| name | pareto-frontier-identification |
| description | Identifying the set of non-dominated solutions in a multi-objective optimization problem. |
In multi-objective optimization (e.g., maximizing F1 while minimizing Delta), a solution is Pareto optimal if no other solution is better in both metrics.
Algorithm to find Pareto Frontier:
- Start with a list of candidate points (after filtering for
F1 > 0.5).
- A point $A$ is "dominated" by point $B$ if:
- $F1_B \ge F1_A$ AND $Delta_B \le Delta_A$
- AND at least one inequality is strict.
- The Pareto frontier consists of all points that are not dominated by any other point in the set.
Implementation Tip:
Sort the candidates by one objective (e.g., F1 descending) first. This simplifies the comparison logic as you iterate through the list to check for dominance.