<b>kernlab</b>- An<i>S4</i>Package for Kernel Methods in<i>R</i> 论文
2004Journal of Statistical Software引用 1832顶会
Gaussian Processes and Bayesian InferenceNeural Networks and ApplicationsTime Series Analysis and Forecasting
摘要
kernlab is an extensible package for kernel-based machine learning methods in R. It takes advantage of R's new S4 ob ject model and provides a framework for creating and using kernel-based algorithms. The package contains dot product primitives (kernels), implementations of support vector machines and the relevance vector machine, Gaussian processes, a ranking algorithm, kernel PCA, kernel CCA, and a spectral clustering algorithm. Moreover it provides a general purpose quadratic programming solver, and an incomplete Cholesky decomposition method.