Constructing weak learner and performance evaluation in AdaBoost

Mian Zhou; Hong Wei

doi:10.1109/CISE.2009.5362581

Constructing weak learner and performance evaluation in AdaBoost

Mian Zhou^*, Hong Wei

^*Corresponding author for this work

Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review

2 Citations (Scopus)

Abstract

This paper gives a deep investigation into AdaBoost algorithm, which is used to boost the performance of any given learning algorithm. Within AdaBoost, weak learners are crucial and primitive parts of the algorithm. Since weak learners are required to train with weights, two types of weak learners: Artificial Neural Network weak learner and naive Bayes weak learner are designed. The results show AdaBoost by naive Bayes weak learners is superior to Artificial Neural Network weak learners, it shares the same generalisation ability with Support Vector Machine.

Original language	English
Title of host publication	Proceedings - 2009 International Conference on Computational Intelligence and Software Engineering, CiSE 2009
DOIs	https://doi.org/10.1109/CISE.2009.5362581
Publication status	Published - 2009
Externally published	Yes
Event	2009 International Conference on Computational Intelligence and Software Engineering, CiSE 2009 - Wuhan, China Duration: 11 Dec 2009 → 13 Dec 2009

Publication series

Name	Proceedings - 2009 International Conference on Computational Intelligence and Software Engineering, CiSE 2009

Conference

Conference	2009 International Conference on Computational Intelligence and Software Engineering, CiSE 2009
Country/Territory	China
City	Wuhan
Period	11/12/09 → 13/12/09

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10.1109/CISE.2009.5362581

Cite this

Zhou, M., & Wei, H. (2009). Constructing weak learner and performance evaluation in AdaBoost. In Proceedings - 2009 International Conference on Computational Intelligence and Software Engineering, CiSE 2009 Article 5362581 (Proceedings - 2009 International Conference on Computational Intelligence and Software Engineering, CiSE 2009). https://doi.org/10.1109/CISE.2009.5362581

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title = "Constructing weak learner and performance evaluation in AdaBoost",

abstract = "This paper gives a deep investigation into AdaBoost algorithm, which is used to boost the performance of any given learning algorithm. Within AdaBoost, weak learners are crucial and primitive parts of the algorithm. Since weak learners are required to train with weights, two types of weak learners: Artificial Neural Network weak learner and naive Bayes weak learner are designed. The results show AdaBoost by naive Bayes weak learners is superior to Artificial Neural Network weak learners, it shares the same generalisation ability with Support Vector Machine.",

author = "Mian Zhou and Hong Wei",

year = "2009",

doi = "10.1109/CISE.2009.5362581",

language = "English",

isbn = "9781424445073",

series = "Proceedings - 2009 International Conference on Computational Intelligence and Software Engineering, CiSE 2009",

booktitle = "Proceedings - 2009 International Conference on Computational Intelligence and Software Engineering, CiSE 2009",

note = "2009 International Conference on Computational Intelligence and Software Engineering, CiSE 2009 ; Conference date: 11-12-2009 Through 13-12-2009",

}

Zhou, M & Wei, H 2009, Constructing weak learner and performance evaluation in AdaBoost. in Proceedings - 2009 International Conference on Computational Intelligence and Software Engineering, CiSE 2009., 5362581, Proceedings - 2009 International Conference on Computational Intelligence and Software Engineering, CiSE 2009, 2009 International Conference on Computational Intelligence and Software Engineering, CiSE 2009, Wuhan, China, 11/12/09. https://doi.org/10.1109/CISE.2009.5362581

Constructing weak learner and performance evaluation in AdaBoost. / Zhou, Mian; Wei, Hong.
Proceedings - 2009 International Conference on Computational Intelligence and Software Engineering, CiSE 2009. 2009. 5362581 (Proceedings - 2009 International Conference on Computational Intelligence and Software Engineering, CiSE 2009).

Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review

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AU - Wei, Hong

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AB - This paper gives a deep investigation into AdaBoost algorithm, which is used to boost the performance of any given learning algorithm. Within AdaBoost, weak learners are crucial and primitive parts of the algorithm. Since weak learners are required to train with weights, two types of weak learners: Artificial Neural Network weak learner and naive Bayes weak learner are designed. The results show AdaBoost by naive Bayes weak learners is superior to Artificial Neural Network weak learners, it shares the same generalisation ability with Support Vector Machine.

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Constructing weak learner and performance evaluation in AdaBoost

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