Man pages for xplus
Positive and Unlabeled Learning from Unbalanced Cases and Sparse Structures
| assess | Assess predictive performance |
| auc | Compute area under the ROC curve |
| auc_matrix | Compute AUC from matrix labels |
| binexample | Example binary labels dataset |
| coef.xplus | Extract coefficients from an xplus model |
| cutoff_example | Example cutoff values |
| fit_xplus_example | Example fitted xplus object |
| get_auc | Compute AUC for predictions from a model |
| get_predictions | Build a tidy prediction table |
| lacs | LACS dataset |
| lacsSample | LACS sample dataset |
| new_xplus | Construct a new xplus object |
| predicted_coefficients_example | Example predicted coefficients |
| predicted_y_example | Example predicted probabilities |
| predict.xplus | Predict from an xplus model |
| print.summary.xplus | Print method for summary.xplus objects |
| print.xplus | Print an xplus model |
| stratified_foldid | Build class-stratified cross-validation fold assignments |
| summary.xplus | Summarize an xplus model |
| validate_xplus | Validate an xplus object |
| xplus | Fit an xplus model |
| xplus_object_example | Example xplus object |
