9126
3229
Test Test
6
Supervised Classification
31430
sklearn.pipeline.Pipeline(transform=sklearn.compose._column_transformer.ColumnTransformer(cat=sklearn.pipeline.Pipeline(onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder,truncatedsvd=sklearn.decomposition._truncated_svd.TruncatedSVD),cont=sklearn.impute._base.SimpleImputer),estimator=sklearn.ensemble._forest.RandomForestClassifier)(2)
7324
Python_3.8.18. Sklearn_1.3.2. NumPy_1.23.5. SciPy_1.10.1.
bootstrap
true
31001
ccp_alpha
0.0
31001
class_weight
null
31001
criterion
"gini"
31001
max_depth
10
31001
max_features
"sqrt"
31001
max_leaf_nodes
null
31001
max_samples
null
31001
min_impurity_decrease
0.0
31001
min_samples_leaf
1
31001
min_samples_split
2
31001
min_weight_fraction_leaf
0.0
31001
n_estimators
50
31001
n_jobs
null
31001
oob_score
false
31001
random_state
43157
31001
verbose
0
31001
warm_start
false
31001
memory
null
31430
steps
[{"oml-python:serialized_object": "component_reference", "value": {"key": "transform", "step_name": "transform"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "estimator", "step_name": "estimator"}}]
31430
verbose
false
31430
n_jobs
null
31432
remainder
"drop"
31432
sparse_threshold
0.3
31432
transformer_weights
null
31432
transformers
[{"oml-python:serialized_object": "component_reference", "value": {"key": "cat", "step_name": "cat", "argument_1": {"oml-python:serialized_object": "function", "value": "openml.extensions.sklearn.cat"}}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "cont", "step_name": "cont", "argument_1": {"oml-python:serialized_object": "function", "value": "openml.extensions.sklearn.cont"}}}]
31432
verbose
false
31432
verbose_feature_names_out
true
31432
memory
null
31433
steps
[{"oml-python:serialized_object": "component_reference", "value": {"key": "onehotencoder", "step_name": "onehotencoder"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "truncatedsvd", "step_name": "truncatedsvd"}}]
31433
verbose
false
31433
categories
"auto"
31434
drop
null
31434
dtype
{"oml-python:serialized_object": "type", "value": "np.float64"}
31434
feature_name_combiner
"concat"
31434
handle_unknown
"ignore"
31434
max_categories
null
31434
min_frequency
null
31434
sparse
false
31434
sparse_output
true
31434
algorithm
"randomized"
31436
n_components
2
31436
n_iter
5
31436
n_oversamples
10
31436
power_iteration_normalizer
"auto"
31436
random_state
51015
31436
tol
0.0
31436
add_indicator
false
31437
copy
true
31437
fill_value
null
31437
keep_empty_features
false
31437
missing_values
NaN
31437
strategy
"median"
31437
openml-python
Sklearn_1.3.2.
1
anneal
https://www.openml.org/data/download/1666876/phpFsFYVN
-1
22551
description
https://test.openml.org/data/download/22551/description.xml
-1
22552
predictions
https://test.openml.org/data/download/22552/predictions.arff
area_under_roc_curve
0.9978196469020465 [0.999144,0.995506,0.997725,0.0,1,1]
average_cost
0
f_measure
0.9371672809172809 [0.666667,0.727273,0.964286,0.0,1,0.969697]
kappa
0.859668693178649
kb_relative_information_score
0.8359978293001734
mean_absolute_error
0.03719987933890885
mean_prior_absolute_error
0.1410223830024713
weighted_recall
0.9425675675675675 [0.5,0.606061,0.995392,0.0,1,0.941176]
number_of_instances
296 [4,33,217,0,25,17]
precision
0.9422604422604421 [1,0.909091,0.935065,0.0,1,1]
predictive_accuracy
0.9425675675675675
prior_entropy
1.3089517057560913
relative_absolute_error
0.2637870566848736
root_mean_prior_squared_error
0.2709125098701948
root_mean_squared_error
0.10991759019451373
root_relative_squared_error
0.40573095073084564
total_cost
0
area_under_roc_curve
0.9978196469020465 [0.999144,0.995506,0.997725,0.0,1,1]
average_cost
0
f_measure
0.9371672809172809 [0.666667,0.727273,0.964286,0.0,1,0.969697]
kappa
0.859668693178649
kb_relative_information_score
0.8359978293001734
mean_absolute_error
0.03719987933890885
mean_prior_absolute_error
0.1410223830024713
weighted_recall
0.9425675675675675 [0.5,0.606061,0.995392,0.0,1,0.941176]
number_of_instances
296 [4,33,217,0,25,17]
precision
0.9422604422604421 [1,0.909091,0.935065,0.0,1,1]
predictive_accuracy
0.9425675675675675
prior_entropy
1.3089517057560913
relative_absolute_error
0.2637870566848736
root_mean_prior_squared_error
0.2709125098701948
root_mean_squared_error
0.10991759019451373
root_relative_squared_error
0.40573095073084564
total_cost
0
usercpu_time_millis
524.8671000000015
usercpu_time_millis_testing
43.556741999999815
usercpu_time_millis_training
481.31035800000177
wall_clock_time_millis
150.64692497253418
wall_clock_time_millis_training
133.27383995056152
wall_clock_time_millis_testing
17.373085021972656