A Hybrid MultiLayer Perceptron Under-Sampling with Bagging Dealing with a Real-Life Imbalanced Rice Dataset

A Hybrid MultiLayer Perceptron Under-Sampling with Bagging Dealing with a Real-Life Imbalanced Rice Dataset

Classification algorithms have shown exceptional prediction results in the supervised learning area. These classification algorithms are not always efficient when it comes to real-life datasets due to class distributions. As a result, datasets for real-life applications are generally imbalanced. Sev...

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Bibliographic Details
Main Authors: Moussa Diallo, Shengwu Xiong, Eshete Derb Emiru, Awet Fesseha, Aminu Onimisi Abdulsalami, Mohamed Abd Elaziz
Format: Article
Language:English
Published: MDPI AG 2021-07-01
Series:Information
Subjects:
classification algorithms
imbalanced dataset
climate change
rice dataset
office du Niger
Online Access:https://www.mdpi.com/2078-2489/12/8/291

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https://www.mdpi.com/2078-2489/12/8/291

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