Two Stages Based Adaptive Sampling Boosting Method

Wang, Cong-Man; Yang, Hao; Li, Fachao; Fu, Ruyan

doi:10.1109/icmlc.2006.259139

Search citation statements

Order By: Relevance

Paper Sections

Select...

Boosting2

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2013

Publication Types

Select...

Article1

Relationship

Self Cite0

Independent1

Authors

Journals

Cited by 1 publication

(2 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Traditional sampling methods such as roulette wheel selection is suitable for the learning procedure of reducing fitting error stage, and based on the characteristics of reducing variance stage, a new sampling method is proposed by Wang et al . (2006) named SS method. Based on continuous sampling plan and SS sampling methods, a new two stages based adaptive sampling boosting method named ASSBoosting is proposed by Wang et al .…”

Section: Boostingmentioning

confidence: 99%

See 1 more Smart Citation

Bagging and boosting variants for handling classifications problems: a survey

Kotsiantis

2013

The Knowledge Engineering Review

View full text Add to dashboard Cite

Bagging and boosting are two of the most well-known ensemble learning methods due to their theoretical performance guarantees and strong experimental results. Since bagging and boosting are an effective and open framework, several researchers have proposed their variants, some of which have turned out to have lower classification error than the original versions. This paper tried to summarize these variants and categorize them into groups. We hope that the references cited cover the major theoretical issues, and provide access to the main branches of the literature dealing with such methods, guiding the researcher in interesting research directions.

show abstract

Section: Boostingmentioning

confidence: 99%

“…Based on continuous sampling plan and SS sampling methods, a new two stages based adaptive sampling boosting method named ASSBoosting is proposed by Wang et al . (2006).…”

Section: Boostingmentioning

confidence: 99%

Bagging and boosting variants for handling classifications problems: a survey

Kotsiantis

2013

The Knowledge Engineering Review

View full text Add to dashboard Cite

show abstract

Two Stages Based Adaptive Sampling Boosting Method

Cited by 1 publication

References 5 publications

Bagging and boosting variants for handling classifications problems: a survey

Bagging and boosting variants for handling classifications problems: a survey

Contact Info

Product

Resources

About