initialize.ftrlprox: Initialize empty FTRL Proximal class
Description
Online elastic net regression using the FTRL Proximal algorithm for training.
Usage
initialize.ftrlprox(theta, levels, lambda, alpha, a, b = 1, save_loss = F, ...)
Arguments
theta
named numeric containing initial coefficients
levels
character vector containing class labels of target label
lambda
regularization term
alpha
mixing parameter, alpha=0 corresponds to L2 regularization and alpha=1 to L1.
b
learning rate parameter controlling decay, defaults to 1.
save_loss
is to save the loss function during training.
Value
ftrlprox model object
Details
This method is intended for setting up a ftrlprox model object before training it using update.