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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.

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.