Run
10228426

Run 10228426

Task 3638 (Supervised Classification) quake Uploaded 06-06-2019 by Felix Neutatz
0 likes downloaded by 0 people 0 issues 0 downvotes , 0 total downloads
  • ComplexityDriven openml-python Sklearn_0.20.3.
Issue #Downvotes for this reason By


Flow

sklearn.pipeline.C58aa21cbe60a7(n3=sklearn.compose._column_transformer.C58a a21cbe5fd7(n4=sklearn.preprocessing._function_transformer.C376a551f6fbbe3), n5=fastsklearnfeature.transformations.mdlp_discretization.MDLPDiscretizerTr ansformation.C376a551f6fc23f,c=sklearn.linear_model.logistic.LogisticRegres sion)(1)Automatically created scikit-learn flow.
sklearn.linear_model.logistic.LogisticRegression(23)_C0.001
sklearn.linear_model.logistic.LogisticRegression(23)_class_weight"balanced"
sklearn.linear_model.logistic.LogisticRegression(23)_dualfalse
sklearn.linear_model.logistic.LogisticRegression(23)_fit_intercepttrue
sklearn.linear_model.logistic.LogisticRegression(23)_intercept_scaling1
sklearn.linear_model.logistic.LogisticRegression(23)_max_iter10000
sklearn.linear_model.logistic.LogisticRegression(23)_multi_class"auto"
sklearn.linear_model.logistic.LogisticRegression(23)_n_jobsnull
sklearn.linear_model.logistic.LogisticRegression(23)_penalty"l2"
sklearn.linear_model.logistic.LogisticRegression(23)_random_state43214
sklearn.linear_model.logistic.LogisticRegression(23)_solver"lbfgs"
sklearn.linear_model.logistic.LogisticRegression(23)_tol0.0001
sklearn.linear_model.logistic.LogisticRegression(23)_verbose0
sklearn.linear_model.logistic.LogisticRegression(23)_warm_startfalse
sklearn.pipeline.C58aa21cbe60a7(n3=sklearn.compose._column_transformer.C58aa21cbe5fd7(n4=sklearn.preprocessing._function_transformer.C376a551f6fbbe3),n5=fastsklearnfeature.transformations.mdlp_discretization.MDLPDiscretizerTransformation.C376a551f6fc23f,c=sklearn.linear_model.logistic.LogisticRegression)(1)_memorynull
sklearn.pipeline.C58aa21cbe60a7(n3=sklearn.compose._column_transformer.C58aa21cbe5fd7(n4=sklearn.preprocessing._function_transformer.C376a551f6fbbe3),n5=fastsklearnfeature.transformations.mdlp_discretization.MDLPDiscretizerTransformation.C376a551f6fc23f,c=sklearn.linear_model.logistic.LogisticRegression)(1)_steps[{"oml-python:serialized_object": "component_reference", "value": {"key": "n3", "step_name": "n3"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "n5", "step_name": "n5"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "c", "step_name": "c"}}]
sklearn.compose._column_transformer.C58aa21cbe5fd7(n4=sklearn.preprocessing._function_transformer.C376a551f6fbbe3)(1)_n_jobsnull
sklearn.compose._column_transformer.C58aa21cbe5fd7(n4=sklearn.preprocessing._function_transformer.C376a551f6fbbe3)(1)_remainder"drop"
sklearn.compose._column_transformer.C58aa21cbe5fd7(n4=sklearn.preprocessing._function_transformer.C376a551f6fbbe3)(1)_sparse_threshold0.3
sklearn.compose._column_transformer.C58aa21cbe5fd7(n4=sklearn.preprocessing._function_transformer.C376a551f6fbbe3)(1)_transformer_weightsnull
sklearn.compose._column_transformer.C58aa21cbe5fd7(n4=sklearn.preprocessing._function_transformer.C376a551f6fbbe3)(1)_transformers[{"oml-python:serialized_object": "component_reference", "value": {"key": "n4", "step_name": "n4", "argument_1": [0]}}]
sklearn.preprocessing._function_transformer.C376a551f6fbbe3(1)_accept_sparsefalse
sklearn.preprocessing._function_transformer.C376a551f6fbbe3(1)_check_inversetrue
sklearn.preprocessing._function_transformer.C376a551f6fbbe3(1)_func{"oml-python:serialized_object": "function", "value": "fastsklearnfeature.candidates.Identity.identity"}
sklearn.preprocessing._function_transformer.C376a551f6fbbe3(1)_inv_kw_argsnull
sklearn.preprocessing._function_transformer.C376a551f6fbbe3(1)_inverse_funcnull
sklearn.preprocessing._function_transformer.C376a551f6fbbe3(1)_kw_argsnull
sklearn.preprocessing._function_transformer.C376a551f6fbbe3(1)_pass_y"deprecated"
sklearn.preprocessing._function_transformer.C376a551f6fbbe3(1)_validatefalse

Result files

xml
Description

XML file describing the run, including user-defined evaluation measures.

arff
Predictions

ARFF file with instance-level predictions generated by the model.

15 Evaluation measures

Area under ROC curve
0.5
Per class
Cross-validation details (10-fold Crossvalidation)
KB relative information score
-0.0187 ± 0.0004
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.5
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.4939 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
Number of instances
2178
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.5551 ± 0.0011
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.9912 ± 0.0003
Cross-validation details (10-fold Crossvalidation)
Recall
0.5551 ± 0.0011
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
1.0123 ± 0.0002
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.497 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.5
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
1.0061 ± 0.0002
Cross-validation details (10-fold Crossvalidation)