An Efficient AdaBoost Algorithm with the Multiple Thresholds Classification

An Efficient AdaBoost Algorithm with the Multiple Thresholds Classification

Adaptive boost (AdaBoost) is a prominent example of an ensemble learning algorithm that combines weak classifiers into strong classifiers through weighted majority voting rules. AdaBoost’s weak classifier, with threshold classification, tries to find the best threshold in one of the data dimensions,...

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Bibliografiska uppgifter
Huvudupphovsmän: Yi Ding, Hongyang Zhu, Ruyun Chen, Ronghui Li
Materialtyp: Artikel
Språk:English
Publicerad: MDPI AG 2022-06-01
Serie:Applied Sciences
Ämnen:
AdaBoost
Multiple Thresholds Classification
accuracy
generalization
Länkar:https://www.mdpi.com/2076-3417/12/12/5872

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https://www.mdpi.com/2076-3417/12/12/5872

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