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 log2-transformed 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 |
useN |
logical specifying if the number of correctly classified out-of-bag observations should
be used in the computation of the importance measure. If |
onlyRemove |
should in the single tree case the multiple tree measure be used? If |
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 |
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 |
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 |
mat.imp |
the matrix containing the improvements if |
measure |
the name of the used importance measure, |
useN |
the value of |
threshold |
NULL, |
mu |
NULL. |
Holger Schwender, holger.schwender@udo.edu
Schwender, H., Ickstadt, K. (2007). Identification of SNP Interactions Using Logic Regression. Biostatistics, 9(1), 187-198.
logic.bagging
, logicFS
,
vim.norm
, vim.signperm