528302,0.528481,0.974843,0.528481,0.528302,0.528302,0.528481,0.528302,0.528481,0.528481,0.528302,0.528481,0.528481,0.528481,0.528481,0.528481,0.528481,0.528302,0.528481]
area_under_roc_curve
0.5061858132314312 [0.503145,0.503165,0.503145,0.496835,0.503165,0.503165,0.503165,0.503165,0.503165,0.503165,0.503145,0.503165,0.503165,0.503145,0.503165,0.503165,0.503145,0.503145,0.503145,0.503165,0.503145,0.503165,0.503145,0.503165,0.503165,0.503145,0.503165,0.503165,0.503145,0.503145,0.503165,0.503165,0.503145,0.503145,0.503145,0.503165,0.503165,0.503145,0.503165,0.503165,0.503145,0.503165,0.503165,0.503145,0.503145,0.503145,0.503145,0.503145,0.503165,0.503165,0.503165,0.503145,0.503145,0.503165,0.503165,0.503145,0.503165,0.503165,0.503165,0.503165,1,0.503165,0.503165,0.503165,0.503165,0.503165,0.503145,0.503165,0.503165,0.503145,0.503165,0.503165,0.503145,0.503165,0.503145,0.503165,0.503165,0.503165,0.503145,0.503145,0.503165,0.503145,0.503165,0.503165,0.503165,0.503145,0.503145,0.503165,0.503145,0.503165,0.503165,0.503145,0.503145,0.503165,0.503165,0.503165,0.503165,0.503145,0.503145,0.503165]
area_under_roc_curve
0.5123888418150003 [0.506329,0.506369,0.506329,0.746815,0.506369,0.506369,0.506369,0.506329,0.506369,0.506369,0.506329,0.506369,0.506369,0.506329,0.506369,0.506369,0.506329,0.506329,0.506329,0.506369,0.506329,0.506369,0.506329,0.506369,0.506369,0.506329,0.506369,0.506369,0.506329,0.506329,0.506369,0.506369,0.506329,0.506329,0.506329,0.506369,0.506369,0.506329,0.506369,0.506369,0.506329,0.506369,0.506369,0.506329,0.506329,0.506329,0.506329,0.506329,0.506369,0.506369,0.506369,0.506369,0.506329,0.506369,0.506329,0.506329,0.506369,0.506369,0.506369,0.506369,0.996835,0.506369,0.506369,0.506369,0.506369,0.506369,0.506329,0.506369,0.506369,0.506329,0.506369,0.506369,0.506329,0.506369,0.506329,0.506369,0.506369,0.506369,0.506329,0.506329,0.506369,0.506369,0.506369,0.506369,0.506369,0.506329,0.506329,0.506369,0.506329,0.506369,0.506369,0.493671,0.506329,0.506369,0.506369,0.506369,0.506329,0.506329,0.506329,0.506369]
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
0.006289308176100629
kappa
0.006289308176100629
kappa
0.012462161418406259
kappa
0.006289308176100629
kappa
0
kappa
0.012229169124297118
kappa
-0.00007862253321802035
kappa
0.012229169124297118
kappa
0.006289308176100629
kappa
0.006329113924050633
kb_relative_information_score
0.008845261973969754
kb_relative_information_score
0.008845261973969754
kb_relative_information_score
0.0149195794708687
kb_relative_information_score
0.04343170533432992
kb_relative_information_score
0.0026091477166615353
kb_relative_information_score
0.04087768176360149
kb_relative_information_score
0.008865413596775697
kb_relative_information_score
0.03714264129602567
kb_relative_information_score
0.008834943238522068
kb_relative_information_score
0.01127305757541274
mean_absolute_error
0.019684860720973855
mean_absolute_error
0.019684860720973855
mean_absolute_error
0.01958518534785659
mean_absolute_error
0.019617275921444518
mean_absolute_error
0.019801351825842764
mean_absolute_error
0.019615864030053262
mean_absolute_error
0.01967885964912286
mean_absolute_error
0.019633812480434144
mean_absolute_error
0.019684772940074986
mean_absolute_error
0.019684050074238794
mean_prior_absolute_error
0.01980002942907592
mean_prior_absolute_error
0.01980002942907592
mean_prior_absolute_error
0.019800029429075917
mean_prior_absolute_error
0.019800029429075917
mean_prior_absolute_error
0.01980002942907591
mean_prior_absolute_error
0.01979995585638609
mean_prior_absolute_error
0.01979995585638609
mean_prior_absolute_error
0.01979995585638609
mean_prior_absolute_error
0.019799955856386102
mean_prior_absolute_error
0.01979995631910742
number_of_instances
160 [2,1,1,2,2,2,2,1,2,2,1,2,2,2,2,2,2,1,2,2,1,2,2,2,2,1,1,2,2,1,2,2,1,1,1,2,1,1,2,2,2,1,1,2,1,1,2,1,2,2,1,2,1,2,1,2,2,1,1,1,1,2,1,1,2,2,2,1,1,2,2,2,1,1,2,2,2,2,1,1,1,2,2,2,1,2,2,2,2,2,2,2,1,2,2,2,1,1,2,1]
number_of_instances
160 [2,1,1,2,2,2,2,1,2,2,1,2,2,2,2,2,2,1,2,2,2,2,2,2,2,2,1,2,2,2,2,2,1,1,1,2,1,1,2,2,2,1,1,2,1,1,2,1,2,2,1,2,1,2,1,2,1,1,1,1,1,2,1,1,2,2,2,1,1,2,2,2,1,1,2,2,2,2,1,1,1,2,1,2,1,2,2,2,2,2,2,2,1,1,2,2,1,1,2,1]
number_of_instances
160 [2,1,2,2,2,1,2,1,1,2,2,1,2,2,2,2,2,2,2,1,2,2,2,1,1,2,1,2,2,2,2,1,2,2,2,1,1,2,1,1,2,1,1,2,2,2,2,2,2,1,1,2,2,2,1,2,1,1,1,1,2,1,1,1,2,2,2,1,1,2,2,2,2,1,2,2,2,1,2,2,1,2,1,2,1,2,2,1,2,1,1,2,2,1,2,1,1,2,2,1]
number_of_instances
160 [2,1,2,2,2,1,2,2,1,2,2,1,2,2,2,2,2,2,2,1,2,2,2,1,1,2,1,2,2,2,2,1,2,2,2,1,1,2,1,1,2,1,1,2,2,2,2,2,1,1,1,2,2,2,2,2,1,1,1,1,2,1,1,1,2,1,2,1,1,2,2,2,2,1,2,2,2,1,2,2,1,2,1,2,1,2,2,1,2,1,1,2,2,1,1,1,2,2,2,1]
number_of_instances
160 [2,2,2,1,1,1,1,2,1,1,2,1,1,2,1,1,2,2,2,1,2,1,2,1,1,2,2,1,2,2,1,1,2,2,2,1,2,2,1,1,2,2,2,2,2,2,2,2,1,1,2,2,2,1,2,2,1,2,2,2,2,1,2,2,1,1,2,2,2,2,1,1,2,2,2,1,1,1,2,2,2,2,1,1,2,2,2,1,2,1,1,2,2,1,1,1,2,2,2,2]
number_of_instances
160 [1,2,2,1,1,1,1,2,1,1,2,1,1,2,1,1,2,2,2,1,2,1,2,1,1,2,2,1,2,2,1,1,2,2,2,1,2,2,1,1,2,2,2,2,2,2,2,2,1,1,2,1,2,1,2,2,2,2,2,2,2,1,2,2,1,1,2,2,2,2,1,1,2,2,2,1,1,1,2,2,2,1,2,1,2,2,2,1,2,1,1,2,2,2,1,1,2,2,2,2]
number_of_instances
160 [1,2,2,1,1,2,1,2,2,1,2,2,1,1,1,1,1,2,1,2,2,1,1,2,2,2,2,1,1,2,1,2,2,2,2,2,2,2,2,2,1,2,2,1,2,2,1,2,1,2,2,1,2,1,2,1,2,2,2,2,2,2,2,2,1,1,1,2,2,1,1,1,2,2,1,1,1,2,2,2,2,1,2,1,2,1,1,2,1,2,2,1,2,2,1,2,2,2,1,2]
number_of_instances
160 [1,2,2,1,1,2,1,2,2,1,2,2,1,1,1,1,1,2,1,2,1,1,1,2,2,1,2,1,1,1,1,2,2,2,2,2,2,2,2,2,1,2,2,1,2,2,1,2,2,2,2,1,2,1,2,1,2,2,2,2,2,2,2,2,1,2,1,2,2,1,1,1,2,2,1,1,1,2,2,2,2,1,2,1,2,1,1,2,1,2,2,1,2,2,2,2,2,2,1,2]
number_of_instances
160 [1,2,1,2,2,2,2,2,2,2,1,2,2,1,2,2,1,1,1,2,1,2,1,2,2,1,2,2,1,1,2,2,1,1,1,2,2,1,2,2,1,2,2,1,1,1,1,1,2,2,2,1,1,2,2,1,2,2,2,2,1,2,2,2,2,2,1,2,2,1,2,2,1,2,1,2,2,2,1,1,2,1,2,2,2,1,1,2,1,2,2,1,1,2,2,2,2,1,1,2]
number_of_instances
159 [1,2,1,2,2,2,2,1,2,2,1,2,2,1,2,2,1,1,1,2,1,2,1,2,2,1,2,2,1,1,2,2,1,1,1,2,2,1,2,2,1,2,2,1,1,1,1,1,2,2,2,2,1,2,1,1,2,2,2,2,1,2,2,2,2,2,1,2,2,1,2,2,1,2,1,2,2,2,1,1,2,2,2,2,2,1,1,2,1,2,2,1,1,2,2,2,1,1,1,2]
predictive_accuracy
0.0125
predictive_accuracy
0.0125
predictive_accuracy
0.01875
predictive_accuracy
0.0125
predictive_accuracy
0.00625
predictive_accuracy
0.01875
predictive_accuracy
0.00625
predictive_accuracy
0.01875
predictive_accuracy
0.0125
predictive_accuracy
0.012578616352201257
prior_entropy
6.644100581449517
prior_entropy
6.644100581449517
prior_entropy
6.644100581449517
prior_entropy
6.644100581449517
prior_entropy
6.644100581449517
prior_entropy
6.643553938691703
prior_entropy
6.643553938691703
prior_entropy
6.643553938691703
prior_entropy
6.643553938691703
prior_entropy
6.64355737669647
recall
0.0125 [0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]
recall
0.0125 [0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]
recall
0.01875 [0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]
recall
0.0125 [0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]
recall
0.00625 [0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]
recall
0.01875 [0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]
recall
0.00625 [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]
recall
0.01875 [0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]
recall
0.0125 [0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]
recall
0.012578616352201259 [0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]
relative_absolute_error
0.9941834072260043
relative_absolute_error
0.9941834072260043
relative_absolute_error
0.9891493049548788
relative_absolute_error
0.9907700385857493
relative_absolute_error
1.0000667876162301
relative_absolute_error
0.99070241228475
relative_absolute_error
0.9938840163007648
relative_absolute_error
0.9916089016987197
relative_absolute_error
0.9941826680247893
relative_absolute_error
0.9941461363348174
root_mean_prior_squared_error
0.09949890883178135
root_mean_prior_squared_error
0.09949890883178135
root_mean_prior_squared_error
0.09949890883178135
root_mean_prior_squared_error
0.09949890883178135
root_mean_prior_squared_error
0.09949890883178135
root_mean_prior_squared_error
0.09949853911503082
root_mean_prior_squared_error
0.09949853911503082
root_mean_prior_squared_error
0.09949853911503082
root_mean_prior_squared_error
0.09949853911503082
root_mean_prior_squared_error
0.0994985414402977
root_mean_squared_error
0.09919656677508504
root_mean_squared_error
0.09919656677508504
root_mean_squared_error
0.09915108137536725
root_mean_squared_error
0.09920636944071876
root_mean_squared_error
0.09951054805729016
root_mean_squared_error
0.09906084690531985
root_mean_squared_error
0.09951744605007061
root_mean_squared_error
0.09916529101465349
root_mean_squared_error
0.09919607491068667
root_mean_squared_error
0.099411836569121
root_relative_squared_error
0.9969613530414945
root_relative_squared_error
0.9969613530414945
root_relative_squared_error
0.9965042083325542
root_relative_squared_error
0.9970598733745193
root_relative_squared_error
1.0001169784236377
root_relative_squared_error
0.9956010187324967
root_relative_squared_error
1.0001900222375921
root_relative_squared_error
0.9966507236855804
root_relative_squared_error
0.9969601141179122
root_relative_squared_error
0.9991285814855013
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
29.205421000028764
usercpu_time_millis
30.245654000054856
usercpu_time_millis
16.001767999910044
usercpu_time_millis
15.316134000045167
usercpu_time_millis
15.384154999992461
usercpu_time_millis
15.525895999871864
usercpu_time_millis
15.484481000157757
usercpu_time_millis
15.293890000066312
usercpu_time_millis
15.658787000006669
usercpu_time_millis
15.344454000000951
usercpu_time_millis_testing
3.1275560000949554
usercpu_time_millis_testing
2.9479820000233303
usercpu_time_millis_testing
0.8572209999329061
usercpu_time_millis_testing
0.8182410000472373
usercpu_time_millis_testing
0.7808450000084122
usercpu_time_millis_testing
0.8241509999606933
usercpu_time_millis_testing
0.8015000000796135
usercpu_time_millis_testing
0.7871200000408862
usercpu_time_millis_testing
0.7840979999400588
usercpu_time_millis_testing
0.8098929999960092
usercpu_time_millis_training
26.07786499993381
usercpu_time_millis_training
27.297672000031525
usercpu_time_millis_training
15.144546999977138
usercpu_time_millis_training
14.49789299999793
usercpu_time_millis_training
14.603309999984049
usercpu_time_millis_training
14.70174499991117
usercpu_time_millis_training
14.682981000078144
usercpu_time_millis_training
14.506770000025426
usercpu_time_millis_training
14.87468900006661
usercpu_time_millis_training
14.534561000004942
wall_clock_time_millis
29.28447723388672
wall_clock_time_millis
30.37571907043457
wall_clock_time_millis
16.005992889404297
wall_clock_time_millis
15.320301055908203
wall_clock_time_millis
15.387773513793945
wall_clock_time_millis
16.201019287109375
wall_clock_time_millis
15.502691268920898
wall_clock_time_millis
15.298128128051758
wall_clock_time_millis
15.66314697265625
wall_clock_time_millis
15.348672866821289
wall_clock_time_millis_testing
3.1728744506835938
wall_clock_time_millis_testing
2.9671192169189453
wall_clock_time_millis_testing
0.8597373962402344
wall_clock_time_millis_testing
0.8208751678466797
wall_clock_time_millis_testing
0.7839202880859375
wall_clock_time_millis_testing
0.8268356323242188
wall_clock_time_millis_testing
0.8046627044677734
wall_clock_time_millis_testing
0.7898807525634766
wall_clock_time_millis_testing
0.7870197296142578
wall_clock_time_millis_testing
0.8132457733154297
wall_clock_time_millis_training
26.111602783203125
wall_clock_time_millis_training
27.408599853515625
wall_clock_time_millis_training
15.146255493164062
wall_clock_time_millis_training
14.499425888061523
wall_clock_time_millis_training
14.603853225708008
wall_clock_time_millis_training
15.374183654785156
wall_clock_time_millis_training
14.698028564453125
wall_clock_time_millis_training
14.508247375488281
wall_clock_time_millis_training
14.876127243041992
wall_clock_time_millis_training
14.53542709350586