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NEWS.md file to track changes to the
package.What’s new: * Fully aligned with the new XGBoost R API: deprecated watchlist removed, predictions use the standard predict(model, xgb.DMatrix) method, eliminating future-breaking warnings. * Bayesian optimization redesigned to use a pure base-R surrogate approach, removing GPfit-related numerical failures while preserving the same function signature and outputs. * Robust failure handling across optimization and modeling: failed models are safely ignored, edge cases handled explicitly, and searches always return valid results. * Reduced dependency footprint, relying mainly on base R plus xgboost and imputeTS, simplifying installation and maintenance. * Cleaner, more stable modeling core (engine, sequencer, hood) with safer cross-validation, early stopping, residual sampling, and base svd() for dimensionality reduction. * Output and API backward compatibility preserved: existing code using audrex, random_search, or bayesian_search continues to work unchanged. * Comprehensive test coverage added via testthat, validating all major paths (gbtree, gblinear, random search, Bayesian search, full audrex pipeline).
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.