Watch the Dallas Symposium LIVE, and fundraiser auction
Ticket proceeds support mindat.org! - click here...
Log InRegister
Quick Links : The Mindat ManualThe Rock H. Currier Digital LibraryMindat Newsletter [Free Download]
Home PageAbout MindatThe Mindat ManualHistory of MindatCopyright StatusWho We AreContact UsAdvertise on Mindat
Donate to MindatCorporate SponsorshipSponsor a PageSponsored PagesMindat AdvertisersAdvertise on Mindat
Learning CenterWhat is a mineral?The most common minerals on earthInformation for EducatorsMindat ArticlesThe ElementsThe Rock H. Currier Digital LibraryGeologic Time
Minerals by PropertiesMinerals by ChemistryAdvanced Locality SearchRandom MineralRandom LocalitySearch by minIDLocalities Near MeSearch ArticlesSearch GlossaryMore Search Options
Search For:
Mineral Name:
Locality Name:
Keyword(s):
 
The Mindat ManualAdd a New PhotoRate PhotosLocality Edit ReportCoordinate Completion ReportAdd Glossary Item
Mining CompaniesStatisticsUsersMineral MuseumsClubs & OrganizationsMineral Shows & EventsThe Mindat DirectoryDevice SettingsThe Mineral Quiz
Photo SearchPhoto GalleriesSearch by ColorNew Photos TodayNew Photos YesterdayMembers' Photo GalleriesPast Photo of the Day GalleryPhotography

Zhang, Wei, Du, Lan, Li, Liling, Zhang, Xuefeng, Liu, Hongwei (2018) Infinite Bayesian one-class support vector machine based on Dirichlet process mixture clustering. Pattern Recognition, 78. 56-78 doi:10.1016/j.patcog.2018.01.006

Advanced
   -   Only viewable:
Reference TypeJournal (article/letter/editorial)
TitleInfinite Bayesian one-class support vector machine based on Dirichlet process mixture clustering
JournalPattern Recognition
AuthorsZhang, WeiAuthor
Du, LanAuthor
Li, LilingAuthor
Zhang, XuefengAuthor
Liu, HongweiAuthor
Year2018 (June)Volume78
PublisherElsevier BV
DOIdoi:10.1016/j.patcog.2018.01.006Search in ResearchGate
Generate Citation Formats
Mindat Ref. ID9367337Long-form Identifiermindat:1:5:9367337:0
GUID0
Full ReferenceZhang, Wei, Du, Lan, Li, Liling, Zhang, Xuefeng, Liu, Hongwei (2018) Infinite Bayesian one-class support vector machine based on Dirichlet process mixture clustering. Pattern Recognition, 78. 56-78 doi:10.1016/j.patcog.2018.01.006
Plain TextZhang, Wei, Du, Lan, Li, Liling, Zhang, Xuefeng, Liu, Hongwei (2018) Infinite Bayesian one-class support vector machine based on Dirichlet process mixture clustering. Pattern Recognition, 78. 56-78 doi:10.1016/j.patcog.2018.01.006
In(2018) Pattern Recognition Vol. 78. Elsevier BV

See Also

These are possibly similar items as determined by title/reference text matching only.

Wang, Huajun, Zhang, Hongwei, Li, Wenqian (2024) Sparse and robust support vector machine with capped squared loss for large-scale pattern classification. Pattern Recognition, 153. 110544 doi:10.1016/j.patcog.2024.110544
Zhang, Shunli, Lu, Wei, Xing, Weiwei, Zhang, Li (2018) Using fuzzy least squares support vector machine with metric learning for object tracking. Pattern Recognition, 84. 112-125 doi:10.1016/j.patcog.2018.07.012
Xing, Hong-Jie, Ji, Man (2018) Robust one-class support vector machine with rescaled hinge loss function. Pattern Recognition, 84. 152-164 doi:10.1016/j.patcog.2018.07.015
Guo, Yinan, Zhang, Zirui, Tang, Fengzhen (2021) Feature selection with kernelized multi-class support vector machine. Pattern Recognition, 117. 107988pp. doi:10.1016/j.patcog.2021.107988
Kumari, Anuradha; Tanveer, M. (2025) Enhancing robustness and sparsity: Least squares one-class support vector machine. Pattern Recognition, 167. doi:10.1016/j.patcog.2025.111691
Sadooghi, Mohammad Saleh, Esmaeilzadeh Khadem, Siamak (2018) Improving one class support vector machine novelty detection scheme using nonlinear features. Pattern Recognition, 83. 14-33 doi:10.1016/j.patcog.2018.05.002
Bicego, Manuele, Figueiredo, Mario A.T. (2009) Soft clustering using weighted one-class support vector machines. Pattern Recognition, 42 (1). 27-32 doi:10.1016/j.patcog.2008.07.004
Shao, Yuan-Hai, Li, Chun-Na, Liu, Ming-Zeng, Wang, Zhen, Deng, Nai-Yang (2018) Sparse L-norm least squares support vector machine with feature selection. Pattern Recognition, 78. 167-181 doi:10.1016/j.patcog.2018.01.016
Wang, Siqi, Liu, Qiang, Zhu, En, Porikli, Fatih, Yin, Jianping (2018) Hyperparameter selection of one-class support vector machine by self-adaptive data shifting. Pattern Recognition, 74. 198-211 doi:10.1016/j.patcog.2017.09.012
Ding, Shifei, Zhang, Xiekai, An, Yuexuan, Xue, Yu (2017) Weighted linear loss multiple birth support vector machine based on information granulation for multi-class classification. Pattern Recognition, 67. 32-46 doi:10.1016/j.patcog.2017.02.011
Kefi-Fatteh, Takoua, Ksantini, Riadh, Kaâniche, Mohamed-Bécha, Bouhoula, Adel (2019) A novel incremental one-class support vector machine based on low variance direction. Pattern Recognition, 91. 308-321 doi:10.1016/j.patcog.2019.02.027
 
and/or  
Mindat.org is an outreach project of the Hudson Institute of Mineralogy, a 501(c)(3) not-for-profit organization.
Copyright © mindat.org and the Hudson Institute of Mineralogy 1993-2025, except where stated. Most political location boundaries are © OpenStreetMap contributors. Mindat.org relies on the contributions of thousands of members and supporters. Founded in 2000 by Jolyon Ralph.
To cite: Ralph, J., Von Bargen, D., Martynov, P., Zhang, J., Que, X., Prabhu, A., Morrison, S. M., Li, W., Chen, W., & Ma, X. (2025). Mindat.org: The open access mineralogy database to accelerate data-intensive geoscience research. American Mineralogist, 110(6), 833–844. doi:10.2138/am-2024-9486.
Privacy Policy - Terms & Conditions - Contact Us / DMCA issues - Report a bug/vulnerability Current server date and time: August 19, 2025 07:29:52
Go to top of page