predict.elm

elm model fitted with <code><a rd-options="" href="/link/elm?package=elmNNRcpp&version=1.0.4" data-mini-rdoc="elmNNRcpp::elm">elm</a></code>.

object

newdata

only used with classification, can be either "class", "prob", "raw", 
which are class (vector), probability (matrix) or the output of the elm function (matrix).

type

Wrapper for <code><a rd-options="" href="/link/elm_predict?package=elmNNRcpp&version=1.0.4" data-mini-rdoc="elmNNRcpp::elm_predict">elm_predict</a></code>.

Training and predict functions for Single Hidden-layer Feedforward Neural Networks (SLFN) using the Extreme Learning Machine (ELM) algorithm. The ELM algorithm differs from the traditional gradient-based algorithms for very short training times (it doesn't need any iterative tuning, this makes learning time very fast) and there is no need to set any other parameters like learning rate, momentum, epochs, etc. This is a reimplementation of the 'elmNN' package using 'RcppArmadillo' after the 'elmNN' package was archived. For more information, see "Extreme learning machine: Theory and applications" by Guang-Bin Huang, Qin-Yu Zhu, Chee-Kheong Siew (2006), Elsevier B.V, <doi:10.1016/j.neucom.2005.12.126>.

Lampros Mouselimis

elmNNRcpp

The Extreme Learning Machine Algorithm

Alberto Gosso

Edwin de Jonge

predict.elm function

elm model fitted with <code><a rd-options='' href='elm'>elm</a></code>.

Wrapper for <code><a rd-options='' href='elm_predict'>elm_predict</a></code>.

predict.elm: Predict with elm

Description

Usage

Arguments

Value