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

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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

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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

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Gait-based Parkinson’s disease diagnosis and severity classification using force sensors and machine learning by Navita, Pooja Mittal, Yogesh Kumar Sharma, Anjani Kumar Rai, Sarita Simaiya, Umesh Kumar Lilhore, Vimal Kumar

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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

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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

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Improving Diabetes Prediction Accuracy in Indonesia: A Comparative Analysis of SVM, Logistic Regression, and Naive Bayes with SMOTE and ADASYN by Selly Rahmawati, Arief Wibowo, Anis Fitri Nur Masruriyah

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S-DCNN: prediction of ATP binding residues by deep convolutional neural network based on SMOTE by Sixi Hao, Sixi Hao, Cai-Yan Li, Xiuzhen Hu, Zhenxing Feng, Gaimei Zhang, Caiyun Yang, Huimin Hu

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Detection of UAV GPS Spoofing Attacks Using a Stacked Ensemble Method by Ting Ma, Xiaofeng Zhang, Zhexin Miao

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Penerapan SMOTE untuk Mengatasi Imbalance Class dalam Klasifikasi Kepribadian MBTI Menggunakan Naive Bayes Classifier by Mutiara Persada Pulungan, Andi Purnomo, Aliyah Kurniasih

Subjects: “…Imbalance Class, Synthetic Minority Over-sampling Technique (SMOTE)…”
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