Showing 4 of total 4 results (show query)
alexkz
kernlab:Kernel-Based Machine Learning Lab
Kernel-based machine learning methods for classification, regression, clustering, novelty detection, quantile regression and dimensionality reduction. Among other methods 'kernlab' includes Support Vector Machines, Spectral Clustering, Kernel PCA, Gaussian Processes and a QP solver.
Maintained by Alexandros Karatzoglou. Last updated 8 months ago.
21 stars 12.26 score 7.8k scripts 487 dependents
ly129
ktweedie:'Tweedie' Compound Poisson Model in the Reproducing Kernel Hilbert Space
Kernel-based 'Tweedie' compound Poisson gamma model using high-dimensional predictors for the analyses of zero-inflated response variables. The package features built-in estimation, prediction and cross-validation tools and supports choice of different kernel functions. For more details, please see Yi Lian, Archer Yi Yang, Boxiang Wang, Peng Shi & Robert William Platt (2023) <doi:10.1080/00401706.2022.2156615>.
Maintained by Yi Lian. Last updated 1 years ago.
2 stars 4.00 score 5 scripts
boxiang-wang
kerndwd:Distance Weighted Discrimination (DWD) and Kernel Methods
A novel implementation that solves the linear distance weighted discrimination and the kernel distance weighted discrimination. Reference: Wang and Zou (2018) <doi:10.1111/rssb.12244>.
Maintained by Boxiang Wang. Last updated 5 years ago.
1.04 score 11 scripts
cran
KERE:Expectile Regression in Reproducing Kernel Hilbert Space
An efficient algorithm inspired by majorization-minimization principle for solving the entire solution path of a flexible nonparametric expectile regression estimator constructed in a reproducing kernel Hilbert space.
Maintained by Yi Yang. Last updated 10 years ago.
1 stars 1.00 score