Abstract
The main goal of this paper is the application of our fuzzy rule-based classification technique with genetically optimized accuracy-interpretability trade-off to the classification of the splice-junction DNA sequences coming from the Molecular Biology (Splice-junction Gene Sequences) benchmark data set (available from the UCI repository). Two multi-objective evolutionary optimization algorithms are employed and compared in the framework of our technique, i.e., the well-known Strength Pareto Evolutionary Algorithm 2 (SPEA2) and our SPEA2’s generalization (referred to as SPEA3) characterized by a higher spread and a better-balanced distribution of solutions. A comparative analysis with 15 alternative approaches is also performed.
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