Usage
vim.input(object, useN = NULL, iter = NULL, prop = TRUE, standardize = NULL, mu = 0, addMatImp = FALSE, prob.case = 0.5, rand = NA)
Arguments
object
an object of class logicBagg, i.e.\ the output of logic.bagging
useN
logical specifying if the number of correctly classified out-of-bag observations should
be used in the computation of the importance measure. If FALSE, the proportion of
correctly classified oob observations is used instead. If NULL (default), then
the specification of useN in object is used.
iter
integer specifying the number of times the values of the considered variable
are permuted in the computation of its importance. If NULL (default), the values
of the variable are not permuted, but the variable is removed from the model.
prop
should the proportion of logic regression models containing the respective variable
also be computed?
standardize
should a standardized version of the importance measure for a set of variables
be returned? By default, standardize = TRUE is used in the classification and the (multinomial)
logistic regression case, and standarize is set to FALSE in the linear regression case. For details, see mu.
mu
a non-negative numeric value. Ignored if standardize = FALSE. Otherwise, a t-statistic
for testing the null hypothesis that the importance of the respective variable is equal to mu
is computed.
addMatImp
should the matrix containing the improvements due to each of the variables in each
of the logic regression models be added to the output?
prob.case
a numeric value between 0 and 1. If the logistic regression approach of logic
regression has been used in logic.bagging, then an observation will be classified as a case (or
more exactly, as 1), if the class probability of this observation is larger than prob.case.
Otherwise, prob.case is ignored.
rand
an integer for setting the random number generator in a reproducible case.