friedman2: Benchmark Problem Friedman 2

In parboost: Distributed Model-Based Boosting

Description

Dataset taken from mlbench. The inputs are 4 independent variables uniformly distributed 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).

Format

A data frame with 100 rows and 5 variables

Source

http://cran.r-project.org/web/packages/mlbench/index.html

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.

Friedrich Leisch & Evgenia Dimitriadou (2010). mlbench: Machine Learning Benchmark Problems. R package version 2.1-1.

parboost documentation built on May 2, 2019, 5:08 a.m.