Learn R Programming

dcorVS (version 1.1)

Variable Selection Algorithms Using the Distance Correlation

Description

The 'FBED' and 'mmpc' variable selection algorithms have been implemented using the distance correlation. The references include: Tsamardinos I., Aliferis C. F. and Statnikov A. (2003). "Time and sample efficient discovery of Markovblankets and direct causal relations". In Proceedings of the ninth ACM SIGKDD international Conference. . Borboudakis G. and Tsamardinos I. (2019). "Forward-backward selection with early dropping". Journal of Machine Learning Research, 20(8): 1--39. . Huo X. and Szekely G.J. (2016). "Fast computing for distance covariance". Technometrics, 58(4): 435--447. .

Copy Link

Version

Install

install.packages('dcorVS')

Monthly Downloads

141

Version

1.1

License

GPL (>= 2)

Maintainer

Michail Tsagris

Last Published

December 10th, 2024

Functions in dcorVS (1.1)

dcorVS-package

Variable Selection Algorithms Using the Distance Correlation.
MMPC and the FBED variable selection algorithms using the distance correlation

MMPC and the FBED variable selection algorithms using the distance correlation
Backward selection algorithms using the distance correlation

Backward selection algorithms using the distance correlation