kernelTDA
This R
-package provides an implementation of the most famous kernels
found in the framework of Topological Data Analysis (TDA), more
specifically:
- Persistence Scale Space Kernel
- Sliced Wasserstein Kernel
- Persistence Fisher Kernel
- Geodesic Wasserstein Kernel(s)
- Persistence Images
Here you can also find an R
interface to the C++ library
HERA, which contains
an efficient implementation of the L_p q-Wasserstein distance
between persistence diagrams.
Finally, this package contains a solver for kernelized Support Vector Machine problems with indefinite kernels, based on the algorithm proposed by Loosli et al.. The implementation is largely based on the C++ library LIBSVM, and on its R interface in the package e1071.
This package is now on CRAN, you can install it with:
install.packages("kernelTDA")