MFF 0.2.4
- Added
plot.mff(type = "weight_heatmap") for a labelled
heatmap of the complete candidate-model by meta-function weight
matrix.
- Added an optional distance-preserving PCA representation for
clustering candidate prediction profiles. This reduces the clustering
space to at most the number of candidate models minus one and makes GK
clustering practical when the validation set is much larger than the
candidate set.
- Strengthened validation of prediction matrices, response vectors,
clustering parameters, tuning grids, and parallel execution
arguments.
predict.mff() now verifies candidate-model identities
and column order before applying fitted weights.predict.mff(type = "best") now reports an informative
error when no validation-selected weight is available, instead of
implicitly returning all meta fuzzy functions.evaluate() now rejects mismatched, empty, malformed,
and non-finite inputs.
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.