kmatrixGauss: Gaussian Kernel Computation for Kernel Local Fisher...
In road2stat/sdml: Supervised Distance Metric Learning with R

Description Usage Arguments Details Value Note Author(s) References See Also Examples

Gaussian kernel computation for klfda.

1	kmatrixGauss(x, sigma = 1)

`x`	n x d matrix of original samples. n is the number of samples.
`sigma`	dimensionality of reduced space. (default: 0.001)

Put kmatrixGauss function details here.

K n x n kernel matrix. n is the number of samples.

Put some note here.

Nan Xiao <https://nanx.me>

Sugiyama, M (2007). Dimensionality reduction of multimodal labeled data by local Fisher discriminant analysis. Journal of Machine Learning Research, vol.8, 1027–1061.

Sugiyama, M (2006). Local Fisher discriminant analysis for supervised dimensionality reduction. In W. W. Cohen and A. Moore (Eds.), Proceedings of 23rd International Conference on Machine Learning (ICML2006), 905–912.

See klfda for the computation of kernel local fisher discriminant analysis