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Machine Learning

Machine Learning

Publishing model:
Hybrid
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Overview

Machine Learning is an international forum focusing on computational approaches to learning.

  • Reports substantive results on a wide range of learning methods applied to various learning problems.
  • Provides robust support through empirical studies, theoretical analysis, or comparison to psychological phenomena.
  • Demonstrates how to apply learning methods to solve significant application problems.
  • Improves how machine learning research is conducted.
  • Prioritizes verifiable and replicable supporting evidence in all published papers.

Editor-in-Chief
  • Michelangelo Ceci
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Journal metrics

Journal Impact Factor
2.9 (2024)
5-year Journal Impact Factor
6.6 (2024)
Submission to first decision (median)
5 days
Downloads
2.4M (2025)

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Latest articles

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This journal has 625 open access articles

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Journal information

Electronic ISSN
1573-0565
Print ISSN
0885-6125
Abstracted and indexed in
  1. ACM Digital Library
  2. ANVUR
  3. BFI List
  4. Baidu
  5. CLOCKSS
  6. CNKI
  7. CNPIEC
  8. Chinese Academy of Medical Science (CAMS)
  9. Current Contents/Engineering, Computing and Technology
  10. DBLP
  11. Dimensions
  12. EBSCO
  13. EI Compendex
  14. Google Scholar
  15. INSPEC
  16. Japanese Science and Technology Agency (JST)
  17. Mathematical Reviews
  18. Naver
  19. OCLC WorldCat Discovery Service
  20. Ovid Discovery
  21. Portico
  22. ProQuest
  23. SCImago
  24. SCOPUS
  25. Science Citation Index Expanded (SCIE)
  26. TD Net Discovery Service
  27. Wanfang
  28. eLibrary.ru
  29. zbMATH
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