mlbench.friedman1: Benchmark Problem Friedman 1

Description Usage Arguments Value References

View source: R/mlbench-regression.R

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(π x1 x2) + 20 (x3 - 0.5)^2 + 10 x4 + 5 x5 + e

where e is N(0,sd).

Usage

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 Jan. 29, 2021, 5:05 p.m.