A Novel Diversity Measure and Classifier Selection Approach for Generating Ensemble Classifiers

A Novel Diversity Measure and Classifier Selection Approach for Generating Ensemble Classifiers

Accuracy and diversity are considered to be the two deriving factors when it comes to generating an ensemble classifier. Focusing only on accuracy causes the ensemble classifier to suffer from “diminishing returns” and the ensemble accuracy tends to plateau; whereas focusing on...

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Bibliographic Details
Main Authors: Muhammad Zohaib Jan, Brijesh Verma
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Ensemble classifiers
neural networks
multiple classifiers learning
diversity measures
Online Access:https://ieeexplore.ieee.org/document/8880589/

Internet

https://ieeexplore.ieee.org/document/8880589/

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