Run
10417332

Run 10417332

Task 23 (Supervised Classification) cmc Uploaded 05-11-2019 by Heinrich Peters
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Flow

sklearn.pipeline.Pipeline(svc=sklearn.svm.classes.SVC)(4)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.pipeline.Pipeline(svc=sklearn.svm.classes.SVC)(4)_memorynull
sklearn.pipeline.Pipeline(svc=sklearn.svm.classes.SVC)(4)_steps[{"oml-python:serialized_object": "component_reference", "value": {"key": "svc", "step_name": "svc"}}]
sklearn.pipeline.Pipeline(svc=sklearn.svm.classes.SVC)(4)_verbosefalse
sklearn.svm.classes.SVC(37)_C1.0
sklearn.svm.classes.SVC(37)_cache_size200
sklearn.svm.classes.SVC(37)_class_weightnull
sklearn.svm.classes.SVC(37)_coef00.0
sklearn.svm.classes.SVC(37)_decision_function_shape"ovr"
sklearn.svm.classes.SVC(37)_degree3
sklearn.svm.classes.SVC(37)_gamma"scale"
sklearn.svm.classes.SVC(37)_kernel"rbf"
sklearn.svm.classes.SVC(37)_max_iter-1
sklearn.svm.classes.SVC(37)_probabilitytrue
sklearn.svm.classes.SVC(37)_random_state3
sklearn.svm.classes.SVC(37)_shrinkingtrue
sklearn.svm.classes.SVC(37)_tol0.001
sklearn.svm.classes.SVC(37)_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.

17 Evaluation measures

0.718 ± 0.0318
Per class
Cross-validation details (10-fold Crossvalidation)
0.5414 ± 0.0371
Per class
Cross-validation details (10-fold Crossvalidation)
0.291 ± 0.0578
Cross-validation details (10-fold Crossvalidation)
0.1877 ± 0.0206
Cross-validation details (10-fold Crossvalidation)
0.3798 ± 0.0081
Cross-validation details (10-fold Crossvalidation)
0.4308 ± 0.0003
Cross-validation details (10-fold Crossvalidation)
1473
Per class
Cross-validation details (10-fold Crossvalidation)
0.5449 ± 0.0419
Per class
Cross-validation details (10-fold Crossvalidation)
0.5519 ± 0.0377
Cross-validation details (10-fold Crossvalidation)
1.539 ± 0.0019
Cross-validation details (10-fold Crossvalidation)
0.5519 ± 0.0377
Per class
Cross-validation details (10-fold Crossvalidation)
0.8815 ± 0.0189
Cross-validation details (10-fold Crossvalidation)
0.4641 ± 0.0003
Cross-validation details (10-fold Crossvalidation)
0.4327 ± 0.0087
Cross-validation details (10-fold Crossvalidation)
0.9323 ± 0.0187
Cross-validation details (10-fold Crossvalidation)