| Issue | #Downvotes for this reason | By |
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| sklearn.linear_model.logistic.LogisticRegression(38) | 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' and 'newton-cg' solvers.) This class implements regularized logistic regression using the 'liblinear' library, 'newton-cg', 'sag' and 'lbfgs' solvers. 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. The 'liblinear' solver supports both L1 and L2 regularization, with a dual formulation only for the L2 penalty. |
| sklearn.linear_model.logistic.LogisticRegression(38)_C | 0.001 |
| sklearn.linear_model.logistic.LogisticRegression(38)_class_weight | "balanced" |
| sklearn.linear_model.logistic.LogisticRegression(38)_dual | false |
| sklearn.linear_model.logistic.LogisticRegression(38)_fit_intercept | true |
| sklearn.linear_model.logistic.LogisticRegression(38)_intercept_scaling | 1 |
| sklearn.linear_model.logistic.LogisticRegression(38)_max_iter | 10000 |
| sklearn.linear_model.logistic.LogisticRegression(38)_multi_class | "auto" |
| ` for more details.">sklearn.linear_model.logistic.LogisticRegression(38)_n_jobs | null |
| sklearn.linear_model.logistic.LogisticRegression(38)_penalty | "l2" |
| sklearn.linear_model.logistic.LogisticRegression(38)_random_state | 43861 |
| sklearn.linear_model.logistic.LogisticRegression(38)_solver | "lbfgs" |
| sklearn.linear_model.logistic.LogisticRegression(38)_tol | 0.0001 |
| sklearn.linear_model.logistic.LogisticRegression(38)_verbose | 0 |
| sklearn.linear_model.logistic.LogisticRegression(38)_warm_start | false |
0.7521 ± 0.0479 Per class Cross-validation details (10-fold Crossvalidation)
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0.6855 ± 0.0436 Per class Cross-validation details (10-fold Crossvalidation)
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0.2911 ± 0.0787 Cross-validation details (10-fold Crossvalidation)
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-0.3169 ± 0.0753 Cross-validation details (10-fold Crossvalidation)
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0.4124 ± 0.0201 Cross-validation details (10-fold Crossvalidation)
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0.363 ± 0.0023 Cross-validation details (10-fold Crossvalidation)
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0.6604 ± 0.0478 Cross-validation details (10-fold Crossvalidation)
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748 Per class Cross-validation details (10-fold Crossvalidation) |
0.7717 ± 0.0309 Per class Cross-validation details (10-fold Crossvalidation)
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0.6604 ± 0.0478 Cross-validation details (10-fold Crossvalidation)
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0.7916 ± 0.0072 Cross-validation details (10-fold Crossvalidation)
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1.136 ± 0.0557 Cross-validation details (10-fold Crossvalidation)
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0.4258 ± 0.0027 Cross-validation details (10-fold Crossvalidation)
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0.4524 ± 0.0197 Cross-validation details (10-fold Crossvalidation)
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1.0623 ± 0.0466 Cross-validation details (10-fold Crossvalidation)
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0.6922 ± 0.0458 Cross-validation details (10-fold Crossvalidation)
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