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Dimension reduction plays an important role in many classification tasks. In this work, we propose a new filter dimension reduction algorithm (PSOPRSE) using binary particle swarm optimisation and probabilistic rough set theory. PSOPRSE aims to maximise a classification performance measure and minimise a newly developed measure reflecting the number of attributes. Both measures are formed by probabilistic...
Based on binary particle swarm optimisation (BPSO) and information theory, this paper proposes two new filter feature selection methods for classification problems. The first algorithm is based on BPSO and the mutual information of each pair of features, which determines the relevance and redundancy of the selected feature subset. The second algorithm is based on BPSO and the entropy of each group...
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