| Supervised learning: Classification | To assess how much this discrimination depends on the classification approach utilized rather than the underlying information content in the data, we employed three different representative classification techniques: penalized logistic regression (a regularized generalized linear model based on Lasso), regularized random forest (a tree-based model), and support vector machine (a kernel-based model). |
| Supervised learning: Classification | Fig 3 summarizes the classification results for ADCP by penalized logistic regression . |
| Supervised learning: Classification | Penalized logistic regression readily enables assessment of the relative importance of different features for classification. |
| Supervised learning: Regression | As with penalized logistic regression , the regularization employed by Lars in training seeks to force coefficients to zero and yield a sparse model. |
| readily interpretable. | Classification of ADCC from antibody features by penalized logistic regression . |
| readily interpretable. | Classification of cytokine release from antibody features by penalized logistic regression . |