Run
10315573

Run 10315573

Task 10101 (Supervised Classification) blood-transfusion-service-center Uploaded 13-08-2019 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.C58ffa214d1ba1(n3=sklearn.pipeline.C58ffa214d1b21(n4=sklea rn.pipeline.C379fc54d0303ab(n5=sklearn.compose._column_transformer.C8e65d02 14f5f(n6=sklearn.preprocessing._function_transformer.C58ffa214d1980)),n7=sk learn.pipeline.C379fc54d030cbb(n8=sklearn.compose._column_transformer.C8e65 d0214f79(n9=sklearn.preprocessing._function_transformer.C379fc54d030a52))), n10=fastsklearnfeature.transformations.IdentityTransformation.C379fc54d0312 fd,c=sklearn.linear_model.logistic.LogisticRegression)(1)Automatically created scikit-learn flow.
sklearn.linear_model.logistic.LogisticRegression(28)_C0.01
sklearn.linear_model.logistic.LogisticRegression(28)_class_weight"balanced"
sklearn.linear_model.logistic.LogisticRegression(28)_dualfalse
sklearn.linear_model.logistic.LogisticRegression(28)_fit_intercepttrue
sklearn.linear_model.logistic.LogisticRegression(28)_intercept_scaling1
sklearn.linear_model.logistic.LogisticRegression(28)_max_iter10000
sklearn.linear_model.logistic.LogisticRegression(28)_multi_class"auto"
sklearn.linear_model.logistic.LogisticRegression(28)_n_jobsnull
sklearn.linear_model.logistic.LogisticRegression(28)_penalty"l2"
sklearn.linear_model.logistic.LogisticRegression(28)_random_state39878
sklearn.linear_model.logistic.LogisticRegression(28)_solver"lbfgs"
sklearn.linear_model.logistic.LogisticRegression(28)_tol0.0001
sklearn.linear_model.logistic.LogisticRegression(28)_verbose0
sklearn.linear_model.logistic.LogisticRegression(28)_warm_startfalse
sklearn.pipeline.C58ffa214d1ba1(n3=sklearn.pipeline.C58ffa214d1b21(n4=sklearn.pipeline.C379fc54d0303ab(n5=sklearn.compose._column_transformer.C8e65d0214f5f(n6=sklearn.preprocessing._function_transformer.C58ffa214d1980)),n7=sklearn.pipeline.C379fc54d030cbb(n8=sklearn.compose._column_transformer.C8e65d0214f79(n9=sklearn.preprocessing._function_transformer.C379fc54d030a52))),n10=fastsklearnfeature.transformations.IdentityTransformation.C379fc54d0312fd,c=sklearn.linear_model.logistic.LogisticRegression)(1)_memorynull
sklearn.pipeline.C58ffa214d1ba1(n3=sklearn.pipeline.C58ffa214d1b21(n4=sklearn.pipeline.C379fc54d0303ab(n5=sklearn.compose._column_transformer.C8e65d0214f5f(n6=sklearn.preprocessing._function_transformer.C58ffa214d1980)),n7=sklearn.pipeline.C379fc54d030cbb(n8=sklearn.compose._column_transformer.C8e65d0214f79(n9=sklearn.preprocessing._function_transformer.C379fc54d030a52))),n10=fastsklearnfeature.transformations.IdentityTransformation.C379fc54d0312fd,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.C58ffa214d1b21(n4=sklearn.pipeline.C379fc54d0303ab(n5=sklearn.compose._column_transformer.C8e65d0214f5f(n6=sklearn.preprocessing._function_transformer.C58ffa214d1980)),n7=sklearn.pipeline.C379fc54d030cbb(n8=sklearn.compose._column_transformer.C8e65d0214f79(n9=sklearn.preprocessing._function_transformer.C379fc54d030a52)))(1)_n_jobsnull
sklearn.pipeline.C58ffa214d1b21(n4=sklearn.pipeline.C379fc54d0303ab(n5=sklearn.compose._column_transformer.C8e65d0214f5f(n6=sklearn.preprocessing._function_transformer.C58ffa214d1980)),n7=sklearn.pipeline.C379fc54d030cbb(n8=sklearn.compose._column_transformer.C8e65d0214f79(n9=sklearn.preprocessing._function_transformer.C379fc54d030a52)))(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.C58ffa214d1b21(n4=sklearn.pipeline.C379fc54d0303ab(n5=sklearn.compose._column_transformer.C8e65d0214f5f(n6=sklearn.preprocessing._function_transformer.C58ffa214d1980)),n7=sklearn.pipeline.C379fc54d030cbb(n8=sklearn.compose._column_transformer.C8e65d0214f79(n9=sklearn.preprocessing._function_transformer.C379fc54d030a52)))(1)_transformer_weightsnull
sklearn.pipeline.C379fc54d0303ab(n5=sklearn.compose._column_transformer.C8e65d0214f5f(n6=sklearn.preprocessing._function_transformer.C58ffa214d1980))(1)_memorynull
sklearn.pipeline.C379fc54d0303ab(n5=sklearn.compose._column_transformer.C8e65d0214f5f(n6=sklearn.preprocessing._function_transformer.C58ffa214d1980))(1)_steps[{"oml-python:serialized_object": "component_reference", "value": {"key": "n5", "step_name": "n5"}}]
sklearn.compose._column_transformer.C8e65d0214f5f(n6=sklearn.preprocessing._function_transformer.C58ffa214d1980)(1)_n_jobsnull
sklearn.compose._column_transformer.C8e65d0214f5f(n6=sklearn.preprocessing._function_transformer.C58ffa214d1980)(1)_remainder"drop"
sklearn.compose._column_transformer.C8e65d0214f5f(n6=sklearn.preprocessing._function_transformer.C58ffa214d1980)(1)_sparse_threshold0.3
sklearn.compose._column_transformer.C8e65d0214f5f(n6=sklearn.preprocessing._function_transformer.C58ffa214d1980)(1)_transformer_weightsnull
sklearn.compose._column_transformer.C8e65d0214f5f(n6=sklearn.preprocessing._function_transformer.C58ffa214d1980)(1)_transformers[{"oml-python:serialized_object": "component_reference", "value": {"key": "n6", "step_name": "n6", "argument_1": [0]}}]
sklearn.preprocessing._function_transformer.C58ffa214d1980(1)_accept_sparsefalse
sklearn.preprocessing._function_transformer.C58ffa214d1980(1)_check_inversetrue
sklearn.preprocessing._function_transformer.C58ffa214d1980(1)_func{"oml-python:serialized_object": "function", "value": "fastsklearnfeature.candidates.Identity.identity"}
sklearn.preprocessing._function_transformer.C58ffa214d1980(1)_inv_kw_argsnull
sklearn.preprocessing._function_transformer.C58ffa214d1980(1)_inverse_funcnull
sklearn.preprocessing._function_transformer.C58ffa214d1980(1)_kw_argsnull
sklearn.preprocessing._function_transformer.C58ffa214d1980(1)_pass_y"deprecated"
sklearn.preprocessing._function_transformer.C58ffa214d1980(1)_validatefalse
sklearn.pipeline.C379fc54d030cbb(n8=sklearn.compose._column_transformer.C8e65d0214f79(n9=sklearn.preprocessing._function_transformer.C379fc54d030a52))(1)_memorynull
sklearn.pipeline.C379fc54d030cbb(n8=sklearn.compose._column_transformer.C8e65d0214f79(n9=sklearn.preprocessing._function_transformer.C379fc54d030a52))(1)_steps[{"oml-python:serialized_object": "component_reference", "value": {"key": "n8", "step_name": "n8"}}]
sklearn.compose._column_transformer.C8e65d0214f79(n9=sklearn.preprocessing._function_transformer.C379fc54d030a52)(1)_n_jobsnull
sklearn.compose._column_transformer.C8e65d0214f79(n9=sklearn.preprocessing._function_transformer.C379fc54d030a52)(1)_remainder"drop"
sklearn.compose._column_transformer.C8e65d0214f79(n9=sklearn.preprocessing._function_transformer.C379fc54d030a52)(1)_sparse_threshold0.3
sklearn.compose._column_transformer.C8e65d0214f79(n9=sklearn.preprocessing._function_transformer.C379fc54d030a52)(1)_transformer_weightsnull
sklearn.compose._column_transformer.C8e65d0214f79(n9=sklearn.preprocessing._function_transformer.C379fc54d030a52)(1)_transformers[{"oml-python:serialized_object": "component_reference", "value": {"key": "n9", "step_name": "n9", "argument_1": [2]}}]
sklearn.preprocessing._function_transformer.C379fc54d030a52(1)_accept_sparsefalse
sklearn.preprocessing._function_transformer.C379fc54d030a52(1)_check_inversetrue
sklearn.preprocessing._function_transformer.C379fc54d030a52(1)_func{"oml-python:serialized_object": "function", "value": "fastsklearnfeature.candidates.Identity.identity"}
sklearn.preprocessing._function_transformer.C379fc54d030a52(1)_inv_kw_argsnull
sklearn.preprocessing._function_transformer.C379fc54d030a52(1)_inverse_funcnull
sklearn.preprocessing._function_transformer.C379fc54d030a52(1)_kw_argsnull
sklearn.preprocessing._function_transformer.C379fc54d030a52(1)_pass_y"deprecated"
sklearn.preprocessing._function_transformer.C379fc54d030a52(1)_validatefalse
fastsklearnfeature.transformations.IdentityTransformation.C379fc54d0312fd(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

0.7314 ± 0.0431
Per class
Cross-validation details (10-fold Crossvalidation)
0.6428 ± 0.0456
Per class
Cross-validation details (10-fold Crossvalidation)
0.2489 ± 0.0735
Cross-validation details (10-fold Crossvalidation)
-0.3379 ± 0.0646
Cross-validation details (10-fold Crossvalidation)
0.4199 ± 0.0164
Cross-validation details (10-fold Crossvalidation)
0.363 ± 0.0023
Cross-validation details (10-fold Crossvalidation)
748
Per class
Cross-validation details (10-fold Crossvalidation)
0.7684 ± 0.037
Per class
Cross-validation details (10-fold Crossvalidation)
0.615 ± 0.0471
Cross-validation details (10-fold Crossvalidation)
0.7916 ± 0.0072
Cross-validation details (10-fold Crossvalidation)
0.615 ± 0.0471
Per class
Cross-validation details (10-fold Crossvalidation)
1.1566 ± 0.0457
Cross-validation details (10-fold Crossvalidation)
0.4258 ± 0.0027
Cross-validation details (10-fold Crossvalidation)
0.4602 ± 0.0146
Cross-validation details (10-fold Crossvalidation)
1.0807 ± 0.035
Cross-validation details (10-fold Crossvalidation)