sim_circle {bark} | R Documentation |
The classification problem Circle is described in the BARK paper (2008).
Inputs are dim independent variables uniformly
distributed on the interval [-1,1]
, only the first 2
out of these dim are actually signals.
Outputs are created according to the formula
y = 1(x1^2+x2^2 \le 2/\pi)
sim_circle(n, dim = 5)
n |
number of data points to generate |
dim |
number of dimension of the problem, no less than 2 |
Returns a list with components
x |
input values (independent variables) |
y |
0/1 output values (dependent variable) |
Ouyang, Zhi (2008) Bayesian Additive Regression Kernels. Duke University. PhD dissertation, Chapter 3.
Other bark simulation functions:
sim_Friedman1()
,
sim_Friedman2()
,
sim_Friedman3()
Other bark functions:
bark-package-deprecated
,
bark-package
,
bark()
,
sim_Friedman1()
,
sim_Friedman2()
,
sim_Friedman3()
sim_circle(n=100, dim=5)