Results 21 to 30 of about 18,586 (269)
A New Under-Sampling Method to Face Class Overlap and Imbalance
Applied Sciences, 2020 Class overlap and class imbalance are two data complexities that challenge the design of effective classifiers in Pattern Recognition and Data Mining as they may cause a significant loss in performance.
Angélica Guzmán-Ponce +3 more
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PLoS ONE, 2021 The spread of Covid-19 has resulted in worldwide health concerns. Social media is increasingly used to share news and opinions about it. A realistic assessment of the situation is necessary to utilize resources optimally and appropriately.
Furqan Rustam +5 more
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The African Journal of Information and Communication, 2023 The narratives shared on social media during a health crisis such as COVID-19 reflect public perceptions of the crisis. This article provides findings from a study of the perceptions of South African citizens regarding the government’s response to the ...
Temitope Kekere +2 more
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A Classifier Capable of Handling Incomplete Data Set
The Journal of the Korean Institute of Information and Communication Engineering, 2010 This paper introduces a classification algorithm which can be applied to a learning problem with incomplete data sets, missing variable values or a class value. This algorithm uses a data expansion method which utilizes weighted values and probability techniques. It operates by extending a classifier which are considered to be in the optimal projection
Jong-Chan Lee, Won-Don Lee
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Remote Sensing, 2022 The class imbalance problem has been reported to exist in remote sensing and hinders the classification performance of many machine learning algorithms.
Daying Quan +5 more
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Random Partition Based Adaptive Distributed Kernelized SVM for Big Data
IEEE Access, 2022 In this paper, we present a distributed classification technique for big data by efficiently using distributed storage architecture and data processing units of a cluster.
Amrit Pal +5 more
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A Novel Integrated Classifier for Handling Data Warehouse Anomalies [PDF]
, 2011 Within databases employed in various commercial sectors, anomalies continue to persist and hinder the overall integrity of data. Typically, Duplicate, Wrong and Missed observations of spatial-temporal data causes the user to be not able to accurately utilise recorded information.
Darcy, Peter +2 more
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Hybrid Deep Learning Models for Multi-classification of Tumour from Brain MRI
Journal of Information Systems Engineering and Business Intelligence, 2022 Background: Brain tumour categorisation can be assisted with computer-aided diagnostic (CAD) for medical applications. Biopsies to classify brain tumours can be costly and time-consuming. Radiologists may also misclassify brain tumour types when handling
Hafiza Akter Munira, Md Saiful Islam
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Entropy-Based Classifier Enhancement to Handle Imbalanced Class Problem
Procedia Computer Science, 2017 The paper presents a possible enhancement of entropy-based classifiers to handle problems, caused by the class imbalance in the original dataset. The proposed method was tested on synthetic data in order to analyse its robustness in the controlled environment with different class proportions.
Kirshners, Arnis +2 more
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FAWOS: Fairness-Aware Oversampling Algorithm Based on Distributions of Sensitive Attributes
IEEE Access, 2021 With the increased use of machine learning algorithms to make decisions which impact people’s lives, it is of extreme importance to ensure that predictions do not prejudice subgroups of the population with respect to sensitive attributes such as ...
Teresa Salazar +3 more
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