Optimal Trees Selection for Classification via Out-of-Bag Assessment and Sub-Bagging

Optimal Trees Selection for Classification via Out-of-Bag Assessment and Sub-Bagging

The effect of training data size on machine learning methods has been well investigated over the past two decades. The predictive performance of tree based machine learning methods, in general, improves with a decreasing rate as the size of training data increases. We investigate this in optimal tre...

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Bibliographic Details
Main Authors: Zardad Khan, Naz Gul, Nosheen Faiz, Asma Gul, Werner Adler, Berthold Lausen
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Tree selection
classification
ensemble learning
out-of-bag sample
random forest
sub-bagging
Online Access:https://ieeexplore.ieee.org/document/9343298/

Internet

https://ieeexplore.ieee.org/document/9343298/

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