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Decision Tree and Ensemble Learning Algorithms with Their Applications in Bioinformatics

  • Dongsheng Che
  • Qi Liu
  • Khaled Rasheed
  • Xiuping Tao
Chapter
Part of the Advances in Experimental Medicine and Biology book series (AEMB, volume 696)

Abstract

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.

Keywords

Decision Tree Random Forest Base Classifier Ensemble Classifier Decision Tree Algorithm 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  • Dongsheng Che
    • 1
  • Qi Liu
  • Khaled Rasheed
  • Xiuping Tao
  1. 1.Department of Computer ScienceEast Stroudsburg UniversityEast StroudsburgUSA

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