Run
10397271

Run 10397271

Task 3 (Supervised Classification) kr-vs-kp Uploaded 02-09-2019 by Heinrich Peters
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Flow

sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer, onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder,svc=sklearn.svm .classes.SVC)(2)Automatically created scikit-learn flow.
sklearn.impute._base.SimpleImputer(3)_add_indicatorfalse
sklearn.impute._base.SimpleImputer(3)_copytrue
sklearn.impute._base.SimpleImputer(3)_fill_valuenull
sklearn.impute._base.SimpleImputer(3)_missing_valuesNaN
sklearn.impute._base.SimpleImputer(3)_strategy"most_frequent"
sklearn.impute._base.SimpleImputer(3)_verbose0
sklearn.svm.classes.SVC(32)_C1186.1858782558738
sklearn.svm.classes.SVC(32)_cache_size200
sklearn.svm.classes.SVC(32)_class_weightnull
sklearn.svm.classes.SVC(32)_coef00.7713422589105245
sklearn.svm.classes.SVC(32)_decision_function_shape"ovr"
sklearn.svm.classes.SVC(32)_degree4
sklearn.svm.classes.SVC(32)_gamma0.09011693632866666
sklearn.svm.classes.SVC(32)_kernel"rbf"
sklearn.svm.classes.SVC(32)_max_iter-1
sklearn.svm.classes.SVC(32)_probabilityfalse
sklearn.svm.classes.SVC(32)_random_state1
sklearn.svm.classes.SVC(32)_shrinkingtrue
sklearn.svm.classes.SVC(32)_tol0.001
sklearn.svm.classes.SVC(32)_verbosefalse
sklearn.preprocessing._encoders.OneHotEncoder(12)_categorical_featuresnull
sklearn.preprocessing._encoders.OneHotEncoder(12)_categoriesnull
sklearn.preprocessing._encoders.OneHotEncoder(12)_dropnull
sklearn.preprocessing._encoders.OneHotEncoder(12)_dtype{"oml-python:serialized_object": "type", "value": "np.float64"}
sklearn.preprocessing._encoders.OneHotEncoder(12)_handle_unknown"ignore"
sklearn.preprocessing._encoders.OneHotEncoder(12)_n_valuesnull
sklearn.preprocessing._encoders.OneHotEncoder(12)_sparsetrue
sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder,svc=sklearn.svm.classes.SVC)(2)_memorynull
sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder,svc=sklearn.svm.classes.SVC)(2)_steps[{"oml-python:serialized_object": "component_reference", "value": {"key": "simpleimputer", "step_name": "simpleimputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "onehotencoder", "step_name": "onehotencoder"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "svc", "step_name": "svc"}}]
sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder,svc=sklearn.svm.classes.SVC)(2)_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

Area under ROC curve
0.996 ± 0.0035
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.9959 ± 0.0036
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.9918 ± 0.0073
Cross-validation details (10-fold Crossvalidation)
KB relative information score
0.9918 ± 0.0073
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0041 ± 0.0036
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.499 ± 0
Cross-validation details (10-fold Crossvalidation)
Number of instances
3196
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.9959 ± 0.0035
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.9959 ± 0.0036
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.9986 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
Recall
0.9959 ± 0.0036
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.0082 ± 0.0073
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4995 ± 0
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.0638 ± 0.0341
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.1277 ± 0.0682
Cross-validation details (10-fold Crossvalidation)