bases 0.2.0
mgcv smooth interface via s() for more
flexible penalization- New
b_nn() for neural network basis expansion
- New
b_tpsob() for tensor product Sobolev space basis
expansion (Zhang and Simon 2023)
- New
b_gff() for graph Fourier features for regression
on spatial and graph-structured data. Requires RSpectra
package for efficient eigendecomposition, and either adj or
igraph for graph representation.
- New
b_conv() for random convolutional features for
regression on images
- More efficient
b_ker() option for many predictions
- Control automatic leaf pruning in
b_bart()
- New vignette on other packages that help produce basis expansions or
embeddings.
bases 0.1.2
- Basis expansions for Gaussian processes / kernel ridge regression,
random Fourier features, BART prior features, and n-way
interactions
- Lightweight ridge regression routine
- Gaussian, Laplace, Rational quadratic, Matérn, and periodic
kernels
- Support for
recipes package