dgp_twoclass {stablelearner} | R Documentation |
Data-Ggnerating Function for Two-Class Problem
Description
Data-generating function to generate artificial data sets of a classification
problem with two response classes, denoted as "A"
and "B"
.
Usage
dgp_twoclass(n = 100, p = 4, noise = 16, rho = 0,
b0 = 0, b = rep(1, p), fx = identity)
Arguments
n |
integer. Number of observations. The default is 100. |
p |
integer. Number of signal predictors. The default is 4. |
noise |
integer. Number of noise predictors. The default is 16. |
rho |
numeric value between -1 and 1 specifying the correlation
between the signal predictors. The correlation is given by |
b0 |
numeric value. Baseline probability for class |
b |
numeric value. Slope parameter for the predictors on the logit scale. The default is 1 for all predictors. |
fx |
a function that is used to transform the predictors. The default
is |
Value
A data.frame
including a column denoted as class
that is
a factor with two levels "A"
and "B"
. All other columns
represent the predictor variables (signal predictors followed by noise
predictors) and are named by "x1"
, "x2"
, etc..
See Also
Examples
dgp_twoclass(n = 200, p = 6, noise = 4)