polynomial_regression: Multivariate Polynomial Regression

In UAHDataScienceSC: Learn Supervised Classification Methods Through Examples and Code

Multivariate Polynomial Regression

Description

Calculates and plots the polynomial regression of a given set of values. Being all of them independent values but one, which is the dependent value. It provides (if asked) information about the process and intermediate values used to calculate the line equation. The approximation depends entirely in the degree of the equations.

Usage

polynomial_regression(data, degree, learn = FALSE, waiting = TRUE)

Arguments

data	x*y data frame with already classified observations. Each column represents a parameter of the values (independent variable). The last column represents the classification value (dependent variable). Each row is a different observation.
degree	Degree of the equations approximation.
learn	Boolean value. If it is set to "TRUE" multiple clarifications and explanations are printed along the code
waiting	If TRUE while learn = TRUE. The code will stop in each "block" of code and wait for the user to press "enter" to continue.

Value

List containing a list for each independent variable, each one contains the equation coefficients.

Author(s)

Víctor Amador Padilla, [e-mail]

Examples

# example code
polynomial_regression(db1rl,4, TRUE, FALSE)
polynomial_regression(db1rl,6)

UAHDataScienceSC documentation built on April 3, 2025, 8:58 p.m.