ssr3d_predict: 3-dimensional SSR model prediction

In sisireg: Sign-Simplicity-Regression-Solver

3-dimensional SSR model prediction

Description

Calculates the prediction for a given 3-dimensional SSR model.

Usage

ssr3d_predict(df_model, xy, ms = FALSE)

Arguments

df_model	data frame with model coordinates.
xy	data frame with coordinates for prediction.
ms	optional: boolean value to use the minimal surface algorithm.

Value

z	array with predictions.

Author(s)

Dr. Lars Metzner

References

Dr. Lars Metzner (2021) Adäquates Maschinelles Lernen. Independently Published.

Examples

# generate data
set.seed(1234)
x <- rnorm(900)
y <- rnorm(900)
xy <- data.frame(x=x, y=y)
z <- rnorm(900) + atan2(x, y)
# Training
df_model <- ssr3d(xy, z)
# Prediction
xx <- c(c(0,1), c(-1,1), c(1,-1))
xx <- matrix(xx, ncol = 2)
yy <- ssr3d_predict(df_model, xx)

sisireg documentation built on Aug. 8, 2025, 7:03 p.m.