Run
9204470

Run 9204470

Task 31 (Supervised Classification) credit-g Uploaded 23-08-2018 by Edilson Correa Jr.
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Flow

sklearn.pipeline.Pipeline(onehotencoder=sklearn.preprocessing.data.OneHotEn coder,standardscaler=sklearn.preprocessing.data.StandardScaler,functiontran sformer=sklearn.preprocessing._function_transformer.FunctionTransformer,fea tureagglomeration=sklearn.cluster.hierarchical.FeatureAgglomeration,sgdclas sifier=sklearn.linear_model.stochastic_gradient.SGDClassifier)(1)Automatically created scikit-learn flow.
sklearn.preprocessing.data.OneHotEncoder(26)_categorical_features[true, false, true, true, false, true, true, false, true, true, false, true, false, true, true, false, true, false, true, true]
sklearn.preprocessing.data.OneHotEncoder(26)_dtype{"oml-python:serialized_object": "type", "value": "np.float64"}
sklearn.preprocessing.data.OneHotEncoder(26)_handle_unknown"error"
sklearn.preprocessing.data.OneHotEncoder(26)_n_values"auto"
sklearn.preprocessing.data.OneHotEncoder(26)_sparsetrue
sklearn.linear_model.stochastic_gradient.SGDClassifier(7)_alpha3.170846362638446e-06
sklearn.linear_model.stochastic_gradient.SGDClassifier(7)_averagetrue
sklearn.linear_model.stochastic_gradient.SGDClassifier(7)_class_weight"balanced"
sklearn.linear_model.stochastic_gradient.SGDClassifier(7)_epsilon0.1
sklearn.linear_model.stochastic_gradient.SGDClassifier(7)_eta00.09722688351233315
sklearn.linear_model.stochastic_gradient.SGDClassifier(7)_fit_intercepttrue
sklearn.linear_model.stochastic_gradient.SGDClassifier(7)_l1_ratio0.15
sklearn.linear_model.stochastic_gradient.SGDClassifier(7)_learning_rate"constant"
sklearn.linear_model.stochastic_gradient.SGDClassifier(7)_loss"squared_hinge"
sklearn.linear_model.stochastic_gradient.SGDClassifier(7)_max_iternull
sklearn.linear_model.stochastic_gradient.SGDClassifier(7)_n_iternull
sklearn.linear_model.stochastic_gradient.SGDClassifier(7)_n_jobs1
sklearn.linear_model.stochastic_gradient.SGDClassifier(7)_penalty"l2"
sklearn.linear_model.stochastic_gradient.SGDClassifier(7)_power_t0.5
sklearn.linear_model.stochastic_gradient.SGDClassifier(7)_random_state60152
sklearn.linear_model.stochastic_gradient.SGDClassifier(7)_shuffletrue
sklearn.linear_model.stochastic_gradient.SGDClassifier(7)_tol0.00953454743007943
sklearn.linear_model.stochastic_gradient.SGDClassifier(7)_verbose0
sklearn.linear_model.stochastic_gradient.SGDClassifier(7)_warm_startfalse
sklearn.cluster.hierarchical.FeatureAgglomeration(2)_affinity"euclidean"
sklearn.cluster.hierarchical.FeatureAgglomeration(2)_compute_full_tree"auto"
sklearn.cluster.hierarchical.FeatureAgglomeration(2)_connectivitynull
sklearn.cluster.hierarchical.FeatureAgglomeration(2)_linkage"average"
sklearn.cluster.hierarchical.FeatureAgglomeration(2)_memorynull
sklearn.cluster.hierarchical.FeatureAgglomeration(2)_n_clusters50
sklearn.cluster.hierarchical.FeatureAgglomeration(2)_pooling_func{"oml-python:serialized_object": "function", "value": "numpy.core.fromnumeric.mean"}
sklearn.preprocessing._function_transformer.FunctionTransformer(3)_accept_sparsetrue
sklearn.preprocessing._function_transformer.FunctionTransformer(3)_func{"oml-python:serialized_object": "function", "value": "__main__."}
sklearn.preprocessing._function_transformer.FunctionTransformer(3)_inv_kw_argsnull
sklearn.preprocessing._function_transformer.FunctionTransformer(3)_inverse_funcnull
sklearn.preprocessing._function_transformer.FunctionTransformer(3)_kw_argsnull
sklearn.preprocessing._function_transformer.FunctionTransformer(3)_pass_y"deprecated"
sklearn.preprocessing._function_transformer.FunctionTransformer(3)_validatetrue
sklearn.pipeline.Pipeline(onehotencoder=sklearn.preprocessing.data.OneHotEncoder,standardscaler=sklearn.preprocessing.data.StandardScaler,functiontransformer=sklearn.preprocessing._function_transformer.FunctionTransformer,featureagglomeration=sklearn.cluster.hierarchical.FeatureAgglomeration,sgdclassifier=sklearn.linear_model.stochastic_gradient.SGDClassifier)(1)_memorynull
sklearn.preprocessing.data.StandardScaler(13)_copytrue
sklearn.preprocessing.data.StandardScaler(13)_with_meanfalse
sklearn.preprocessing.data.StandardScaler(13)_with_stdtrue

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
0.7217 ± 0.046
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.7205 ± 0.0454
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.3902 ± 0.0861
Cross-validation details (10-fold Crossvalidation)
KB relative information score
256.768 ± 12.2368
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.291 ± 0.0479
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.4202
Cross-validation details (10-fold Crossvalidation)
Number of instances
1000
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.76 ± 0.0367
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.709 ± 0.0479
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.8818
Cross-validation details (10-fold Crossvalidation)
Recall
0.709 ± 0.0479
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.6926 ± 0.1141
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4583
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.5394 ± 0.0441
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
1.1772 ± 0.0963
Cross-validation details (10-fold Crossvalidation)