Decision Tree and Ensemble Learning Algorithms with Their Applications in Bioinformatics
Decision Tree and Ensemble Learning Algorithms with Their Applications in Bioinformatics
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DOI：
10.1007/978-1-4419-7046-6_19
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发表时间：
2011-01-01
期刊：
影响因子：
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通讯作者：
Tao, Xiuping
中科院分区：
文献类型：
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作者：
Che, Dongsheng;Liu, Qi;Tao, Xiuping
机器学习方法在生物信息学中有着广泛的应用，决策树是该领域应用最成功的方法之一。在这一章中，我们简要回顾了决策树和相关的集成算法，并展示了这些方法在解决生物问题上的成功应用。我们希望通过学习决策树和集成分类器的算法，生物学家可以对机器学习算法的工作原理有基本的了解。另一方面，通过接触决策树和集成算法在生物信息学中的应用，计算机科学家可以更好地了解他们在未来的研究方向中可能致力于哪些生物信息学主题。我们的目标是提供一个平台，弥合生物学家和计算机科学家之间的差距。
Machine learning approaches have wide applications in bioinformatics, and decision tree is one of the successful approaches applied in this field. In this chapter, we briefly review decision tree and related ensemble algorithms and show the successful applications of such approaches on solving biological problems. We hope that by learning the algorithms of decision trees and ensemble classifiers, biologists can get the basic ideas of how machine learning algorithms work. On the other hand, by being exposed to the applications of decision trees and ensemble algorithms in bioinformatics, computer scientists can get better ideas of which bioinformatics topics they may work on in their future research directions. We aim to provide a platform to bridge the gap between biologists and computer scientists.