119
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Python_3.9.18. Sklearn_0.24.0. NumPy_1.26.3. SciPy_1.10.0.
cv
{"oml-python:serialized_object": "cv_object", "value": {"name": "sklearn.model_selection._split.StratifiedKFold", "parameters": {"n_splits": "2", "random_state": "62501", "shuffle": "true"}}}
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error_score
NaN
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n_iter
5
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n_jobs
null
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param_distributions
{"bootstrap": [true, false], "criterion": ["gini", "entropy"], "max_depth": [3, null], "max_features": [1, 2, 3, 4], "min_samples_leaf": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10], "min_samples_split": [2, 3, 4, 5, 6, 7, 8, 9, 10]}
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pre_dispatch
"2*n_jobs"
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random_state
12172
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refit
true
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return_train_score
false
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scoring
null
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verbose
0
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bootstrap
true
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ccp_alpha
0.0
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class_weight
null
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criterion
"gini"
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max_depth
null
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max_features
"auto"
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max_leaf_nodes
null
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max_samples
null
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min_impurity_decrease
0.0
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min_impurity_split
null
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min_samples_leaf
1
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min_samples_split
2
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min_weight_fraction_leaf
0.0
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n_estimators
5
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n_jobs
null
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oob_score
false
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random_state
33003
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verbose
0
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warm_start
false
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openml-python
Sklearn_0.24.0.
usercpu_time_millis_training
92.5849999999997
wall_clock_time_millis_training
92.58317947387695
usercpu_time_millis_testing
1.207799999999537
usercpu_time_millis
93.79279999999923
wall_clock_time_millis_testing
1.2099742889404297
wall_clock_time_millis
101.89056396484375
predictive_accuracy
0.7075098814229249