Hybridization of DEBOHID with ENN algorithm for highly imbalanced datasets by Sedat Korkmaz

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Hybrid clustering strategies for effective oversampling and undersampling in multiclass classification by Amirreza Salehi, Majid Khedmati

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SMOTE vs. SMOTEENN: A Study on the Performance of Resampling Algorithms for Addressing Class Imbalance in Regression Models by Gazi Husain, Daniel Nasef, Rejath Jose, Jonathan Mayer, Molly Bekbolatova, Timothy Devine, Milan Toma

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Sixth-Second Order Normalized Cumulant Blind Equalization Algorithm Based on Oversampling by Xiaoqin Zhang, Yongsheng Hu, Liyi Zhang

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Combinatorial intrusion detection model based on deep recurrent neural network and improved SMOTE algorithm by Binghao YAN, Guodong HAN

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Adaptive co-site interference cancellation algorithm with multiple virtual references by Yue-lei XIE, Jie LIU, Min-zheng LI, Shan OUYANG, Gui-sheng LIAO

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MKC-SMOTE: A Novel Synthetic Oversampling Method for Multi-Class Imbalanced Data Classification by Jiao Wang, Norhashidah Awang

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Enhancing Accuracy and Precision in Omni-Angle Edge-Based Modulation Transfer Function Measurements by Kenichiro Masaoka

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Enhancing Telemarketing Success Using Ensemble-Based Online Machine Learning by Shahriar Kaisar, Md Mamunur Rashid, Abdullahi Chowdhury, Sakib Shahriar Shafin, Joarder Kamruzzaman, Abebe Diro

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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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Machine Learning Algorithms Analysis of Synthetic Minority Oversampling Technique (SMOTE): Application to Credit Default Prediction by Emmanuel de-Graft Johnson Owusu-Ansah, Richard Doamekpor, Richard Kodzo Avuglah, Yaa Kyere Adwubi

Subjects: “…credit scoring, smote, oversampling, undersampling, class imbalance, machine learning algorithms…”
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A novel oversampling method based on Wasserstein CGAN for imbalanced classification by Hongfang Zhou, Heng Pan, Kangyun Zheng, Zongling Wu, Qingyu Xiang

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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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Multivariate Segment Expandable Encoder-Decoder Model for Time Series Forecasting by Yanhong Li, David C. Anastasiu

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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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Developing clinical prognostic models to predict graft survival after renal transplantation: comparison of statistical and machine learning models by Getahun Mulugeta, Temesgen Zewotir, Awoke Seyoum Tegegne, Mahteme Bekele Muleta, Leja Hamza Juhar

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Enhanced Fetal Arrhythmia Classification by Non-Invasive ECG Using Cross Domain Feature and Spatial Differences Windows Information by Gede Angga Pradipta, Putu Desiana Wulaning Ayu, Made Liandana, Dandy Pramana Hostiadi

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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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Detection Schemes With Low-Resolution ADCs and Spatial Oversampling for Transmission With Higher-Order Constellations in Terahertz Band by Christian Forsch, Peter Zillmann, Osama Alrabadi, Stefan Brueck, Wolfgang Gerstacker

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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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