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   Articles with "data imbalance" as a keyword



Parallel and incremental credit card fraud detection model to handle concept drift and data imbalance

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recommendations! Published in 2018 at "Neural Computing and Applications"

DOI: 10.1007/s00521-018-3633-8

Abstract: Real-time fraud detection in credit card transactions is challenging due to the intrinsic properties of transaction data, namely data imbalance, noise, borderline entities and concept drift. The advent of mobile payment systems has further complicated… read more here.

Keywords: fraud detection; model; credit card; data imbalance ... See more keywords

Data imbalance in cardiac health diagnostics using CECG-GAN

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recommendations! Published in 2024 at "Scientific Reports"

DOI: 10.1038/s41598-024-65619-8

Abstract: Heart disease is the world’s leading cause of death. Diagnostic models based on electrocardiograms (ECGs) are often limited by the scarcity of high-quality data and issues of data imbalance. To address these challenges, we propose… read more here.

Keywords: imbalance cardiac; data imbalance; cecg gan;

Imbalanced feature generation based on bootstrap power spectral curve for estimating respiratory rate

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recommendations! Published in 2025 at "Scientific Reports"

DOI: 10.1038/s41598-025-02270-x

Abstract: Rapid respiratory rate (RR) changes in older adults may indicate serious illness. Therefore, accurately estimating RR for cardiorespiratory fitness is essential. However, machine learning algorithm-related errors are unsuitable for medical decision-making processes because some data… read more here.

Keywords: data imbalance; imbalanced feature; methodology; feature ... See more keywords

ProEGAN-MS: A Progressive Growing Generative Adversarial Networks for Electrocardiogram Generation

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recommendations! Published in 2021 at "IEEE Access"

DOI: 10.1109/access.2021.3069827

Abstract: Electrocardiogram (ECG) is a physiological signal widely used in monitoring heart health, which is of great significance to the detection and diagnosis of heart diseases. Because abnormal heart rhythms are very rare, most ECG datasets… read more here.

Keywords: progressive growing; generation; data imbalance; model ... See more keywords

How to Handle Data Imbalance and Feature Selection Problems in CNN-Based Stock Price Forecasting

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recommendations! Published in 2022 at "IEEE Access"

DOI: 10.1109/access.2022.3160797

Abstract: Stock market forecasting is a time series problem that aims to predict possible future prices or directions of an index/stock. The stock data contains high uncertainty and is influenced by too many factors; hence it… read more here.

Keywords: data imbalance; cnn based; stock; feature selection ... See more keywords

YOLO-MR: Meta-Learning-Based Lesion Detection Algorithm for Resolving Data Imbalance

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recommendations! Published in 2024 at "IEEE Access"

DOI: 10.1109/access.2024.3384088

Abstract: The early detection and precise diagnosis of gastrointestinal diseases, particularly gastric cancer, play a vital role in improving patient survival rates and treatment outcomes. However, diagnosing these conditions can be challenging when symptoms are mild… read more here.

Keywords: data imbalance; model; yolo model; meta ... See more keywords

Majority or Minority: Data Imbalance Learning Method for Named Entity Recognition

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recommendations! Published in 2024 at "IEEE Access"

DOI: 10.1109/access.2024.3522972

Abstract: Data imbalance presents a significant challenge in various machine learning (ML) tasks, particularly named entity recognition (NER) within natural language processing (NLP). NER exhibits a data imbalance with a long-tail distribution, featuring numerous minority classes… read more here.

Keywords: data imbalance; majority; entity; language ... See more keywords

Few-Shot GAN: Improving the Performance of Intelligent Fault Diagnosis in Severe Data Imbalance

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recommendations! Published in 2023 at "IEEE Transactions on Instrumentation and Measurement"

DOI: 10.1109/tim.2023.3271746

Abstract: In severe data imbalance scenarios, fault samples are generally scarce, challenging the health management of industrial machinery significantly. Generative adversarial network (GAN), a promising solution to solve the data imbalance problem, suffers from a negative… read more here.

Keywords: severe data; fault diagnosis; data imbalance; imbalance ... See more keywords

GA-CatBoost-Weight Algorithm for Predicting Casualties in Terrorist Attacks: Addressing Data Imbalance and Enhancing Performance

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recommendations! Published in 2024 at "Mathematics"

DOI: 10.3390/math12060818

Abstract: Terrorism poses a significant threat to international peace and stability. The ability to predict potential casualties resulting from terrorist attacks, based on specific attack characteristics, is vital for protecting the safety of innocent civilians. However,… read more here.

Keywords: data imbalance; algorithm; terrorist attacks; catboost weight ... See more keywords