Abstract
In this paper, we propose an ant evolutionary classification model, which treats different classes as ant colonies to classify the unlabeled instances. In our model, each ant colony sends its members to propagate its unique pheromone on the unlabeled instances. The unlabeled instances are treated as unlabeled ants. They are assigned to different ant colonies according to the pheromone that different colonies leave on it. Next, the natural selection is carried out to maintain the history colony information as well as the scale of swarms. Theoretical analysis and experimental results show the effectiveness of our proposed model for evolutionary data classification.
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He, P., Xu, X., Lu, L., Qian, H., Zhang, W., Li, K. (2014). Semi-supervised Ant Evolutionary Classification. In: Tan, Y., Shi, Y., Coello, C.A.C. (eds) Advances in Swarm Intelligence. ICSI 2014. Lecture Notes in Computer Science, vol 8795. Springer, Cham. https://doi.org/10.1007/978-3-319-11897-0_1
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DOI: https://doi.org/10.1007/978-3-319-11897-0_1
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