Benchmark Problem Friedman 2

Description

The regression problem Friedman 2 as described in Friedman (1991) and Breiman (1996). Inputs are 4 independent variables uniformly distrtibuted over the ranges

0 ≤ x1 ≤ 100

40 π ≤ x2 ≤ 560 π

0 ≤ x3 ≤ 1

1 ≤ x4 ≤ 11

The outputs are created according to the formula

y = (x1^2 + (x2 x3 - (1/(x2 x4)))^2)^{0.5} + e

where e is N(0,sd).

Usage

mlbench.friedman2(n, sd=125)

Arguments

Value

Returns a list with components

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.

Results