Issue | #Downvotes for this reason | By |
---|
sklearn.pipeline.Pipeline(standardscaler=sklearn.preprocessing.data.Standar dScaler,svc=sklearn.svm.classes.SVC)(8) | 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 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 to None. |
sklearn.preprocessing.data.StandardScaler(43)_copy | true |
sklearn.preprocessing.data.StandardScaler(43)_with_mean | true |
sklearn.preprocessing.data.StandardScaler(43)_with_std | true |
sklearn.pipeline.Pipeline(standardscaler=sklearn.preprocessing.data.StandardScaler,svc=sklearn.svm.classes.SVC)(8)_steps | [{"oml-python:serialized_object": "component_reference", "value": {"key": "standardscaler", "step_name": "standardscaler"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "svc", "step_name": "svc"}}] |
sklearn.svm.classes.SVC(46)_C | 1.0 |
sklearn.svm.classes.SVC(46)_cache_size | 200 |
sklearn.svm.classes.SVC(46)_class_weight | null |
sklearn.svm.classes.SVC(46)_coef0 | 0.0 |
sklearn.svm.classes.SVC(46)_decision_function_shape | null |
sklearn.svm.classes.SVC(46)_degree | 3 |
sklearn.svm.classes.SVC(46)_gamma | "auto" |
sklearn.svm.classes.SVC(46)_kernel | "rbf" |
sklearn.svm.classes.SVC(46)_max_iter | -1 |
sklearn.svm.classes.SVC(46)_probability | true |
sklearn.svm.classes.SVC(46)_random_state | 9457 |
sklearn.svm.classes.SVC(46)_shrinking | true |
sklearn.svm.classes.SVC(46)_tol | 0.001 |
sklearn.svm.classes.SVC(46)_verbose | false |
0.7286 ± 0.0362 Per class Cross-validation details (10-fold Crossvalidation)
|
0.533 ± 0.0326 Per class Cross-validation details (10-fold Crossvalidation)
|
0.2761 ± 0.0475 Cross-validation details (10-fold Crossvalidation)
|
0.1985 ± 0.026 Cross-validation details (10-fold Crossvalidation)
|
0.3754 ± 0.0088 Cross-validation details (10-fold Crossvalidation)
|
0.4308 ± 0.0003 Cross-validation details (10-fold Crossvalidation)
|
0.5451 ± 0.0299 Cross-validation details (10-fold Crossvalidation)
|
1473 Per class Cross-validation details (10-fold Crossvalidation) |
0.536 ± 0.0388 Per class Cross-validation details (10-fold Crossvalidation)
|
0.5451 ± 0.0299 Cross-validation details (10-fold Crossvalidation)
|
1.539 ± 0.0019 Cross-validation details (10-fold Crossvalidation)
|
0.8713 ± 0.0203 Cross-validation details (10-fold Crossvalidation)
|
0.4641 ± 0.0003 Cross-validation details (10-fold Crossvalidation)
|
0.4305 ± 0.011 Cross-validation details (10-fold Crossvalidation)
|
0.9276 ± 0.0236 Cross-validation details (10-fold Crossvalidation)
|
0.5044 ± 0.0346 Cross-validation details (10-fold Crossvalidation)
|