Results 211 to 220 of about 39,020 (265)

PET-TURTLE: Deep Unsupervised Support Vector Machines for Imbalanced Data Clusters. [PDF]

IEEE Signal Process Lett
Salazar Cavazos J.
europepmc   +1 more source

Dilated Balanced cross entropy loss for medical image segmentation. [PDF]

BMC Med Imaging
Hosseini SM, Baghshah MS.
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A transfer learning approach for automatic conflicts detection in software requirement sentence pairs based on dual encoders. [PDF]

PLoS One
Wang Y, Jiang T, Bai J, Zou Z, Xue T, Zhang N, Luan J.   +6 more
europepmc   +1 more source

Key Measures for Evaluating Diagnostic Accuracy in Multi-Class Classification: An Overview and Simulation-Based Comparison. [PDF]

Korean J Radiol
Ryu L, Han K, Jung I, Park YW, Ahn SS, Hwang D.   +5 more
europepmc   +1 more source

Machine learning for land use change analysis in environmental protection areas. [PDF]

Environ Monit Assess
Lizcano Toledo MV, Rodrigues de Oliveira J, De Oro Arenas LA, Dutra Lusquinho Filho LA, Pereira Dos Santos A, Ferreira da Costa RV, Lourenço RW, da Cunha E Silva DC.   +7 more
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Assessing the data complexity of imbalanced datasets

Information Sciences, 2021
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Victor H. Barella, Luís Paulo F. Garcia, Marcilio C. P. de Souto, Ana Carolina Lorena, André C. P. L. F. de Carvalho   +4 more
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Detection of malicious javascript on an imbalanced dataset

Internet of Things, 2021
Abstract In order to be able to detect new malicious JavaScript with low cost, methods with machine learning techniques have been proposed and gave positive results. These methods focus on achieving a light-weight filtering model that can quickly and precisely filter out malicious data for dynamic analysis.
Phung Minh Ngoc, Mamoru Mimura
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Imbalanced Learning in Massive Phishing Datasets

2020 IEEE 6th Intl Conference on Big Data Security on Cloud (BigDataSecurity), IEEE Intl Conference on High Performance and Smart Computing, (HPSC) and IEEE Intl Conference on Intelligent Data and Security (IDS), 2020
Phishing is one of the major threats facing internet users in today’s work. Such attacks continue costing billions of dollars to companies around the words thus requiring more efficient detection techniques to curb the danger. This paper proposes a big data friendly implementation of Multiclass Imbalance Learning in Ensembles through Selective Sampling
Ali Azari, Josephine M. Namayanja, Navneet Kaur, Vasundhara Misal, Suraksha Shukla   +4 more
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