| Issue | #Downvotes for this reason | By |
|---|
| -do-not-check-capabilities | If set, classifier capabilities are not checked before classifier is built (use with caution). | |
| B | Add Bias term with the given value if >= 0; if < 0, no bias term added (default: 1) | default: 1.0 |
| C | Set the cost parameter C (default: 1) | default: 1.0 |
| E | Set tolerance of termination criterion (default: 0.01) | default: 0.01 |
| M | Turn off missing value replacement. WARNING: use only if your data has no missing values. | |
| N | Turn on nominal to binary conversion. | |
| P | Use probability estimation (default: off) currently for L2-regularized logistic regression, L1-regularized logistic regression or L2-regularized logistic regression (dual)! | |
| S | Set type of solver (default: 1) for multi-class classification 0 -- L2-regularized logistic regression (primal) 1 -- L2-regularized L2-loss support vector classification (dual) 2 -- L2-regularized L2-loss support vector classification (primal) 3 -- L2-regularized L1-loss support vector classification (dual) 4 -- support vector classification by Crammer and Singer 5 -- L1-regularized L2-loss support vector classification 6 -- L1-regularized logistic regression 7 -- L2-regularized logistic regression (dual) for regression 11 -- L2-regularized L2-loss support vector regression (primal) 12 -- L2-regularized L2-loss support vector regression (dual) 13 -- L2-regularized L1-loss support vector regression (dual) | default: 1 |
| W | Set the parameters C of class i to weight[i]*C (default: 1) | |
| Z | Turn on normalization of input data (default: off) | |
| output-debug-info | If set, classifier is run in debug mode and may output additional info to the console |