Multi-label optimal margin distribution machine Article Swipe

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Zhi-Hao Tan , Peng Hui Tan , Yuan Jiang , Zhi‐Hua Zhou ·

YOU? · · 2019 · Open Access · · DOI: https://doi.org/10.1007/s10994-019-05837-8

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Support Vector Machine

Computer Science

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Margin (machine learning) Support vector machine Computer science Convergence (economics) Artificial intelligence Generalization Machine learning Rank (graph theory) Variance (accounting) Distribution (mathematics) Mathematical optimization Margin classifier Pattern recognition (psychology) Algorithm Mathematics Combinatorics Economics Accounting Mathematical analysis Economic growth Business

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Type: article
Language: en
Landing Page: https://doi.org/10.1007/s10994-019-05837-8
PDF: https://link.springer.com/content/pdf/10.1007/s10994-019-05837-8.pdf
OA Status: bronze
Cited By: 28
References: 43
Related Works: 10
OpenAlex ID: https://openalex.org/W3012018197

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OpenAlex ID: https://openalex.org/W3012018197

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DOI: https://doi.org/10.1007/s10994-019-05837-8

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Title: Multi-label optimal margin distribution machine

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Type: article

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Language: en

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Publication year: 2019

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Publication date: 2019-10-10

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Authors: Zhi-Hao Tan, Peng Hui Tan, Yuan Jiang, Zhi‐Hua Zhou

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Landing page: https://doi.org/10.1007/s10994-019-05837-8

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PDF URL: https://link.springer.com/content/pdf/10.1007/s10994-019-05837-8.pdf

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OA status: bronze

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Concepts: Margin (machine learning), Support vector machine, Computer science, Convergence (economics), Artificial intelligence, Generalization, Machine learning, Rank (graph theory), Variance (accounting), Distribution (mathematics), Mathematical optimization, Margin classifier, Pattern recognition (psychology), Algorithm, Mathematics, Combinatorics, Economics, Accounting, Mathematical analysis, Economic growth, Business

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Cited by: 28

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Citations by year (recent): 2024: 5, 2023: 5, 2022: 9, 2021: 5, 2020: 4

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References (count): 43

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Related works (count): 10

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institutions_distinct_count	4
citation_normalized_percentile.value	0.92201972
citation_normalized_percentile.is_in_top_1_percent	False
citation_normalized_percentile.is_in_top_10_percent	True