logicFS (version 1.42.0)

vim.chisq: ChiSquare Based Importance

Description

Determining the importance of interactions found by logic.bagging or logicFS by Pearson's ChiSquare Statistic. Only available for the classification and the logistic regression approach of logic regression.

Usage

vim.chisq(object, data = NULL, cl = NULL)

Arguments

object
either an object of class logicFS or the output of an application of logic.bagging with importance = TRUE.
data
a data frame or matrix consisting of 0's and 1's in which each column corresponds to one of the explanatory variables used in the original analysis with logic.bagging or logicFS, and each row corresponds to an observation. Must be specified if object is an object of class logicFS, or cl is specified. If object is an object of class logicBagg and neither data nor cl is specified, data and cl stored in object is used to compute the ChiSquare statistics. It is, however, highly recommended to use new data to test the interactions contained in object, as they have been found using the data stored in object, and it is very likely that most of them will show up as interesting if they are tested on the same data set.
cl
a numeric vector of 0's and 1's specifying the class labels of the observations in data. Must be specified either if object is an object of class logicFS, or if data is specified.

Value

An object of class logicFS containing
primes
the prime implicants
vim
the values of Pearson's ChiSquare statistic,
prop
NULL,
type
NULL,
param
further parameters (if object is the output of logicFS or vim.logicFS with addInfo = TRUE),
mat.imp
NULL,
measure
"ChiSquare Based",
threshold
the 1 - 0.05/m quantile of the ChiSquare distribution with one degree of freedom,
mu
NULL.

Details

Currently Pearson's ChiSquare statistic is computed without continuity correction. Contrary to vim.logicFS (and vim.norm and vim.signperm), vim.chisq does neither take the logic regression models into acount nor uses the out-of-bag observations for computing the importances of the identified interactions. It "just" tests each of the found interactions on the whole data set by calculating Pearson's ChiSquare statistic for each of these interactions. It is, therefore, highly recommended to use an independent data set for specifying the importances of these interactions with vim.chisq.

See Also

logic.bagging, logicFS, vim.logicFS, vim.norm, vim.ebam