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Journal of Computer and Creative Technologyปัญหาความไม่สมดุลของข้อมูลในกระบวนการเรียนรู้ของเครื่องเป็นข้อจำกัดสำคัญที่ส่งผลต่อประสิทธิภาพของโมเดล โดยเฉพาะในกรณีที่กลุ่มข้อมูลกลุ่มน้อยมีจำนวนน้อยกว่ากลุ่มข้อมูลกลุ่มใหญ่ ทำให้โมเดลเรียนรู้มีความลำเอียงและจำแนกข้อมูลได้ไม่แม่นยำ วิธีการแก้ไขปัญหานี้
วริสรา วสุอารยะศักดิ์ +3 more
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Implementasi SMOTE dan Under Sampling pada Imbalanced Dataset untuk Prediksi Kebangkrutan Perusahaan
Jurnal Komputer Terapan, 2021 Kebangkrutan pada suatu perusahaan menjadi masalah yang serius karena dapat menyebabkan kerusakan ekonomi serta konsekuensi sosial lainnya. Sangat penting untuk melakukan prediksi kebangkrutan sedini mungkin karena prediksi ini dapat bermanfaat untuk ...
Wilda Imama Sabilla +1 more
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Data Driven Prognosis of Cervical Cancer Using Class Balancing and Machine Learning Techniques [PDF]
EAI Endorsed Transactions on Energy Web, 2020 INTRODUCTION: With the progression of innovation and its joint effort with health care services, the world has achieved a lot of benefits. AI procedures and machine learning techniques are constantly improving existing statistical methods for better ...
Mamta Arora +2 more
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Prediction of the Road Accidents Severity Level: Case of Saint-Petersburg and Leningrad Oblast
International Journal of Technology, 2023 This article examines the factors influencing the severity of road accidents in St. Petersburg and Leningrad oblast for 2015–2023. The study is carried out on the analysis of 69190 road accidents and 6 groups of factors using the logit model and ...
Angi Skhvediani +3 more
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Analysis and Classification of Customer Churn Using Machine Learning Models
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi), 2023 Analysis studies of customer loss (customer churn) have been used for years to increase profitability and build customer relationships with companies.
Muhammad Maulana Sidiq Nurhidayat +1 more
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IEEE AccessImbalanced class distribution reduces the generalizability of classifiers in EEG-based epilepsy detection. This study examines the impact of the synthetic minority oversampling technique (SMOTE) and its variants on imbalanced electroencephalography (EEG)
Ahmet Gokay Calis, Halit Ergezer
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IEEE AccessAnemia is a widespread worldwide health problem that has a substantial effect on groups who are particularly susceptible. The objective of this work is to improve the diagnosis of anemia by creating a hybrid machine learning model called SMOTE-MRS.
Dimas Chaerul Ekty Saputra +2 more
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Addressing imbalanced data classification with Cluster-Based Reduced Noise SMOTE.
PLoS ONEIn recent years, the challenge of imbalanced data has become increasingly prominent in machine learning, affecting the performance of classification algorithms. This study proposes a novel data-level oversampling method called Cluster-Based Reduced Noise
Javad Hemmatian +2 more
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A SMOTE PCA HDBSCAN approach for enhancing water quality classification in imbalanced datasets
Scientific ReportsClass imbalance poses a significant challenge in water quality classification, often leading to biased predictions and diminished accuracy for minority classes.
Norashikin Nasaruddin +3 more
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IEEE AccessClass-imbalance problems have become a key challenge in machine learning, often results in training too many majority samples and learning too few minority samples.
Yongjie Huang
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