Run
10228994

Run 10228994

Task 31 (Supervised Classification) credit-g Uploaded 04-07-2019 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.C58cd5178ca5c4(n3=sklearn.pipeline.C58cd5178ca511(n4=sklea rn.pipeline.C58cd5178ca39d(n5=sklearn.compose._column_transformer.C58cd5178 ca345(n6=sklearn.preprocessing._function_transformer.C8e154f27a9e4)),n7=skl earn.pipeline.C378052eb7e6ef7(n8=sklearn.compose._column_transformer.C37805 2eb7e6cb4(n9=sklearn.preprocessing._function_transformer.C58cd5178ca456))), n10=fastsklearnfeature.transformations.IdentityTransformation.C58cd5178ca5a 0,c=sklearn.linear_model.logistic.LogisticRegression)(1)Automatically created scikit-learn flow.
sklearn.linear_model.logistic.LogisticRegression(23)_C0.1
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_state61529
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.C58cd5178ca5c4(n3=sklearn.pipeline.C58cd5178ca511(n4=sklearn.pipeline.C58cd5178ca39d(n5=sklearn.compose._column_transformer.C58cd5178ca345(n6=sklearn.preprocessing._function_transformer.C8e154f27a9e4)),n7=sklearn.pipeline.C378052eb7e6ef7(n8=sklearn.compose._column_transformer.C378052eb7e6cb4(n9=sklearn.preprocessing._function_transformer.C58cd5178ca456))),n10=fastsklearnfeature.transformations.IdentityTransformation.C58cd5178ca5a0,c=sklearn.linear_model.logistic.LogisticRegression)(1)_memorynull
sklearn.pipeline.C58cd5178ca5c4(n3=sklearn.pipeline.C58cd5178ca511(n4=sklearn.pipeline.C58cd5178ca39d(n5=sklearn.compose._column_transformer.C58cd5178ca345(n6=sklearn.preprocessing._function_transformer.C8e154f27a9e4)),n7=sklearn.pipeline.C378052eb7e6ef7(n8=sklearn.compose._column_transformer.C378052eb7e6cb4(n9=sklearn.preprocessing._function_transformer.C58cd5178ca456))),n10=fastsklearnfeature.transformations.IdentityTransformation.C58cd5178ca5a0,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": "n10", "step_name": "n10"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "c", "step_name": "c"}}]
sklearn.pipeline.C58cd5178ca511(n4=sklearn.pipeline.C58cd5178ca39d(n5=sklearn.compose._column_transformer.C58cd5178ca345(n6=sklearn.preprocessing._function_transformer.C8e154f27a9e4)),n7=sklearn.pipeline.C378052eb7e6ef7(n8=sklearn.compose._column_transformer.C378052eb7e6cb4(n9=sklearn.preprocessing._function_transformer.C58cd5178ca456)))(1)_n_jobsnull
sklearn.pipeline.C58cd5178ca511(n4=sklearn.pipeline.C58cd5178ca39d(n5=sklearn.compose._column_transformer.C58cd5178ca345(n6=sklearn.preprocessing._function_transformer.C8e154f27a9e4)),n7=sklearn.pipeline.C378052eb7e6ef7(n8=sklearn.compose._column_transformer.C378052eb7e6cb4(n9=sklearn.preprocessing._function_transformer.C58cd5178ca456)))(1)_transformer_list[{"oml-python:serialized_object": "component_reference", "value": {"key": "n4", "step_name": "n4"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "n7", "step_name": "n7"}}]
sklearn.pipeline.C58cd5178ca511(n4=sklearn.pipeline.C58cd5178ca39d(n5=sklearn.compose._column_transformer.C58cd5178ca345(n6=sklearn.preprocessing._function_transformer.C8e154f27a9e4)),n7=sklearn.pipeline.C378052eb7e6ef7(n8=sklearn.compose._column_transformer.C378052eb7e6cb4(n9=sklearn.preprocessing._function_transformer.C58cd5178ca456)))(1)_transformer_weightsnull
sklearn.pipeline.C58cd5178ca39d(n5=sklearn.compose._column_transformer.C58cd5178ca345(n6=sklearn.preprocessing._function_transformer.C8e154f27a9e4))(1)_memorynull
sklearn.pipeline.C58cd5178ca39d(n5=sklearn.compose._column_transformer.C58cd5178ca345(n6=sklearn.preprocessing._function_transformer.C8e154f27a9e4))(1)_steps[{"oml-python:serialized_object": "component_reference", "value": {"key": "n5", "step_name": "n5"}}]
sklearn.compose._column_transformer.C58cd5178ca345(n6=sklearn.preprocessing._function_transformer.C8e154f27a9e4)(1)_n_jobsnull
sklearn.compose._column_transformer.C58cd5178ca345(n6=sklearn.preprocessing._function_transformer.C8e154f27a9e4)(1)_remainder"drop"
sklearn.compose._column_transformer.C58cd5178ca345(n6=sklearn.preprocessing._function_transformer.C8e154f27a9e4)(1)_sparse_threshold0.3
sklearn.compose._column_transformer.C58cd5178ca345(n6=sklearn.preprocessing._function_transformer.C8e154f27a9e4)(1)_transformer_weightsnull
sklearn.compose._column_transformer.C58cd5178ca345(n6=sklearn.preprocessing._function_transformer.C8e154f27a9e4)(1)_transformers[{"oml-python:serialized_object": "component_reference", "value": {"key": "n6", "step_name": "n6", "argument_1": [0]}}]
sklearn.preprocessing._function_transformer.C8e154f27a9e4(1)_accept_sparsefalse
sklearn.preprocessing._function_transformer.C8e154f27a9e4(1)_check_inversetrue
sklearn.preprocessing._function_transformer.C8e154f27a9e4(1)_func{"oml-python:serialized_object": "function", "value": "fastsklearnfeature.candidates.Identity.identity"}
sklearn.preprocessing._function_transformer.C8e154f27a9e4(1)_inv_kw_argsnull
sklearn.preprocessing._function_transformer.C8e154f27a9e4(1)_inverse_funcnull
sklearn.preprocessing._function_transformer.C8e154f27a9e4(1)_kw_argsnull
sklearn.preprocessing._function_transformer.C8e154f27a9e4(1)_pass_y"deprecated"
sklearn.preprocessing._function_transformer.C8e154f27a9e4(1)_validatefalse
sklearn.pipeline.C378052eb7e6ef7(n8=sklearn.compose._column_transformer.C378052eb7e6cb4(n9=sklearn.preprocessing._function_transformer.C58cd5178ca456))(1)_memorynull
sklearn.pipeline.C378052eb7e6ef7(n8=sklearn.compose._column_transformer.C378052eb7e6cb4(n9=sklearn.preprocessing._function_transformer.C58cd5178ca456))(1)_steps[{"oml-python:serialized_object": "component_reference", "value": {"key": "n8", "step_name": "n8"}}]
sklearn.compose._column_transformer.C378052eb7e6cb4(n9=sklearn.preprocessing._function_transformer.C58cd5178ca456)(1)_n_jobsnull
sklearn.compose._column_transformer.C378052eb7e6cb4(n9=sklearn.preprocessing._function_transformer.C58cd5178ca456)(1)_remainder"drop"
sklearn.compose._column_transformer.C378052eb7e6cb4(n9=sklearn.preprocessing._function_transformer.C58cd5178ca456)(1)_sparse_threshold0.3
sklearn.compose._column_transformer.C378052eb7e6cb4(n9=sklearn.preprocessing._function_transformer.C58cd5178ca456)(1)_transformer_weightsnull
sklearn.compose._column_transformer.C378052eb7e6cb4(n9=sklearn.preprocessing._function_transformer.C58cd5178ca456)(1)_transformers[{"oml-python:serialized_object": "component_reference", "value": {"key": "n9", "step_name": "n9", "argument_1": [11]}}]
sklearn.preprocessing._function_transformer.C58cd5178ca456(1)_accept_sparsefalse
sklearn.preprocessing._function_transformer.C58cd5178ca456(1)_check_inversetrue
sklearn.preprocessing._function_transformer.C58cd5178ca456(1)_func{"oml-python:serialized_object": "function", "value": "fastsklearnfeature.candidates.Identity.identity"}
sklearn.preprocessing._function_transformer.C58cd5178ca456(1)_inv_kw_argsnull
sklearn.preprocessing._function_transformer.C58cd5178ca456(1)_inverse_funcnull
sklearn.preprocessing._function_transformer.C58cd5178ca456(1)_kw_argsnull
sklearn.preprocessing._function_transformer.C58cd5178ca456(1)_pass_y"deprecated"
sklearn.preprocessing._function_transformer.C58cd5178ca456(1)_validatefalse
fastsklearnfeature.transformations.IdentityTransformation.C58cd5178ca5a0(1)_number_parent_featuresnull

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.

17 Evaluation measures

0.7285 ± 0.0418
Per class
Cross-validation details (10-fold Crossvalidation)
0.6913 ± 0.0436
Per class
Cross-validation details (10-fold Crossvalidation)
0.3423 ± 0.0862
Cross-validation details (10-fold Crossvalidation)
-0.0352 ± 0.055
Cross-validation details (10-fold Crossvalidation)
0.4189 ± 0.0162
Cross-validation details (10-fold Crossvalidation)
0.4202
Cross-validation details (10-fold Crossvalidation)
1000
Per class
Cross-validation details (10-fold Crossvalidation)
0.7446 ± 0.0413
Per class
Cross-validation details (10-fold Crossvalidation)
0.678 ± 0.0459
Cross-validation details (10-fold Crossvalidation)
0.8813
Cross-validation details (10-fold Crossvalidation)
0.678 ± 0.0459
Per class
Cross-validation details (10-fold Crossvalidation)
0.9971 ± 0.0386
Cross-validation details (10-fold Crossvalidation)
0.4583
Cross-validation details (10-fold Crossvalidation)
0.4579 ± 0.0174
Cross-validation details (10-fold Crossvalidation)
0.9993 ± 0.0379
Cross-validation details (10-fold Crossvalidation)