Abstract
As one of the important issues of data classification, classification has attracted the attention of many researchers in the field of data mining. Different from clustering research issues, in classification research issues, evolutionary clustering algorithms (EAs) were only used to improve the performance of classifiers either by optimizing the parameters or structure of the classifiers, or by pre-processing the inputs of the classifiers. Lots of evolutionary algorithms are employed to solve unsupervised classification, i.e., clustering. In this article, we will create a new mathematical model for supervised classification problem and use brain storm optimization algorithm (BSO) to search the global optimal solution, which resolved the problem of supervised classification with new ideas. The main objective is to find a better method. By using a new classification algorithm based on BSO, we are looking forward to optimizing the result.
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Xue, Y., Tang, T., Ma, T. (2016). Classification Based on Brain Storm Optimization Algorithm. In: Gong, M., Pan, L., Song, T., Zhang, G. (eds) Bio-inspired Computing – Theories and Applications. BIC-TA 2016. Communications in Computer and Information Science, vol 681. Springer, Singapore. https://doi.org/10.1007/978-981-10-3611-8_30
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DOI: https://doi.org/10.1007/978-981-10-3611-8_30
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