rtemis (version 0.79)

expand.glmLiteBoostTV: Expand boosting series

Description

Expand a glmLiteBoostTV object by adding more iterations

Usage

expand.glmLiteBoostTV(object, x, y = NULL, x.valid = NULL,
  y.valid = NULL, x.test = NULL, y.test = NULL, resid = NULL,
  mod.params = NULL, max.iter = 10, learning.rate = NULL,
  weights.p = 1, weights.0 = 0, seed = NULL, prefix = NULL,
  verbose = TRUE, trace = 0, print.error.plot = "final",
  print.plot = FALSE)

Arguments

object

glmLiteBoostTV object

x

Numeric vector or matrix / data frame of features i.e. independent variables

y

Numeric vector of outcome, i.e. dependent variable

x.valid

Data.frame; optional: Validation data

y.valid

Float, vector; optional: Validation outcome

x.test

Numeric vector or matrix / data frame of testing set features Columns must correspond to columns in x

y.test

Numeric vector of testing set outcome

resid

Float, vector, length = length(y): Residuals to work on. Do not change unless you know what you're doing. Default = NULL, for regular boosting

mod.params

Named list of arguments for mod

max.iter

Integer: Maximum number of iterations (additive steps) to perform. Default = 10

learning.rate

Float (0, 1] Learning rate for the additive steps

prefix

Internal

verbose

Logical: If TRUE, print summary to screen.

trace

Integer: If > 0, print diagnostic info to console

print.error.plot

String or Integer: "final" plots a training and validation (if available) error curve at the end of training. If integer, plot training and validation error curve every this many iterations during training. "none" for no plot.

print.plot

Logical: if TRUE, produce plot using mplot3 Takes precedence over plot.fitted and plot.predicted