make_reduced_basis_map: Mass-based reduction of basis functions

In jeremyrcoyle/mangolassi: The Scalable Highly Adaptive Lasso

Mass-based reduction of basis functions

Description

A helper function that finds which basis functions to keep (and equivalently which to discard) based on the proportion of 1's (observations, i.e., "mass") included in a given basis function.

Usage

make_reduced_basis_map(x_basis, reduce_basis_crit)

Arguments

x_basis

A matrix of basis functions with all redundant basis functions already removed.

reduce_basis_crit

A scalar numeric value bounded in the open interval (0,1) indicating the minimum proportion of 1's in a basis function column needed for the basis function to be included in the procedure to fit the Lasso. Any basis functions with a lower proportion of 1's than the specified cutoff will be removed. This argument defaults to NULL, in which case all basis functions are used in the lasso-fitting stage of the HAL algorithm.

Value

A binary numeric vector indicating which columns of the matrix of basis functions to keep (given a one) and which to discard (given a zero).

jeremyrcoyle/mangolassi documentation built on Nov. 22, 2024, 10:14 a.m.