Run
10459584

Run 10459584

Task 3711 (Supervised Classification) elevators Uploaded 20-05-2020 by Marc Zöller
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  • automl_meta_features openml-python Sklearn_0.22.1.
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Flow

sklearn.pipeline.Pipeline(step_0=sklearn.decomposition._truncated_svd.Trunc atedSVD,step_1=sklearn.svm._classes.SVC)(1)Pipeline of transforms with a final estimator. Sequentially apply a list of transforms and a final estimator. Intermediate steps of the pipeline must be 'transforms', that is, they must implement fit and transform methods. The final estimator only needs to implement fit. The transformers in the pipeline can be cached using ``memory`` argument. The purpose of the pipeline is to assemble several steps that can be cross-validated together while setting different parameters. For this, it enables setting parameters of the various steps using their names and the parameter name separated by a '__', as in the example below. A step's estimator may be replaced entirely by setting the parameter with its name to another estimator, or a transformer removed by setting it to 'passthrough' or ``None``.
sklearn.svm._classes.SVC(4)_C242.8093747585185
sklearn.svm._classes.SVC(4)_break_tiestrue
sklearn.svm._classes.SVC(4)_cache_size200
sklearn.svm._classes.SVC(4)_class_weightnull
sklearn.svm._classes.SVC(4)_coef0-8.06260207170828
sklearn.svm._classes.SVC(4)_decision_function_shape"ovr"
sklearn.svm._classes.SVC(4)_degree5
sklearn.svm._classes.SVC(4)_gamma3.892222847062705e-05
sklearn.svm._classes.SVC(4)_kernel"poly"
sklearn.svm._classes.SVC(4)_max_iter-1
sklearn.svm._classes.SVC(4)_probabilityfalse
sklearn.svm._classes.SVC(4)_random_state42
sklearn.svm._classes.SVC(4)_shrinkingfalse
sklearn.svm._classes.SVC(4)_tol3.3492710771559716e-05
sklearn.svm._classes.SVC(4)_verbosefalse
sklearn.decomposition._truncated_svd.TruncatedSVD(1)_algorithm"arpack"
sklearn.decomposition._truncated_svd.TruncatedSVD(1)_n_components3
sklearn.decomposition._truncated_svd.TruncatedSVD(1)_n_iter15
sklearn.decomposition._truncated_svd.TruncatedSVD(1)_random_state42
sklearn.decomposition._truncated_svd.TruncatedSVD(1)_tol3.1053692280658014
sklearn.pipeline.Pipeline(step_0=sklearn.decomposition._truncated_svd.TruncatedSVD,step_1=sklearn.svm._classes.SVC)(1)_memorynull
sklearn.pipeline.Pipeline(step_0=sklearn.decomposition._truncated_svd.TruncatedSVD,step_1=sklearn.svm._classes.SVC)(1)_steps[{"oml-python:serialized_object": "component_reference", "value": {"key": "step_0", "step_name": "step_0"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "step_1", "step_name": "step_1"}}]
sklearn.pipeline.Pipeline(step_0=sklearn.decomposition._truncated_svd.TruncatedSVD,step_1=sklearn.svm._classes.SVC)(1)_verbosefalse

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.

18 Evaluation measures

0.4947 ± 0.0122
Per class
Cross-validation details (10-fold Crossvalidation)
0.5684 ± 0.0107
Per class
Cross-validation details (10-fold Crossvalidation)
-0.0107 ± 0.0244
Cross-validation details (10-fold Crossvalidation)
-0.0778 ± 0.0276
Cross-validation details (10-fold Crossvalidation)
0.4317 ± 0.0111
Cross-validation details (10-fold Crossvalidation)
0.4271 ± 0
Cross-validation details (10-fold Crossvalidation)
0.5683 ± 0.0111
Cross-validation details (10-fold Crossvalidation)
16599
Per class
Cross-validation details (10-fold Crossvalidation)
0.5684 ± 0.0105
Per class
Cross-validation details (10-fold Crossvalidation)
0.5683 ± 0.0111
Cross-validation details (10-fold Crossvalidation)
0.8921 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
1.0107 ± 0.0259
Cross-validation details (10-fold Crossvalidation)
0.4621 ± 0
Cross-validation details (10-fold Crossvalidation)
0.657 ± 0.0084
Cross-validation details (10-fold Crossvalidation)
1.4218 ± 0.0182
Cross-validation details (10-fold Crossvalidation)
0.4947 ± 0.0122
Cross-validation details (10-fold Crossvalidation)