Description Usage Arguments Details Value Author(s)
Online elastic net regression using the FTRL Proximal algorithm for training.
1 2 | initialize.ftrlprox(theta, levels, lambda, alpha, a, b = 1, save_loss = F,
...)
|
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. |
a |
learning rate parameter |
b |
learning rate parameter controlling decay, defaults to 1. |
save_loss |
is to save the loss function during training. |
... |
additional args |
This method is intended for setting up a ftrlprox model object before training it using update.
ftrlprox model object
Vilhelm von Ehrenheim
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