pareto_filter: Generates normalized weight vector of k dimensions and s...
In ingridas/EPICR: An Implementation of Efficient Pareto Iterative Classification Method
Description
Usage
Arguments
Value
View source: R/pareto_filter.R
Description
Generates normalized weight vector of k dimensions and s divisions, so that each weight vector is near
the previous one. It uses the method of generating reflected k-ary Gray codes.
Usage
1
pareto_filter(y, x)
Arguments
y
- objective values corresponding to x
x
- decision values
Value
yp - Pareto front in the objective space, xp - Pareto set in the decision space,
ip - logical indicator, TRUE if solution is nondominated, FALSE if solution is dominated
ingridas/EPICR documentation built on May 18, 2019, 4:54 a.m.
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Description Usage Arguments Value
View source: R/pareto_filter.R
Description
Generates normalized weight vector of k dimensions and s divisions, so that each weight vector is near the previous one. It uses the method of generating reflected k-ary Gray codes.
Usage
1 | pareto_filter(y, x)
|
Arguments
y |
- objective values corresponding to |
x |
- decision values |
Value
yp - Pareto front in the objective space, xp - Pareto set in the decision space, ip - logical indicator, TRUE if solution is nondominated, FALSE if solution is dominated
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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