FSSFO-based computationally efficient wrapper feature selection for software defect prediction using NASA/PROMISE datasets and multiple classifiers.
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Updated
Jul 21, 2026 - Python
FSSFO-based computationally efficient wrapper feature selection for software defect prediction using NASA/PROMISE datasets and multiple classifiers.
An experimental optimization project comparing classical and metaheuristic methods, applying a modified legacy EvoloPy framework to wrapper-based feature selection, and evaluating PSO with stagnation-aware early stopping.
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