preProcess

data


Pre processing function for the training and test data set. Each numeric variable is standardized between -1 and 1 and each categorical variable is coded with a dummy coding.


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.

Alessio Petrozziello

ELMR

Extreme Machine Learning (ELM)

preProcess function

Pre processing function for the training and test data set. Each numeric variable is standardized between -1 and 1 and each categorical variable is coded with a dummy coding.

preProcess: Pre processing function for the training and test data set. Each numeric variable is standardized between -1 and 1 and each categorical variable is coded with a dummy coding.

Description

Usage

Arguments

Value