| Issue | #Downvotes for this reason | By |
|---|
| sklearn.linear_model.logistic.LogisticRegression(35) | 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(35)_C | 1.0 |
| sklearn.linear_model.logistic.LogisticRegression(35)_class_weight | null |
| sklearn.linear_model.logistic.LogisticRegression(35)_dual | false |
| sklearn.linear_model.logistic.LogisticRegression(35)_fit_intercept | true |
| sklearn.linear_model.logistic.LogisticRegression(35)_intercept_scaling | 1 |
| sklearn.linear_model.logistic.LogisticRegression(35)_max_iter | 100 |
| sklearn.linear_model.logistic.LogisticRegression(35)_multi_class | "ovr" |
| sklearn.linear_model.logistic.LogisticRegression(35)_n_jobs | 1 |
| sklearn.linear_model.logistic.LogisticRegression(35)_penalty | "l2" |
| sklearn.linear_model.logistic.LogisticRegression(35)_random_state | 13352 |
| sklearn.linear_model.logistic.LogisticRegression(35)_solver | "liblinear" |
| sklearn.linear_model.logistic.LogisticRegression(35)_tol | 0.0001 |
| sklearn.linear_model.logistic.LogisticRegression(35)_verbose | 0 |
| sklearn.linear_model.logistic.LogisticRegression(35)_warm_start | false |
0.8123 ± 0.0209 Per class Cross-validation details (10-fold Crossvalidation)
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0.74 ± 0.0158 Per class Cross-validation details (10-fold Crossvalidation)
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0.3559 ± 0.0415 Cross-validation details (10-fold Crossvalidation)
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0.2371 ± 0.0249 Cross-validation details (10-fold Crossvalidation)
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0.3123 ± 0.0085 Cross-validation details (10-fold Crossvalidation)
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0.4147 ± 0.0003 Cross-validation details (10-fold Crossvalidation)
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0.7498 ± 0.0136 Cross-validation details (10-fold Crossvalidation)
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5404 Per class Cross-validation details (10-fold Crossvalidation) |
0.737 ± 0.0163 Per class Cross-validation details (10-fold Crossvalidation)
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0.7498 ± 0.0136 Cross-validation details (10-fold Crossvalidation)
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0.8732 ± 0.001 Cross-validation details (10-fold Crossvalidation)
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0.753 ± 0.0206 Cross-validation details (10-fold Crossvalidation)
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0.4554 ± 0.0004 Cross-validation details (10-fold Crossvalidation)
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0.3974 ± 0.0098 Cross-validation details (10-fold Crossvalidation)
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0.8728 ± 0.0213 Cross-validation details (10-fold Crossvalidation)
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0.6667 ± 0.0215 Cross-validation details (10-fold Crossvalidation)
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