vim.logicFS {logicFS}R Documentation

Importance Measures

Description

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.

Usage

vim.logicFS(log.out, prob.case = 0.5, addInfo = FALSE, addMatImp = TRUE)

Arguments

log.out an object of class logicBagg, i.e. the output of logic.bagging
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

Value

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
threshold NULL
mu NULL

Author(s)

Holger Schwender, holger.schwender@udo.edu

References

Schwender, H., Ickstadt, K. (2007). Identification of SNP Interactions Using Logic Regression. Biostatistics, doi:10.1093/biostatistics/kxm024.

See Also

logic.bagging, logicFS, vim.norm, vim.perm


[Package logicFS version 1.10.0 Index]