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首页> 外文期刊>International Journal of Innovative Research in Science, Engineering and Technology >HM Ant Miner Using Evolutionary Algorithm
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HM Ant Miner Using Evolutionary Algorithm

机译：使用进化算法的HM Ant Miner

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A novel Ant Colony Optimization algorithm (ACO) combined for the hierarchical multi- label classification problem of protein function prediction. This kind of problem is mainly focused on biometric area, given the large increase in the number of uncharacterized proteins available for analysis and the importance of determining their functions in order to improve the current biological knowledge. Because it is known that a protein can perform more than one function and many protein functional-definition schemes are organized in a hierarchical structure, the classification problem in this case is an instance of a hierarchical multilabel problem. In this classification method, each class might have multiple class labels and class labels are represented in a hierarchical structure—either a tree or a directed acyclic graph (DAG) structure. A more difficult problem than conventional flat classification in this approach, given that the classification algorithm has to take into account hierarchical relationships between class labels and be able to predict multiple class labels for the same example. The proposed ACO algorithm discovers an ordered list of hierarchical multi-label classification rules.
机译：结合蚁群优化算法（ACO）的蛋白质功能预测的分层多标签分类问题。鉴于可用于分析的未表征蛋白质的数量大量增加以及确定其功能以提高当前生物学知识的重要性，这种问题主要集中在生物特征领域。因为已知一种蛋白质可以执行多种功能，并且许多蛋白质功能定义方案以分层结构组织，所以这种情况下的分类问题就是分层多标签问题的一个实例。在这种分类方法中，每个类别可能具有多个类别标签，并且类别标签以分层结构（树或有向无环图（DAG）结构）表示。鉴于分类算法必须考虑类别标签之间的层次关系，并且能够预测同一示例的多个类别标签，因此比传统的平面分类更困难的问题是这种方法。提出的ACO算法发现了分层的多标签分类规则的有序列表。

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