Applications of Support Vector Machine (SVM) Learning in Cancer Genomics. [PDF]
Cancer Genomics Proteomics, 2018 Machine learning with maximization (support) of separating margin (vector), called support vector machine (SVM) learning, is a powerful classification tool that has been used for cancer genomic classification or subtyping. Today, as advancements in high-throughput technologies lead to production of large amounts of genomic and epigenomic data, the ...
Huang S +5 more
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Deep Learning Based Skin Lesion Segmentation and Classification of Melanoma Using Support Vector Machine (SVM) [PDF]
Asian Pac J Cancer Prev, 2019 Objective: The main objective of this study is to improve the classification performance of melanoma using deep learning based automatic skin lesion segmentation.
R D S, A S.
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Analysis of dengue infection based on Raman spectroscopy and support vector machine (SVM). [PDF]
Biomed Opt Express, 2016 The current study presents the use of Raman spectroscopy combined with support vector machine (SVM) for the classification of dengue suspected human blood sera. Raman spectra for 84 clinically dengue suspected patients acquired from Holy Family Hospital,
Khan S +5 more
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Penerapan Support Vector Machine (SVM) untuk Pengkategorian Penelitian
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi), 2017 Research every college will continue to grow. Research will be stored in softcopy and hardcopy. The preparation of the research should be categorized in order to facilitate the search for people who need reference.
Fithri Selva Jumeilah
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Application of support vector machine (SVM) for prediction toxic activity of different data sets
Toxicology, 2006 As a new method, support vector machine (SVM) were applied for prediction of toxicity of different data sets compared with other two common methods, multiple linear regression (MLR) and RBFNN.
B T Fan, M C Liu, Z D Hu
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Multiclass Contour-Preserving Classification with Support Vector Machine (SVM)
Journal of Intelligent Systems, 2017 Multiclass contour-preserving classification (MCOV) has been used to preserve the contour of the data set and improve the classification accuracy of a feed-forward neural network.
Fuangkhon Piyabute
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CompareSVM: supervised, Support Vector Machine (SVM) inference of gene regularity networks. [PDF]
BMC Bioinformatics, 2014 Predication of gene regularity network (GRN) from expression data is a challenging task. There are many methods that have been developed to address this challenge ranging from supervised to unsupervised methods.
Gillani Z, Akash MS, Rahaman MD, Chen M.
europepmc +2 more sources
PVP-SVM: Sequence-Based Prediction of Phage Virion Proteins Using a Support Vector Machine
Frontiers in Microbiology, 2018 Accurately identifying bacteriophage virion proteins from uncharacterized sequences is important to understand interactions between the phage and its host bacteria in order to develop new antibacterial drugs.
Tae Hwan Shin +2 more
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Research on Bearing Fault Diagnosis Method Based on IPSO-RVM
Journal of Harbin University of Science and Technology, 2022 Aiming at the problems of poor classification effect of support vector machine in traditional particle swarm optimization support vector machine and inaccuracy of traditional particle swarm optimization in bearing fault diagnosis, an improved particle ...
ZHANG Han +4 more
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