nlareg: 'rtemis' internal: NonLinear Activation regression (NLAreg)

In egenn/rtemis: Machine Learning and Visualization

rtemis internal: NonLinear Activation regression (NLAreg)

Description

rtemis internal: NonLinear Activation regression (NLAreg)

Usage

nlareg(
  x,
  y,
  b_o = mean(y),
  W_o = 1,
  b_h = 0,
  W_h = 0,
  activation = softplus,
  optim.method = "BFGS",
  control = list(),
  ...
)

Arguments

x	Numeric vector or matrix / data frame of features i.e. independent variables
y	Numeric vector of outcome, i.e. dependent variable
b_o	Float, vector (length y): Output bias. Defaults to mean(y)
W_o	Float: Output weight. Defaults to 1
b_h	Float: Hidden layer bias. Defaults to 0
W_h	Float, vector (length NCOL(x)): Hidden layer weights. Defaults to 0
activation	String or Function: Activation function to use: provide its name or the function itself. Default = linksoftplus
optim.method	Character: Optimization method to use: "Nelder-Mead", "BFGS", "CG", "L-BFGS-B", "SANN", "Brent". See stats::optim for more details. Default = "BFGS"
control	List: Control parameters passed to stats::optim
...	Additional arguments

Value

nlareg object

Author(s)

E.D. Gennatas

egenn/rtemis documentation built on March 28, 2024, 12:53 p.m.