Orderly Roulette Selection Based Ant Colony Algorithm for Hierarchical Multilabel Protein Function Prediction

Zhengping Liang, Rui Guo, Jiangtao Sun, Zhong Ming and Zexuan Zhu

Mathematical Problems in Engineering, 2017, vol. 2017, 1-15

Abstract:

Ant colony optimization (ACO) algorithms have been successfully applied to identify classification rules in data mining. This paper proposes a new ant colony optimization algorithm, named , for the hierarchical multilabel classification problem in protein function prediction. The proposed algorithm is characterized by an orderly roulette selection strategy that distinguishes the merits of the data attributes through attributes importance ranking in classification model construction. A new pheromone update strategy is introduced to prevent the algorithm from getting trapped in local optima and thus leading to more efficient identification of classification rules. The comparison studies to other closely related algorithms on 16 publicly available datasets reveal the efficiency of the proposed algorithm.

Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:6320273

DOI: 10.1155/2017/6320273

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