OSelm_train.formula

a symbolic description of the model to be fitted.

formula

training data frame containing the variables specified in formula.

data

select if the ELM must perform a "regression" or "classification"

Elm_type

nHiddenNeurons

"rbf" for radial basis function with Gaussian kernels , "sig" for sigmoidal fucntion, "sin" for sine function, "hardlim" for hard limit function

ActivationFunction

size of each chunk to be processed at each step

Block


Trains an extreme learning machine with random weights


Training and prediction functions are provided for the Extreme Learning Machine algorithm (ELM). The ELM use a Single Hidden Layer Feedforward Neural Network (SLFN) with random generated weights and no gradient-based backpropagation. The training time is very short and the online version allows to update the model using small chunk of the training set at each iteration. The only parameter to tune is the hidden layer size and the learning function.

OSelm_train.formula: Trains an extreme learning machine with random weights

Description

Usage

Arguments

Value