vim.logicFS {logicFS} | R Documentation |
Computes the value of the single or the multiple tree measure, respectively, for each prime implicant contained in a logic bagging model to specify the importance of the prime implicant for classification, if the response is binary. If the response is quantitative, the importance is specified by a measure based on the mean square prediction error.
vim.logicFS(log.out, useN = TRUE, onlyRemove = FALSE, prob.case = 0.5, addInfo = FALSE, addMatImp = TRUE)
log.out |
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. |
onlyRemove |
should in the single tree case the multiple tree measure be used? If TRUE ,
the prime implicants are only removed from the trees when determining the importance in the
single tree case. If FALSE , the original single tree measure is computed for each prime
implicant, i.e. a prime implicant is not only removed from the trees in which it is contained,
but also added to the trees that do not contain this interaction. Ignored in all other than the
classification case. |
prob.case |
a numeric value between 0 and 1. If the logistic regression approach
of logic regression is used (i.e. if the response is binary, and in logic.bagging
ntrees is set to a value larger than 1, or glm.if.1tree is
set to TRUE ), then an observation will be classified as a case (or
more exactly as 1), if the class probability of this observation estimated
by the logic bagging model is larger than prob.case . |
addInfo |
should further information on the logic regression models be added? |
addMatImp |
should the matrix containing the improvements due to the prime implicants
in each of the iterations be added to the output? (For each of the prime implicants,
the importance is computed by the average over the B improvements.) Must be
set to TRUE , if standardized importances should be computed using
vim.norm , or if permutation based importances should be computed
using vim.perm . |
An object of class logicFS
containing
primes |
the prime implicants, |
vim |
the importance of the prime implicants, |
prop |
the proportion of logic regression models containing the prime implicants, |
type |
the type of model (1: classification, 2: linear regression, 3: logistic regression), |
param |
further parameters (if addInfo = TRUE ), |
mat.imp |
the matrix containing the improvements if addMatImp = TRUE ,
otherwise, NULL , |
measure |
the name of the used importance measure, |
useN |
the value of useN , |
threshold |
NULL, |
mu |
NULL. |
Holger Schwender, holger.schwender@udo.edu
Schwender, H., Ickstadt, K. (2007). Identification of SNP Interactions Using Logic Regression. Biostatistics, doi:10.1093/biostatistics/kxm024.
logic.bagging
, logicFS
,
vim.norm
, vim.perm