ftrlprox.default: FTRL Proximal for matrix class

In while/FTRLProximal: FTRL Proximal Implementation for Elastic Net Regression

Description

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

Usage

## Default S3 method:
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

Details

This method is intended for matrix input.

Value

ftrlprox model object

Author(s)

Vilhelm von Ehrenheim

while/FTRLProximal documentation built on May 4, 2019, 5:23 a.m.