Impact of a multiple oversampling technique-based assessment framework on shallow rockburst prediction models by Guozhu Rao, Guozhu Rao, Yunzhang Rao, Yunzhang Rao, Yangjun Xie, Qiang Huang, Jiazheng Wan, Jiyong Zhang

Subjects: “…oversampling techniques…”
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Predicting Depression: a comparative study of machine learning approaches based on language usage. by Luciana Mariñelarena-Dondena, Edgardo Ferretti, Manolis Maragoudakis, Maximiliano Sapino, Marcelo Luis Errecalde

Subjects: “…smote (synthetic minority oversampling technique)…”
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A stacked ensemble approach with resampling techniques for highly effective fraud detection in imbalanced datasets by Idongesit E. Eteng, Udeze L. Chinedu, Ayei E. Ibor

Subjects: “…Synthetic Minority Oversampling Technique (SMOTE)…”
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GAN data reconstruction based prediction method of telecom subscriber loss by Kehong A, Xiaodong HU

Subjects: “…synthetic mi-nority oversampling technique…”
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Synthetic Data Generation and Evaluation Techniques for Classifiers in Data Starved Medical Applications by Wan D. Bae, Shayma Alkobaisi, Matthew Horak, Siddheshwari Bankar, Sartaj Bhuvaji, Sungroul Kim, Choon-Sik Park

Subjects: “…synthetic minority oversampling technique…”
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Comprehensive Evaluation of Bankruptcy Prediction in Taiwanese Firms Using Multiple Machine Learning Models by Hung V. Pham, Tuan Chu, Tuan M. Le, Hieu M. Tran, Huong T.K. Tran, Khanh N. Yen, Son V. T. Dao

Subjects: “…synthetic minority oversampling technique (smote)…”
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Detection of UAV GPS Spoofing Attacks Using a Stacked Ensemble Method by Ting Ma, Xiaofeng Zhang, Zhexin Miao

Subjects: “…synthetic minority oversampling technique (SMOTE)…”
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