pimp.mat.bin: Predictor Importance Matrix – Classification

In LogicForest: Logic Forest

Predictor Importance Matrix – Classification

Description

Internal function called by pimp.import to construct a binary/logical matrix representing which predictors (columns) are used in each interaction (rows) of a sample.

Usage

pimp.mat.bin(pimps.out, testdata)

Arguments

pimps.out	R object containing vec.primes, tmp.mat, vec.pimpvars, and list.pimps.
testdata	Data frame or matrix of out-of-bag (OOB) samples.

Details

Note: For regression models, see pimp.mat.nonbin which accommodates complements of logic trees.

Value

A list with the following components:

pimp.names

Vector of predictor names.

pimp.datamat

Logical matrix indicating which predictors (columns) are used in each interaction (rows).

Author(s)

Bethany J. Wolf [e-mail]

References

Wolf BJ, Hill EG, Slate EH. Logic Forest: an ensemble classifier for discovering logical combinations of binary markers. Bioinformatics. 2010;26(17):2183–2189. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1093/bioinformatics/btq354")}

See Also

pimp.import

LogicForest documentation built on Feb. 14, 2026, 1:08 a.m.