rkaf 0.1.0

Initial development version

• Added core Kolmogorov-Arnold Fourier Network modules using torch:
  • nn_random_fourier_features()
  • nn_kaf_layer()
  • nn_kaf()
• Added high-level model creation with kaf().
• Added model fitting with kaf_fit().
• Added formula interface with kaf_fit_formula().
• Added support for:
  • regression
  • binary classification
  • multiclass classification
• Added prediction methods:
  • type = "response"
  • type = "prob"
  • type = "class"
  • type = "link"
• Added training utilities:
  • mini-batch training
  • validation splits
  • explicit validation data
  • early stopping
  • best-model restoration
  • predictor standardization
  • optional target standardization for regression
• Added diagnostics:
  • extract_kaf_scales()
  • extract_fourier_params()
  • plot_kaf_scales()
• Added README, pkgdown site, and getting started vignette.
• Added references and attribution to the original KAF paper and related Python implementations.