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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.

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.