icp.torus.eval {ClusTorus}R Documentation

Inductive prediction sets for each level

Description

icp.torus.eval evaluates whether each pre-specified evaluation point is contained in the inductive conformal prediction sets for each given level.

Usage

icp.torus.eval(icp.torus, level = 0.1, eval.point = grid.torus())

Arguments

icp.torus

an object containing all values to compute the conformity score, which will be constructed with icp.torus.score.

level

either a scalar or a vector, or even NULL. Default value is 0.1.

eval.point

N x N numeric matrix on [0, 2π)^2. Default input is grid.torus.

Value

returns a cp object with the boolean values which indicate whether each evaluation point is contained in the inductive conformal prediction sets for each given level.

References

S. Jung, K. Park, and B. Kim (2021), "Clustering on the torus by conformal prediction"

See Also

grid.torus, icp.torus.score

Examples


data <- toydata1[, 1:2]

icp.torus <- icp.torus.score(data, method = "all",
                             mixturefitmethod = "general",
                             param = list(J = 4, concentration = 25))

icp.torus.eval(icp.torus, level = c(0.1, 0.08), eval.point = grid.torus())


[Package ClusTorus version 0.1.3 Index]