首页> 外文期刊>Advances in Experimental Medicine and Biology >Decision tree and ensemble learning algorithms with their applications in bioinformatics
【24h】

Decision tree and ensemble learning algorithms with their applications in bioinformatics

机译:决策树和集成学习算法及其在生物信息学中的应用

获取原文
获取原文并翻译 | 示例

摘要

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.
机译:机器学习方法在生物信息学中具有广泛的应用,决策树是该领域成功应用的方法之一。在本章中,我们简要回顾了决策树和相关的集成算法,并展示了这种方法在解决生物学问题上的成功应用。我们希望,通过学习决策树和集成分类器的算法,生物学家可以获得机器学习算法如何工作的基本思想。另一方面,通过暴露于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可能在未来的研究方向上从事哪些生物信息学主题。我们旨在提供一个平台,以弥合生物学家和计算机科学家之间的鸿沟。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号