A Gene Expression Programming Algorithm for Multi-Label Classification
This paper presents a Gene Expression Programming algorithm for multi-label classification which encodes a discriminant function into each individual to show whether a pattern belongs to a given class or not. The algorithm also applies a niching technique to guarantee that the population includes functions for each existing class. The algorithm has been compared to other recently published algorithms. The results found on several datasets demonstrate the feasibility of this approach in the tackling of multi-label problems.
gene expression programming multi-label classification discriminant functions machine learning