MFF 0.2.3

• Added an end-to-end vignette demonstrating the boot.train()–tune.mff()–predict()–evaluate() workflow and the separation of validation-based selection from final test evaluation.
• Added a testthat unit-test suite covering the public interface, all four membership-generation methods, input validation, prediction-matrix dimensions, and sequential/parallel bootstrap reproducibility.
• Reworked examples to use lightweight prediction matrices and disabled parallel execution explicitly in examples and the vignette.
• Limited XGBoost and LightGBM inside model.train() to one thread to avoid oversubscribing CRAN check machines.
• Added print(), summary(), and plot() methods for fitted and tuned MFF objects.
• Extended plot.mff() with validation-safe test score, observed-versus-predicted, and test-series visualizations. Test plots use the validation-selected function by default and never reselect a function using test performance.
• Made the computationally intensive model.train() example interactive-only so that CRAN example checks do not initialize several external learner libraries merely to demonstrate the convenience function.