RuleMats: Compute matrices that identify the rules

In pre: Prediction Rule Ensembles

Compute matrices that identify the rules

Description

This function computes the matrices that are needed to compute marginal Shapley values of a RuleSHAP model. These matrices check which points satisfy each of the subrules of each rule. They also check which predictors are involved in the definition of each rule.

Usage

RuleMats(rules, x_df)

Arguments

rules	a character vector containing the rules to compute the matrices for
x_df	a dataframe containing the observations to compute the matrices for

Value

RulePredMat A matrix with as many rows as there are rules and as many columns as there are predictors. The j-th column has ones on the entries corresponding to rules that involve the j-th predictor, while all remaining entries are zeroes. Can be computed with the RuleMats function.

Rs a list of as many matrices as there are rules. The j-th element is a matrix corresponding to the j-th rule. Each of its columns corresponds to the 0-1 encoding of a subrule of the j-th rule, as observed in the data provided with input parameter x.

Author(s)

Giorgio Spadaccini

pre documentation built on Sept. 1, 2026, 1:06 a.m.