mlbench.friedman1

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).

datagen

A collection of artificial and real-world machine learning
benchmark problems, including, e.g., several
data sets from the UCI repository.

Friedrich Leisch

mlbench

Machine Learning Benchmark Problems

mlbench.friedman1 function

<dl><dt>n</dt>
<dd>number of patterns to create</dd><dt>sd</dt>
<dd>Standard deviation of noise</dd></dl>

Arguments

Benchmark Problem Friedman 1 — mlbench.friedman1

<dl>

<dt>n</dt>
<dd>number of patterns to create</dd>

<dt>sd</dt>
<dd>Standard deviation of noise</dd>

</dl>

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mlbench.friedman1: Benchmark Problem Friedman 1

Description

Usage

Value

Arguments

References