Run
9204501

Run 9204501

Task 168343 (Supervised Classification) credit-g Uploaded 05-09-2018 by Guilherme Perticarari
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Flow

sklearn.pipeline.Pipeline(OneHotEncoder=sklearn.preprocessing.data.OneHotEn coder,LogisticRegression=sklearn.linear_model.logistic.LogisticRegression)( 1)Automatically created scikit-learn flow.
sklearn.preprocessing.data.OneHotEncoder(26)_categorical_features"all"
sklearn.preprocessing.data.OneHotEncoder(26)_dtype{"oml-python:serialized_object": "type", "value": "np.float64"}
sklearn.preprocessing.data.OneHotEncoder(26)_handle_unknown"ignore"
sklearn.preprocessing.data.OneHotEncoder(26)_n_values"auto"
sklearn.preprocessing.data.OneHotEncoder(26)_sparsefalse
sklearn.linear_model.logistic.LogisticRegression(16)_C1.0
sklearn.linear_model.logistic.LogisticRegression(16)_class_weightnull
sklearn.linear_model.logistic.LogisticRegression(16)_dualfalse
sklearn.linear_model.logistic.LogisticRegression(16)_fit_intercepttrue
sklearn.linear_model.logistic.LogisticRegression(16)_intercept_scaling1
sklearn.linear_model.logistic.LogisticRegression(16)_max_iter100
sklearn.linear_model.logistic.LogisticRegression(16)_multi_class"ovr"
sklearn.linear_model.logistic.LogisticRegression(16)_n_jobs1
sklearn.linear_model.logistic.LogisticRegression(16)_penalty"l2"
sklearn.linear_model.logistic.LogisticRegression(16)_random_state20359
sklearn.linear_model.logistic.LogisticRegression(16)_solver"liblinear"
sklearn.linear_model.logistic.LogisticRegression(16)_tol0.0001
sklearn.linear_model.logistic.LogisticRegression(16)_verbose0
sklearn.linear_model.logistic.LogisticRegression(16)_warm_startfalse
sklearn.pipeline.Pipeline(OneHotEncoder=sklearn.preprocessing.data.OneHotEncoder,LogisticRegression=sklearn.linear_model.logistic.LogisticRegression)(1)_memorynull

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
0.7585
Per class
Cross-validation details (33% Holdout set)
F measure
0.7323
Per class
Cross-validation details (33% Holdout set)
Kappa
0.3495
Cross-validation details (33% Holdout set)
KB relative information score
71.9228
Cross-validation details (33% Holdout set)
Mean absolute error
0.3194
Cross-validation details (33% Holdout set)
Mean prior absolute error
0.4202
Cross-validation details (33% Holdout set)
Number of instances
330
Per class
Cross-validation details (33% Holdout set)
Precision
0.729
Per class
Cross-validation details (33% Holdout set)
Predictive accuracy
0.7394
Cross-validation details (33% Holdout set)
Prior entropy
0.8818
Cross-validation details (33% Holdout set)
Recall
0.7394
Per class
Cross-validation details (33% Holdout set)
Relative absolute error
0.7601
Cross-validation details (33% Holdout set)
Root mean prior squared error
0.4583
Cross-validation details (33% Holdout set)
Root mean squared error
0.4209
Cross-validation details (33% Holdout set)
Root relative squared error
0.9185
Cross-validation details (33% Holdout set)