Results 11 to 20 of about 46,171 (307)
Prediction of hematocrit through imbalanced dataset of blood spectra [PDF]
Healthcare Technology Letters, 2021 In spite of machine learning has been successfully used in a wide range of healthcare applications, there are several parameters that could influence the performance of a machine learning system.
Cristoforo Decaro +3 more
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An Imbalanced Generative Adversarial Network-Based Approach for Network Intrusion Detection in an Imbalanced Dataset [PDF]
Sensors, 2023 In modern networks, a Network Intrusion Detection System (NIDS) is a critical security device for detecting unauthorized activity. The categorization effectiveness for minority classes is limited by the imbalanced class issues connected with the dataset.
Yamarthi Narasimha Rao +1 more
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Imbalanced Ensemble Classifier for Learning from Imbalanced Business School Dataset [PDF]
International Journal of Mathematical, Engineering and Management Sciences, 2019 Private business schools in India face a regular problem of picking quality students for their MBA programs to achieve the desired placement percentage. Generally, such datasets are biased towards one class, i.e., imbalanced in nature.
Tanujit Chakraborty
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Boundary expansion algorithm of a decision tree induction for an imbalanced dataset [PDF]
Songklanakarin Journal of Science and Technology (SJST), 2017 A decision tree is one of the famous classifiers based on a recursive partitioning algorithm. This paper introduces the Boundary Expansion Algorithm (BEA) to improve a decision tree induction that deals with an imbalanced dataset.
Kesinee Boonchuay +2 more
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A Cost-Sensitive Ensemble Method for Class-Imbalanced Datasets [PDF]
Abstract and Applied Analysis, 2013 In imbalanced learning methods, resampling methods modify an imbalanced dataset to form a balanced dataset. Balanced data sets perform better than imbalanced datasets for many base classifiers.
Yong Zhang, Dapeng Wang
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Plant Identification in a Combined-Imbalanced Leaf Dataset
IEEE Access, 2022 Plant identification has applications in ethnopharmacology and agriculture. Since leaves are one of a distinguishable feature of a plant, they are routinely used for identification. Recent developments in deep learning have made it possible to accurately
Viraj K. Gajjar +2 more
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Three-Stage Recursive Learning Technique for Face Mask Detection on Imbalanced Datasets
MathematicsIn response to the COVID-19 pandemic, governments worldwide have implemented mandatory face mask regulations in crowded public spaces, making the development of automatic face mask detection systems critical.
Chi-Yi Tsai +2 more
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LoRAS: an oversampling approach for imbalanced datasets [PDF]
Machine Learning, 2020 AbstractThe Synthetic Minority Oversampling TEchnique (SMOTE) is widely-used for the analysis of imbalanced datasets. It is known that SMOTE frequently over-generalizes the minority class, leading to misclassifications for the majority class, and effecting the overall balance of the model.
Saptarshi Bej +4 more
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Intelligent Model for Enhancing the Bankruptcy Prediction with Imbalanced Data Using Oversampling and CatBoost [PDF]
International Journal of Intelligent Computing and Information Sciences, 2022 Bankruptcy prediction is one of the most significant financial decision-making problems, which prevents financial institutions from sever risks. Most of bankruptcy datasets suffer from imbalanced distribution between output classes, which could lead to ...
Samar Aly +2 more
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Applied Sciences, 2022 A homemade defective model of an induction motor was created by the laboratory team to acquire the vibration acceleration signals of five operating states of an induction motor under different loads. Two major learning models, namely a deep convolutional
Hong-Chan Chang +3 more
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