matrix.interaction: Creates a matrix with pairwise interactions.

In adelie: Group Lasso and Elastic Net Solver for Generalized Linear Models

Creates a matrix with pairwise interactions.

Description

Creates a matrix with pairwise interactions.

Usage

matrix.interaction(
  mat,
  intr_keys = NULL,
  intr_values,
  levels = NULL,
  n_threads = 1
)

Arguments

mat	The dense matrix, which can include factors with levels coded as non-negative integers.
intr_keys	List of feature indices. This is a list of all features with which interactions can be formed. Default is 1:p where p is the number of columns in mat.
intr_values	List of list of feature indices. For each of the m <= p indices listed in intr_keys, there is a list of indices indicating which columns are candidates for interaction with that feature. If a list is list(NULL), that means all other features are candidates for interactions. The default is a list of length m where each element is list(NULL); that is rep(list(NULL), m.
levels	Number of levels for each of the columns of mat, with 1 representing a quantitative feature. A factor with K levels should be represented by the numbers 0,1,...,K-1.
n_threads	Number of threads.

Value

Pairwise interaction matrix. Logic is used to avoid repetitions. For each factor variable, the column is one-hot-encoded to form a basis for that feature. The object is an S4 class with methods for efficient computation by adelie. Note that some of the arguments are transformed to C++ base 0 for internal use, and if the object is examined, it will reflect that.

Author(s)

Trevor Hastie and James Yang
Maintainer: Trevor Hastie [e-mail]

Examples

n <- 10
p <- 20
X_dense <- matrix(rnorm(n * p), n, p)
X_dense[,1] <- rbinom(n, 4, 0.5)
intr_keys <- c(1, 2)
intr_values <- list(NULL, c(1, 3))
levels <- c(c(5), rep(1, p-1))
out <- matrix.interaction(X_dense, intr_keys, intr_values, levels)

adelie documentation built on Sept. 11, 2024, 6:36 p.m.