Run
10588209

Run 10588209

Task 18 (Supervised Classification) mfeat-morphological Uploaded 26-09-2022 by VAIBHAV JAISWAL
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Flow

sklearn.pipeline.Pipeline(numerical=sklearn.pipeline.Pipeline(Imputer=sklea rn.impute._base.SimpleImputer,scaler=sklearn.preprocessing._data.StandardSc aler),model=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.preprocessing._data.StandardScaler(11)_copytrue
sklearn.preprocessing._data.StandardScaler(11)_with_meantrue
sklearn.preprocessing._data.StandardScaler(11)_with_stdtrue
sklearn.impute._base.SimpleImputer(30)_add_indicatorfalse
sklearn.impute._base.SimpleImputer(30)_copytrue
sklearn.impute._base.SimpleImputer(30)_fill_valuenull
sklearn.impute._base.SimpleImputer(30)_missing_valuesNaN
sklearn.impute._base.SimpleImputer(30)_strategy"mean"
sklearn.impute._base.SimpleImputer(30)_verbose0
sklearn.pipeline.Pipeline(Imputer=sklearn.impute._base.SimpleImputer,scaler=sklearn.preprocessing._data.StandardScaler)(2)_memorynull
sklearn.pipeline.Pipeline(Imputer=sklearn.impute._base.SimpleImputer,scaler=sklearn.preprocessing._data.StandardScaler)(2)_steps[{"oml-python:serialized_object": "component_reference", "value": {"key": "Imputer", "step_name": "Imputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "scaler", "step_name": "scaler"}}]
sklearn.pipeline.Pipeline(Imputer=sklearn.impute._base.SimpleImputer,scaler=sklearn.preprocessing._data.StandardScaler)(2)_verbosefalse
sklearn.pipeline.Pipeline(numerical=sklearn.pipeline.Pipeline(Imputer=sklearn.impute._base.SimpleImputer,scaler=sklearn.preprocessing._data.StandardScaler),model=sklearn.svm._classes.SVC)(1)_memorynull
sklearn.pipeline.Pipeline(numerical=sklearn.pipeline.Pipeline(Imputer=sklearn.impute._base.SimpleImputer,scaler=sklearn.preprocessing._data.StandardScaler),model=sklearn.svm._classes.SVC)(1)_steps[{"oml-python:serialized_object": "component_reference", "value": {"key": "numerical", "step_name": "numerical"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "model", "step_name": "model"}}]
sklearn.pipeline.Pipeline(numerical=sklearn.pipeline.Pipeline(Imputer=sklearn.impute._base.SimpleImputer,scaler=sklearn.preprocessing._data.StandardScaler),model=sklearn.svm._classes.SVC)(1)_verbosefalse
sklearn.svm._classes.SVC(11)_C1.0
sklearn.svm._classes.SVC(11)_break_tiesfalse
sklearn.svm._classes.SVC(11)_cache_size200
sklearn.svm._classes.SVC(11)_class_weightnull
sklearn.svm._classes.SVC(11)_coef00.0
sklearn.svm._classes.SVC(11)_decision_function_shape"ovr"
sklearn.svm._classes.SVC(11)_degree3
sklearn.svm._classes.SVC(11)_gamma"scale"
sklearn.svm._classes.SVC(11)_kernel"rbf"
sklearn.svm._classes.SVC(11)_max_iter-1
sklearn.svm._classes.SVC(11)_probabilityfalse
sklearn.svm._classes.SVC(11)_random_state0
sklearn.svm._classes.SVC(11)_shrinkingtrue
sklearn.svm._classes.SVC(11)_tol0.001
sklearn.svm._classes.SVC(11)_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

0.5125 ± 0.0056
Per class
Cross-validation details (10-fold Crossvalidation)
0.1245 ± 0.0096
Per class
Cross-validation details (10-fold Crossvalidation)
0.025 ± 0.0112
Cross-validation details (10-fold Crossvalidation)
0.0823 ± 0.0105
Cross-validation details (10-fold Crossvalidation)
0.1755 ± 0.002
Cross-validation details (10-fold Crossvalidation)
0.18
Cross-validation details (10-fold Crossvalidation)
0.1225 ± 0.0101
Cross-validation details (10-fold Crossvalidation)
2000
Per class
Cross-validation details (10-fold Crossvalidation)
0.1268 ± 0.0096
Per class
Cross-validation details (10-fold Crossvalidation)
0.1225 ± 0.0101
Cross-validation details (10-fold Crossvalidation)
3.3219
Cross-validation details (10-fold Crossvalidation)
0.975 ± 0.0112
Cross-validation details (10-fold Crossvalidation)
0.3
Cross-validation details (10-fold Crossvalidation)
0.4189 ± 0.0024
Cross-validation details (10-fold Crossvalidation)
1.3964 ± 0.008
Cross-validation details (10-fold Crossvalidation)
0.1225 ± 0.0101
Cross-validation details (10-fold Crossvalidation)