Run
10228298

Run 10228298

Task 3876 (Supervised Classification) analcatdata_challenger Uploaded 01-06-2019 by Felix Neutatz
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  • ComplexityDriven openml-python Sklearn_0.20.3.
Issue #Downvotes for this reason By


Flow

sklearn.pipeline.C58a457af1b76a(n3=sklearn.compose._column_transformer.C58a 457af1b6b4(n4=sklearn.preprocessing._function_transformer.C3766b6cd712066), n5=fastsklearnfeature.transformations.OneDivisionTransformation.C3766b6cd71 27ef,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_state36135
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.C58a457af1b76a(n3=sklearn.compose._column_transformer.C58a457af1b6b4(n4=sklearn.preprocessing._function_transformer.C3766b6cd712066),n5=fastsklearnfeature.transformations.OneDivisionTransformation.C3766b6cd7127ef,c=sklearn.linear_model.logistic.LogisticRegression)(1)_memorynull
sklearn.pipeline.C58a457af1b76a(n3=sklearn.compose._column_transformer.C58a457af1b6b4(n4=sklearn.preprocessing._function_transformer.C3766b6cd712066),n5=fastsklearnfeature.transformations.OneDivisionTransformation.C3766b6cd7127ef,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.C58a457af1b6b4(n4=sklearn.preprocessing._function_transformer.C3766b6cd712066)(1)_n_jobsnull
sklearn.compose._column_transformer.C58a457af1b6b4(n4=sklearn.preprocessing._function_transformer.C3766b6cd712066)(1)_remainder"drop"
sklearn.compose._column_transformer.C58a457af1b6b4(n4=sklearn.preprocessing._function_transformer.C3766b6cd712066)(1)_sparse_threshold0.3
sklearn.compose._column_transformer.C58a457af1b6b4(n4=sklearn.preprocessing._function_transformer.C3766b6cd712066)(1)_transformer_weightsnull
sklearn.compose._column_transformer.C58a457af1b6b4(n4=sklearn.preprocessing._function_transformer.C3766b6cd712066)(1)_transformers[{"oml-python:serialized_object": "component_reference", "value": {"key": "n4", "step_name": "n4", "argument_1": [0]}}]
sklearn.preprocessing._function_transformer.C3766b6cd712066(1)_accept_sparsefalse
sklearn.preprocessing._function_transformer.C3766b6cd712066(1)_check_inversetrue
sklearn.preprocessing._function_transformer.C3766b6cd712066(1)_func{"oml-python:serialized_object": "function", "value": "fastsklearnfeature.candidates.Identity.identity"}
sklearn.preprocessing._function_transformer.C3766b6cd712066(1)_inv_kw_argsnull
sklearn.preprocessing._function_transformer.C3766b6cd712066(1)_inverse_funcnull
sklearn.preprocessing._function_transformer.C3766b6cd712066(1)_kw_argsnull
sklearn.preprocessing._function_transformer.C3766b6cd712066(1)_pass_y"deprecated"
sklearn.preprocessing._function_transformer.C3766b6cd712066(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
0.6421 ± 0.297
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.8516 ± 0.0685
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.1995 ± 0.3544
Cross-validation details (10-fold Crossvalidation)
KB relative information score
-907.4701 ± 3.5649
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.5 ± 0
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.1273 ± 0.0196
Cross-validation details (10-fold Crossvalidation)
Number of instances
138
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.9132 ± 0.057
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.8116 ± 0.0911
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.3712
Cross-validation details (10-fold Crossvalidation)
Recall
0.8116 ± 0.0911
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
3.9268 ± 1.027
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.247 ± 0.0592
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.5 ± 0
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
2.0244 ± 1.6021
Cross-validation details (10-fold Crossvalidation)