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Deep Learning-Based Imbalanced Classification With Fuzzy Support Vector Machine
Frontiers in Bioengineering and Biotechnology, 2022 Imbalanced classification is widespread in the fields of medical diagnosis, biomedicine, smart city and Internet of Things. The imbalance of data distribution makes traditional classification methods more biased towards majority classes and ignores the ...
Ke-Fan Wang +6 more
doaj +1 more source
The Synthetic-Oversampling Method: Using Photometric Colors to Discover Extremely Metal-Poor Stars [PDF]
, 2015 Extremely metal-poor (EMP) stars ([Fe/H] < -3.0 dex) provide a unique window into understanding the first generation of stars and early chemical enrichment of the Universe.
Miller, A. A.
core +3 more sources
Adaptive equalization in oversampled subbands [PDF]
Conference Record of Thirty-Second Asilomar Conference on Signals, Systems and Computers (Cat. No.98CH36284), 1998 The potential presence of fractional delays, nonminimum phase parts, and a colouring of the channel output can require adaptive equalisers to adapt very long filters, which can have slow convergence for LMS-type adaptive algorithms. The authors present a novel oversampled subband approach to adaptive equalisation, which can both significantly reduce ...
Weiß, S. +3 more
openaire +7 more sources
Applied Sciences, 2019 A dropout early warning system enables schools to preemptively identify students who are at risk of dropping out of school, to promptly react to them, and eventually to help potential dropout students to continue their learning for a better future ...
Sunbok Lee, Jae Young Chung
doaj +1 more source
Entropy, 2021 Insider threats are malicious acts that can be carried out by an authorized employee within an organization. Insider threats represent a major cybersecurity challenge for private and public organizations, as an insider attack can cause extensive damage ...
Taher Al‐Shehari, Rakan Alsowail
semanticscholar +1 more source
AE-CGAN Model based High Performance Network Intrusion Detection System
Applied Sciences, 2019 In this paper, a high-performance network intrusion detection system based on deep learning is proposed for situations in which there are significant imbalances between normal and abnormal traffic.
JooHwa Lee, KeeHyun Park
doaj +1 more source
Credibility Based Imbalance Boosting Method for Software Defect Proneness Prediction
Applied Sciences, 2020 Imbalanced data are a major factor for degrading the performance of software defect models. Software defect dataset is imbalanced in nature, i.e., the number of non-defect-prone modules is far more than that of defect-prone ones, which results in the ...
Haonan Tong, Shihai Wang, Guangling Li
doaj +1 more source
Equalization with oversampling in multiuser CDMA systems [PDF]
, 2004 Some of the major challenges in the design of new-generation wireless mobile systems are the suppression of multiuser interference (MUI) and inter-symbol interference (ISI) within a single user created by the multipath propagation. Both of these problems
Vaidyanathan, P. P., Vrcelj, Bojan
core +3 more sources
Annals of Geophysics, 2000 The Center for Marine Resources and Environmental Technology has been developing a new method to improve the resolution of high-resolution seismic profiling.
C. R. Partouche
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Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi), 2020 Oversampling is a technique to balance the number of data records for each class by generating data with a small number of records in a class, so that the amount is balanced with data with a class with a large number of records.
Nurul Chamidah +2 more
doaj +1 more source