RWNN-package: RWNN: Random Weight Neural Networks

In svilsen/RWNN: Random Weight Neural Networks

RWNN: Random Weight Neural Networks

Description

Creation, estimation, and prediction of random weight neural networks (RWNN), Schmidt et al. (1992) \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1109/ICPR.1992.201708")}, including popular variants like extreme learning machines, Huang et al. (2006) \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1016/j.neucom.2005.12.126")}, sparse RWNN, Zhang et al. (2019) \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1016/j.neunet.2019.01.007")}, and deep RWNN, Henríquez et al. (2018) \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1109/IJCNN.2018.8489703")}. It further allows for the creation of ensemble RWNNs like bagging RWNN, Sui et al. (2021) \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1109/ECCE47101.2021.9595113")}, boosting RWNN, stacking RWNN, and ensemble deep RWNN, Shi et al. (2021) \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1016/j.patcog.2021.107978")}.

Author(s)

Maintainer: Søren B. Vilsen [e-mail]

Søren B. Vilsen <[e-mail]>

svilsen/RWNN documentation built on Feb. 23, 2025, 3:17 p.m.