Navigating extreme class imbalance in suicide risk prediction [PDF]
Frontiers in PsychiatryBackgroundThe implementation of suicide risk models is challenging because the conditions in which they are developed often do not reflect those in which they are being used.
Christopher Kitchen +7 more
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LRID: A new metric of multi-class imbalance degree based on likelihood-ratio test [PDF]
Pattern Recognition Letters, 2018 In this paper, we introduce a new likelihood ratio imbalance degree (LRID) to measure the class-imbalance extent of multi-class data. Imbalance ratio (IR) is usually used to measure class-imbalance extent in imbalanced learning problems.
Rui Zhu, Zhanyu Ma, Guijin Wang
exaly +3 more sources
A systematic study of the class imbalance problem in convolutional neural networks
Neural Networks, 2018 In this study, we systematically investigate the impact of class imbalance on classification performance of convolutional neural networks (CNNs) and compare frequently used methods to address the issue.
Mateusz Buda +2 more
exaly +3 more sources
Optimizing Class Imbalance in Facial Expression Recognition Using Dynamic Intra-Class Clustering [PDF]
BiomimeticsWhile deep neural networks demonstrate robust performance in visual tasks, the long-tail distribution of real-world data leads to significant recognition accuracy degradation in critical scenarios such as medical human–robot affective interaction ...
Qingdu Li +8 more
doaj +2 more sources
Variance Extrapolated Class-Imbalance-Aware Domain Adaptive Myocardial Segmentation in Multi-Sequence Cardiac MRI. [PDF]
IEEE J Biomed Health InformXing F +6 more
europepmc +3 more sources
A novel generative adversarial networks modelling for the class imbalance problem in high dimensional omics data [PDF]
BMC Medical Informatics and Decision MakingClass imbalance remains a large problem in high-throughput omics analyses, causing bias towards the over-represented class when training machine learning-based classifiers.
Samuel Cusworth +2 more
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DATA IMBALANCE IN LANDSLIDE SUSCEPTIBILITY ZONATION: UNDER-SAMPLING FOR CLASS-IMBALANCE LEARNING [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2020 Machine learning methods such as artificial neural network, support vector machine etc. require a large amount of training data, however, the number of landslide occurrences are limited in a study area.
S. K. Gupta +3 more
doaj +1 more source
JOIV: International Journal on Informatics Visualization, 2021 The class imbalance problem in the multi-class dataset is more challenging to manage than the problem in the two classes and this problem is more complicated if accompanied by overlapping.
Hartono Hartono, Erianto Ongko
doaj +1 more source
A Hybrid Sampling Approach for Imbalanced Binary and Multi-Class Data Using Clustering Analysis
IEEE Access, 2022 Unequal data distribution among different classes usually cause a class imbalance problem. Due to the class imbalance, the classification models become biased toward the majority class and misclassify the minority class.
Abdul Sattar Palli +4 more
doaj +1 more source
Experimental Comparison of Classification Methods under Class Imbalance [PDF]
EAI Endorsed Transactions on Scalable Information Systems, 2021 The class imbalance problem is prevalent in many domains including medical, natural language processing, image recognition, economic and geographic areas etc.
Hui Chen, Mengru Ji
doaj +1 more source