Enhancing Image Classification of Cabbage Plant Diseases Using a Hybrid Model Convolutional Neural Network and XGBoost

Classifying imbalanced datasets presents significant challenges, often leading to biased model performance, particularly in multiclass classification. This study addresses these issues by integrating Convolutional Neural Networks (CNN) and XGBoost, leveraging CNN’s exceptional feature extraction cap...

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Bibliographic Details
Main Authors:	Nabila Ayunda Sovia, Ni Wayan Surya Wardhani, Eni Sumarminingsih, Elvo Ramadhan Shofa
Format:	Article
Language:	English
Published:	Mathematics Department UIN Maulana Malik Ibrahim Malang 2025-03-01
Series:	Cauchy: Jurnal Matematika Murni dan Aplikasi
Subjects:	cabbage classification convolutional neural network imbalance data xgboost
Online Access:	https://ejournal.uin-malang.ac.id/index.php/Math/article/view/30866
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Enhancing Image Classification of Cabbage Plant Diseases Using a Hybrid Model Convolutional Neural Network and XGBoost

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