Run
18064

Run 18064

Task 119 (Supervised Classification) diabetes Uploaded 12-11-2019 by Continuous Integration
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  • openml-python Sklearn_0.22.dev0.
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Flow

TESTf605fd7759sklearn.linear_model._logistic.LogisticRegression(1)Logistic Regression (aka logit, MaxEnt) classifier. In the multiclass case, the training algorithm uses the one-vs-rest (OvR) scheme if the 'multi_class' option is set to 'ovr', and uses the cross-entropy loss if the 'multi_class' option is set to 'multinomial'. (Currently the 'multinomial' option is supported only by the 'lbfgs', 'sag', 'saga' and 'newton-cg' solvers.) This class implements regularized logistic regression using the 'liblinear' library, 'newton-cg', 'sag', 'saga' and 'lbfgs' solvers. **Note that regularization is applied by default**. It can handle both dense and sparse input. Use C-ordered arrays or CSR matrices containing 64-bit floats for optimal performance; any other input format will be converted (and copied). The 'newton-cg', 'sag', and 'lbfgs' solvers support only L2 regularization with primal formulation, or no regularization. The 'liblinear' solver supports both L1 and L2 regularization, with a dual formulation only for the L2 penalty. The Elastic-Net regularization is only su...
TESTf605fd7759sklearn.linear_model._logistic.LogisticRegression(1)_C1.0
TESTf605fd7759sklearn.linear_model._logistic.LogisticRegression(1)_class_weightnull
TESTf605fd7759sklearn.linear_model._logistic.LogisticRegression(1)_dualfalse
TESTf605fd7759sklearn.linear_model._logistic.LogisticRegression(1)_fit_intercepttrue
TESTf605fd7759sklearn.linear_model._logistic.LogisticRegression(1)_intercept_scaling1
TESTf605fd7759sklearn.linear_model._logistic.LogisticRegression(1)_l1_rationull
TESTf605fd7759sklearn.linear_model._logistic.LogisticRegression(1)_max_iter100
TESTf605fd7759sklearn.linear_model._logistic.LogisticRegression(1)_multi_class"auto"
` for more details">TESTf605fd7759sklearn.linear_model._logistic.LogisticRegression(1)_n_jobsnull
TESTf605fd7759sklearn.linear_model._logistic.LogisticRegression(1)_penalty"l2"
TESTf605fd7759sklearn.linear_model._logistic.LogisticRegression(1)_random_state62501
TESTf605fd7759sklearn.linear_model._logistic.LogisticRegression(1)_solver"lbfgs"
TESTf605fd7759sklearn.linear_model._logistic.LogisticRegression(1)_tol0.0001
TESTf605fd7759sklearn.linear_model._logistic.LogisticRegression(1)_verbose0
TESTf605fd7759sklearn.linear_model._logistic.LogisticRegression(1)_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.

18 Evaluation measures

0.8264
Per class
Cross-validation details (10% Holdout set)
0.7671
Per class
Cross-validation details (10% Holdout set)
0.4882
Cross-validation details (10% Holdout set)
0.3135
Cross-validation details (10% Holdout set)
0.3244
Cross-validation details (10% Holdout set)
0.4589
Cross-validation details (10% Holdout set)
0.7747
Cross-validation details (10% Holdout set)
253
Per class
Cross-validation details (10% Holdout set)
0.7714
Per class
Cross-validation details (10% Holdout set)
0.7747
Cross-validation details (10% Holdout set)
0.9463
Cross-validation details (10% Holdout set)
0.7068
Cross-validation details (10% Holdout set)
0.4813
Cross-validation details (10% Holdout set)
0.401
Cross-validation details (10% Holdout set)
0.8333
Cross-validation details (10% Holdout set)
0.7321
Cross-validation details (10% Holdout set)