fastml version 0.7.5

Breaking changes

Removed incomplete or unstable survival backends where correct, leakage-safe behavior could not be guaranteed.

Full Survival Analysis Support: Added training, resampling, prediction, metric computation, and model summarization for time-to-event outcomes.
Guarded Survival Resampling: Introduced a workflow enforcing leakage-safe preprocessing, imputation, and model fitting within each resampling split.
Integrated Brier Score (IBS): Added IBS and expanded survival metric support with flexible time handling and user-configurable summary outputs.
New Survival Engines: Added support for parametric and semi-parametric models, including Cox, penalized Cox, Royston–Parmar, and flexible parametric survival models.
Advanced Resampling Strategies: Implemented grouped, blocked, rolling, stratified, and unbiased nested cross-validation.
Fold-wise Imputation: Added support for advanced imputation during resampling while preventing outcome leakage.
Engine Parameters: Introduced an engine_params argument to allow passing engine-specific options in a consistent way.
S3 Methods: Added explicit S3 method annotations for fastml generics.

Improved robustness of survival predictions, including risk scores, survival probabilities, quantiles, medians, and time estimates.
Enhanced survival summary outputs with clearer metric alignment and better handling of stratified and time-varying Cox models.
Improved extraction of predictions and summaries for parametric survival engines.
Strengthened recipe validation and sandboxing to harden preprocessing isolation and reduce user-induced leakage.
Improved handling of novel and missing categorical levels during prediction.
Integrated resampling metadata more tightly into training workflows and summaries.

Fixed multiple issues in survival label validation, prediction post-processing, and metric computation.
Corrected survival risk and probability calculations for several engines and model types.
Fixed log-rank calculation for time-varying Cox models.
Fixed summary formatting when confidence intervals are unavailable.
Removed inappropriate confusion matrix warnings for non-classification tasks.
Fixed edge cases leading to NA survival predictions and early exits during survival time computation.
Addressed naming collisions and alignment issues in tuning grids and metric selection.