Run
10228440

Run 10228440

Task 9971 (Supervised Classification) ilpd 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.C376aa5a9cd1667(n3=sklearn.compose._column_transformer.C37 6aa5a9cd0bb3(n4=sklearn.preprocessing._function_transformer.C58aaa2a9480d5) ,n5=fastsklearnfeature.transformations.mdlp_discretization.MDLPDiscretizerT ransformation.C58aaa2a9481a9,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_state16537
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.C376aa5a9cd1667(n3=sklearn.compose._column_transformer.C376aa5a9cd0bb3(n4=sklearn.preprocessing._function_transformer.C58aaa2a9480d5),n5=fastsklearnfeature.transformations.mdlp_discretization.MDLPDiscretizerTransformation.C58aaa2a9481a9,c=sklearn.linear_model.logistic.LogisticRegression)(1)_memorynull
sklearn.pipeline.C376aa5a9cd1667(n3=sklearn.compose._column_transformer.C376aa5a9cd0bb3(n4=sklearn.preprocessing._function_transformer.C58aaa2a9480d5),n5=fastsklearnfeature.transformations.mdlp_discretization.MDLPDiscretizerTransformation.C58aaa2a9481a9,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.C376aa5a9cd0bb3(n4=sklearn.preprocessing._function_transformer.C58aaa2a9480d5)(1)_n_jobsnull
sklearn.compose._column_transformer.C376aa5a9cd0bb3(n4=sklearn.preprocessing._function_transformer.C58aaa2a9480d5)(1)_remainder"drop"
sklearn.compose._column_transformer.C376aa5a9cd0bb3(n4=sklearn.preprocessing._function_transformer.C58aaa2a9480d5)(1)_sparse_threshold0.3
sklearn.compose._column_transformer.C376aa5a9cd0bb3(n4=sklearn.preprocessing._function_transformer.C58aaa2a9480d5)(1)_transformer_weightsnull
sklearn.compose._column_transformer.C376aa5a9cd0bb3(n4=sklearn.preprocessing._function_transformer.C58aaa2a9480d5)(1)_transformers[{"oml-python:serialized_object": "component_reference", "value": {"key": "n4", "step_name": "n4", "argument_1": [0]}}]
sklearn.preprocessing._function_transformer.C58aaa2a9480d5(1)_accept_sparsefalse
sklearn.preprocessing._function_transformer.C58aaa2a9480d5(1)_check_inversetrue
sklearn.preprocessing._function_transformer.C58aaa2a9480d5(1)_func{"oml-python:serialized_object": "function", "value": "fastsklearnfeature.candidates.Identity.identity"}
sklearn.preprocessing._function_transformer.C58aaa2a9480d5(1)_inv_kw_argsnull
sklearn.preprocessing._function_transformer.C58aaa2a9480d5(1)_inverse_funcnull
sklearn.preprocessing._function_transformer.C58aaa2a9480d5(1)_kw_argsnull
sklearn.preprocessing._function_transformer.C58aaa2a9480d5(1)_pass_y"deprecated"
sklearn.preprocessing._function_transformer.C58aaa2a9480d5(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.

17 Evaluation measures

Area under ROC curve
0.4881 ± 0.0127
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.598 ± 0.0043
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
-0.0148 ± 0.0287
Cross-validation details (10-fold Crossvalidation)
KB relative information score
-0.3955 ± 0.0188
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.5 ± 0
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.4091 ± 0.0032
Cross-validation details (10-fold Crossvalidation)
Number of instances
583
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.5726 ± 0.0095
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.693 ± 0.046
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.8641 ± 0.01
Cross-validation details (10-fold Crossvalidation)
Recall
0.693 ± 0.046
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
1.2222 ± 0.0097
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4521 ± 0.0036
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.5 ± 0
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
1.106 ± 0.0088
Cross-validation details (10-fold Crossvalidation)