Improving the Performance of an Associative Classifier in the Context of Class-Imbalanced Classification

Improving the Performance of an Associative Classifier in the Context of Class-Imbalanced Classification

Class imbalance remains an open problem in pattern recognition, machine learning, and related fields. Many of the state-of-the-art classification algorithms tend to classify all unbalanced dataset patterns by assigning them to a majority class, thus failing to correctly classify a minority class. As...

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Bibliographic Details
Main Authors: Carlos Alberto Rolón-González, Rodrigo Castañón-Méndez, Antonio Alarcón-Paredes, Itzamá López-Yáñez, Cornelio Yáñez-Márquez
Format: Article
Language:English
Published: MDPI AG 2021-05-01
Series:Electronics
Subjects:
associative memories
class-imbalanced datasets
pattern classifier
Lernmatrix
linear associator
Online Access:https://www.mdpi.com/2079-9292/10/9/1095

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https://www.mdpi.com/2079-9292/10/9/1095

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