Run
8858253

Run 8858253

Task 146818 (Supervised Classification) Australian Uploaded 21-02-2018 by Jan van Rijn
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Flow

sklearn.pipeline.Pipeline(imputation=openmlstudy14.preprocessing.Conditiona lImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,variencethres hold=sklearn.feature_selection.variance_threshold.VarianceThreshold,classif ier=sklearn.linear_model.logistic.LogisticRegression)(1)Automatically created scikit-learn flow.
openmlstudy14.preprocessing.ConditionalImputer(6)_axis0
openmlstudy14.preprocessing.ConditionalImputer(6)_categorical_features[0, 3, 4, 5, 7, 8, 10, 11]
openmlstudy14.preprocessing.ConditionalImputer(6)_copytrue
openmlstudy14.preprocessing.ConditionalImputer(6)_fill_empty0
openmlstudy14.preprocessing.ConditionalImputer(6)_missing_values"NaN"
openmlstudy14.preprocessing.ConditionalImputer(6)_strategy"median"
openmlstudy14.preprocessing.ConditionalImputer(6)_strategy_nominal"most_frequent"
openmlstudy14.preprocessing.ConditionalImputer(6)_verbose0
sklearn.preprocessing.data.OneHotEncoder(18)_categorical_features[0, 3, 4, 5, 7, 8, 10, 11]
sklearn.preprocessing.data.OneHotEncoder(18)_dtype{"oml-python:serialized_object": "type", "value": "np.float64"}
sklearn.preprocessing.data.OneHotEncoder(18)_handle_unknown"ignore"
sklearn.preprocessing.data.OneHotEncoder(18)_n_values"auto"
sklearn.preprocessing.data.OneHotEncoder(18)_sparsetrue
sklearn.feature_selection.variance_threshold.VarianceThreshold(12)_threshold0.0
sklearn.linear_model.logistic.LogisticRegression(12)_C1.0
sklearn.linear_model.logistic.LogisticRegression(12)_class_weightnull
sklearn.linear_model.logistic.LogisticRegression(12)_dualfalse
sklearn.linear_model.logistic.LogisticRegression(12)_fit_intercepttrue
sklearn.linear_model.logistic.LogisticRegression(12)_intercept_scaling1
sklearn.linear_model.logistic.LogisticRegression(12)_max_iter100
sklearn.linear_model.logistic.LogisticRegression(12)_multi_class"ovr"
sklearn.linear_model.logistic.LogisticRegression(12)_n_jobs1
sklearn.linear_model.logistic.LogisticRegression(12)_penalty"l2"
sklearn.linear_model.logistic.LogisticRegression(12)_random_state1
sklearn.linear_model.logistic.LogisticRegression(12)_solver"liblinear"
sklearn.linear_model.logistic.LogisticRegression(12)_tol0.0001
sklearn.linear_model.logistic.LogisticRegression(12)_verbose0
sklearn.linear_model.logistic.LogisticRegression(12)_warm_startfalse

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
0.9281 ± 0.0232
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.8611 ± 0.0374
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.7192 ± 0.0745
Cross-validation details (10-fold Crossvalidation)
KB relative information score
430.3116 ± 2.2074
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.1969 ± 0.014
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.494 ± 0.0008
Cross-validation details (10-fold Crossvalidation)
Number of instances
690
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.8616 ± 0.0357
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.8609 ± 0.0375
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.9913
Cross-validation details (10-fold Crossvalidation)
Recall
0.8609 ± 0.0375
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.3986 ± 0.0283
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.497 ± 0.0008
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.3173 ± 0.0251
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.6385 ± 0.0504
Cross-validation details (10-fold Crossvalidation)