eval_poly: Polynomial evaluation

In nn2poly: Neural Network Weights Transformation into Polynomial Coefficients

Polynomial evaluation

Description

Evaluates one or several polynomials on the given data.

Usage

eval_poly(poly, newdata, monomials = FALSE)

Arguments

poly	List containing 2 items: labels and values. labels: List of integer vectors with same length (or number of cols) as values, where each integer vector denotes the combination of variables associated to the coefficient value stored at the same position in values. That is, the monomials in the polynomial. Note that the variables are numbered from 1 to p, with the intercept is represented by 0. values: Matrix (can also be a vector if single polynomial), where each column represents a polynomial, with same number of rows as the length of labels, containing at each row the value of the coefficient of the monomial given by the equivalent label in that same position. Example: If labels contains the integer vector c(1,1,3) at position 5, then the value stored in values at row 5 is the coefficient associated with the term x_1^2*x_3.
newdata	Input data as matrix, vector or dataframe. Number of columns (or elements in vector) should be the number of variables in the polynomial (dimension p). Response variable to be predicted should not be included.
monomials	Boolean determining if the returned item should contain the evaluations of all the monomials of the provided polynomials (monomials==TRUE), or if the final polynomial evaluation should be computed, i.e., adding up all the monomials (monomials==FALSE). Defaults to FALSE.

Details

Note that this function is unstable and subject to change. Therefore it is not exported but this documentations is left available so users can use it if needed to simulate data by using nn2poly:::eval_poly().

Value

If monomials==FALSE, returns a matrix containing the evaluation of the polynomials on the given data. The matrix has dimensions (n_sample, n_polynomials), meaning that each column corresponds to the result of evaluating all the data for a polynomial. If a single polynomial is provided, the output is a vector instead of a row matrix.

If monomials==TRUE, returns a 3D array containing the monomials of each polynomial evaluated on the given data. The array has dimensions (n_sample, n_monomial_terms, n_polynomials), where element [i,j,k] contains the evaluation on observation i on monomial j of polynomial k, where monomial j corresponds to the one on poly$labels[[j]].

See Also

eval_poly() is also used in predict.nn2poly().

nn2poly documentation built on July 18, 2026, 1:07 a.m.