Creation, estimation, and prediction of random weight neural networks (RWNN), Schmidt et al. (1992) tools:::Rd_expr_doi("10.1109/ICPR.1992.201708"), including popular variants like extreme learning machines, Huang et al. (2006) tools:::Rd_expr_doi("10.1016/j.neucom.2005.12.126"), sparse RWNN, Zhang et al. (2019) tools:::Rd_expr_doi("10.1016/j.neunet.2019.01.007"), and deep RWNN, Henríquez et al. (2018) 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) tools:::Rd_expr_doi("10.1109/ECCE47101.2021.9595113"), boosting RWNN, stacking RWNN, and ensemble deep RWNN, Shi et al. (2021) tools:::Rd_expr_doi("10.1016/j.patcog.2021.107978").
Maintainer: Søren B. Vilsen svilsen@math.aau.dk
Søren B. Vilsen <svilsen@math.aau.dk>