mlbench.friedman1: Benchmark Problem Friedman 1

In mlbench: Machine Learning Benchmark Problems

Benchmark Problem Friedman 1

Description

The regression problem Friedman 1 as described in Friedman (1991) and Breiman (1996). Inputs are 10 independent variables uniformly distributed on the interval [0,1], only 5 out of these 10 are actually used. Outputs are created according to the formula

y = 10 \sin(\pi x1 x2) + 20 (x3 - 0.5)^2 + 10 x4 + 5 x5 + e

where e is N(0,sd).

Usage

mlbench.friedman1(n, sd=1)

Arguments

n	number of patterns to create
sd	Standard deviation of noise

Value

Returns a list with components

x	input values (independent variables)
y	output values (dependent variable)

References

Breiman, Leo (1996) Bagging predictors. Machine Learning 24, pages 123-140.

Friedman, Jerome H. (1991) Multivariate adaptive regression splines. The Annals of Statistics 19 (1), pages 1-67.

mlbench documentation built on May 29, 2024, 4:49 a.m.