FTRLProximal (version 0.3.0)

ftrlprox.default: FTRL Proximal for matrix class

Description

Online elastic net regression using the FTRL Proximal algorithm for training.

Usage

"ftrlprox"(x, y, lambda, alpha, a, b = 1, num_epochs = 1, save_loss = F, ...)

Arguments

x

the model matrix containing features

y

the response variable

lambda

regularization term

alpha

mixing parameter, alpha=0 corresponds to L2 regularization and alpha=1 to L1.

a

learning rate parameter.

b

learning rate parameter controlling decay, defaults to 1.

num_epochs

number of times we should traverse over the traiing set, defaults to 1.

save_loss

is to save the loss function during training.

...

additional args

Value

ftrlprox model object

Details

This method is intended for matrix input.