Run
10228302

Run 10228302

Task 3876 (Supervised Classification) analcatdata_challenger Uploaded 01-06-2019 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.C3766b73890f638(n32=sklearn.pipeline.C3766b73890f1b2(n33=s klearn.pipeline.C3766b73890e5f8(n34=sklearn.compose._column_transformer.C37 66b73890dff4(n35=sklearn.preprocessing._function_transformer.C3766b73890ddb 3),n36=fastsklearnfeature.transformations.OneHotTransformation.C3766b73890e 2e3),n37=sklearn.pipeline.C3766b73890eea4(n38=sklearn.compose._column_trans former.C3766b73890ed2d(n39=sklearn.preprocessing._function_transformer.C376 6b73890ec1b))),n40=fastsklearnfeature.transformations.HigherOrderCommutativ eTransformation.C3766b73890f518,c=sklearn.linear_model.logistic.LogisticReg ression)(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_state44724
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.C3766b73890f638(n32=sklearn.pipeline.C3766b73890f1b2(n33=sklearn.pipeline.C3766b73890e5f8(n34=sklearn.compose._column_transformer.C3766b73890dff4(n35=sklearn.preprocessing._function_transformer.C3766b73890ddb3),n36=fastsklearnfeature.transformations.OneHotTransformation.C3766b73890e2e3),n37=sklearn.pipeline.C3766b73890eea4(n38=sklearn.compose._column_transformer.C3766b73890ed2d(n39=sklearn.preprocessing._function_transformer.C3766b73890ec1b))),n40=fastsklearnfeature.transformations.HigherOrderCommutativeTransformation.C3766b73890f518,c=sklearn.linear_model.logistic.LogisticRegression)(1)_memorynull
sklearn.pipeline.C3766b73890f638(n32=sklearn.pipeline.C3766b73890f1b2(n33=sklearn.pipeline.C3766b73890e5f8(n34=sklearn.compose._column_transformer.C3766b73890dff4(n35=sklearn.preprocessing._function_transformer.C3766b73890ddb3),n36=fastsklearnfeature.transformations.OneHotTransformation.C3766b73890e2e3),n37=sklearn.pipeline.C3766b73890eea4(n38=sklearn.compose._column_transformer.C3766b73890ed2d(n39=sklearn.preprocessing._function_transformer.C3766b73890ec1b))),n40=fastsklearnfeature.transformations.HigherOrderCommutativeTransformation.C3766b73890f518,c=sklearn.linear_model.logistic.LogisticRegression)(1)_steps[{"oml-python:serialized_object": "component_reference", "value": {"key": "n32", "step_name": "n32"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "n40", "step_name": "n40"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "c", "step_name": "c"}}]
sklearn.pipeline.C3766b73890f1b2(n33=sklearn.pipeline.C3766b73890e5f8(n34=sklearn.compose._column_transformer.C3766b73890dff4(n35=sklearn.preprocessing._function_transformer.C3766b73890ddb3),n36=fastsklearnfeature.transformations.OneHotTransformation.C3766b73890e2e3),n37=sklearn.pipeline.C3766b73890eea4(n38=sklearn.compose._column_transformer.C3766b73890ed2d(n39=sklearn.preprocessing._function_transformer.C3766b73890ec1b)))(1)_n_jobsnull
sklearn.pipeline.C3766b73890f1b2(n33=sklearn.pipeline.C3766b73890e5f8(n34=sklearn.compose._column_transformer.C3766b73890dff4(n35=sklearn.preprocessing._function_transformer.C3766b73890ddb3),n36=fastsklearnfeature.transformations.OneHotTransformation.C3766b73890e2e3),n37=sklearn.pipeline.C3766b73890eea4(n38=sklearn.compose._column_transformer.C3766b73890ed2d(n39=sklearn.preprocessing._function_transformer.C3766b73890ec1b)))(1)_transformer_list[{"oml-python:serialized_object": "component_reference", "value": {"key": "n33", "step_name": "n33"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "n37", "step_name": "n37"}}]
sklearn.pipeline.C3766b73890f1b2(n33=sklearn.pipeline.C3766b73890e5f8(n34=sklearn.compose._column_transformer.C3766b73890dff4(n35=sklearn.preprocessing._function_transformer.C3766b73890ddb3),n36=fastsklearnfeature.transformations.OneHotTransformation.C3766b73890e2e3),n37=sklearn.pipeline.C3766b73890eea4(n38=sklearn.compose._column_transformer.C3766b73890ed2d(n39=sklearn.preprocessing._function_transformer.C3766b73890ec1b)))(1)_transformer_weightsnull
sklearn.pipeline.C3766b73890e5f8(n34=sklearn.compose._column_transformer.C3766b73890dff4(n35=sklearn.preprocessing._function_transformer.C3766b73890ddb3),n36=fastsklearnfeature.transformations.OneHotTransformation.C3766b73890e2e3)(1)_memorynull
sklearn.pipeline.C3766b73890e5f8(n34=sklearn.compose._column_transformer.C3766b73890dff4(n35=sklearn.preprocessing._function_transformer.C3766b73890ddb3),n36=fastsklearnfeature.transformations.OneHotTransformation.C3766b73890e2e3)(1)_steps[{"oml-python:serialized_object": "component_reference", "value": {"key": "n34", "step_name": "n34"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "n36", "step_name": "n36"}}]
sklearn.compose._column_transformer.C3766b73890dff4(n35=sklearn.preprocessing._function_transformer.C3766b73890ddb3)(1)_n_jobsnull
sklearn.compose._column_transformer.C3766b73890dff4(n35=sklearn.preprocessing._function_transformer.C3766b73890ddb3)(1)_remainder"drop"
sklearn.compose._column_transformer.C3766b73890dff4(n35=sklearn.preprocessing._function_transformer.C3766b73890ddb3)(1)_sparse_threshold0.3
sklearn.compose._column_transformer.C3766b73890dff4(n35=sklearn.preprocessing._function_transformer.C3766b73890ddb3)(1)_transformer_weightsnull
sklearn.compose._column_transformer.C3766b73890dff4(n35=sklearn.preprocessing._function_transformer.C3766b73890ddb3)(1)_transformers[{"oml-python:serialized_object": "component_reference", "value": {"key": "n35", "step_name": "n35", "argument_1": [1]}}]
sklearn.preprocessing._function_transformer.C3766b73890ddb3(1)_accept_sparsefalse
sklearn.preprocessing._function_transformer.C3766b73890ddb3(1)_check_inversetrue
sklearn.preprocessing._function_transformer.C3766b73890ddb3(1)_func{"oml-python:serialized_object": "function", "value": "fastsklearnfeature.candidates.Identity.identity"}
sklearn.preprocessing._function_transformer.C3766b73890ddb3(1)_inv_kw_argsnull
sklearn.preprocessing._function_transformer.C3766b73890ddb3(1)_inverse_funcnull
sklearn.preprocessing._function_transformer.C3766b73890ddb3(1)_kw_argsnull
sklearn.preprocessing._function_transformer.C3766b73890ddb3(1)_pass_y"deprecated"
sklearn.preprocessing._function_transformer.C3766b73890ddb3(1)_validatefalse
fastsklearnfeature.transformations.OneHotTransformation.C3766b73890e2e3(1)_raw_feature0
fastsklearnfeature.transformations.OneHotTransformation.C3766b73890e2e3(1)_value0.0
fastsklearnfeature.transformations.OneHotTransformation.C3766b73890e2e3(1)_value_id0
sklearn.pipeline.C3766b73890eea4(n38=sklearn.compose._column_transformer.C3766b73890ed2d(n39=sklearn.preprocessing._function_transformer.C3766b73890ec1b))(1)_memorynull
sklearn.pipeline.C3766b73890eea4(n38=sklearn.compose._column_transformer.C3766b73890ed2d(n39=sklearn.preprocessing._function_transformer.C3766b73890ec1b))(1)_steps[{"oml-python:serialized_object": "component_reference", "value": {"key": "n38", "step_name": "n38"}}]
sklearn.compose._column_transformer.C3766b73890ed2d(n39=sklearn.preprocessing._function_transformer.C3766b73890ec1b)(1)_n_jobsnull
sklearn.compose._column_transformer.C3766b73890ed2d(n39=sklearn.preprocessing._function_transformer.C3766b73890ec1b)(1)_remainder"drop"
sklearn.compose._column_transformer.C3766b73890ed2d(n39=sklearn.preprocessing._function_transformer.C3766b73890ec1b)(1)_sparse_threshold0.3
sklearn.compose._column_transformer.C3766b73890ed2d(n39=sklearn.preprocessing._function_transformer.C3766b73890ec1b)(1)_transformer_weightsnull
sklearn.compose._column_transformer.C3766b73890ed2d(n39=sklearn.preprocessing._function_transformer.C3766b73890ec1b)(1)_transformers[{"oml-python:serialized_object": "component_reference", "value": {"key": "n39", "step_name": "n39", "argument_1": [1]}}]
sklearn.preprocessing._function_transformer.C3766b73890ec1b(1)_accept_sparsefalse
sklearn.preprocessing._function_transformer.C3766b73890ec1b(1)_check_inversetrue
sklearn.preprocessing._function_transformer.C3766b73890ec1b(1)_func{"oml-python:serialized_object": "function", "value": "fastsklearnfeature.candidates.Identity.identity"}
sklearn.preprocessing._function_transformer.C3766b73890ec1b(1)_inv_kw_argsnull
sklearn.preprocessing._function_transformer.C3766b73890ec1b(1)_inverse_funcnull
sklearn.preprocessing._function_transformer.C3766b73890ec1b(1)_kw_argsnull
sklearn.preprocessing._function_transformer.C3766b73890ec1b(1)_pass_y"deprecated"
sklearn.preprocessing._function_transformer.C3766b73890ec1b(1)_validatefalse
fastsklearnfeature.transformations.HigherOrderCommutativeTransformation.C3766b73890f518(1)_method{"oml-python:serialized_object": "function", "value": "numpy.nanprod"}
fastsklearnfeature.transformations.HigherOrderCommutativeTransformation.C3766b73890f518(1)_number_parent_features2
fastsklearnfeature.transformations.HigherOrderCommutativeTransformation.C3766b73890f518(1)_sympy_method0

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)
Kappa
± 0.3162
Cross-validation details (10-fold Crossvalidation)
KB relative information score
-907.4711 ± 3.5649
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.5
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)
Predictive accuracy
0.9348 ± 0.0228
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.3712
Cross-validation details (10-fold Crossvalidation)
Recall
0.9348 ± 0.0228
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
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
2.0244 ± 1.6021
Cross-validation details (10-fold Crossvalidation)