Machine Learning is an international forum for research on computational approaches to learning. The journal publishes articles reporting substantive results on a wide range of learning methods applied to a variety of learning problems.

The journal features papers that describe research on problems and methods, applications research, and issues of research methodology. Papers making claims about learning problems or methods provide solid support via empirical studies, theoretical analysis, or comparison to psychological phenomena. Applications papers show how to apply learning methods to solve important applications problems. Research methodology papers improve how machine learning research is conducted.

All papers describe the supporting evidence in ways that can be verified or replicated by other researchers. The papers also detail the learning component clearly and discuss assumptions regarding knowledge representation and the performance task.

  • An international forum for research on computational approaches to learning.
  • Reports substantive results on a wide range of learning methods applied to a variety of learning problems.
  • Provides solid support via empirical studies, theoretical analysis, or comparison to psychological phenomena.
  • Shows how to apply learning methods to solve important applications problems.
  • Improves how machine learning research is conducted.

Journal information

Editor-in-Chief
  • Hendrik Blockeel
Publishing model
Hybrid (Transformative Journal). How to publish with us, including Open Access

Journal metrics

5.414 (2021)
Impact factor
5.808 (2021)
Five year impact factor
47 days
Submission to first decision (Median)
1,086,053 (2021)
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About this journal

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. Current Contents/Engineering, Computing and Technology
  9. DBLP
  10. Dimensions
  11. EBSCO Applied Science & Technology Source
  12. EBSCO Associates Programs Source
  13. EBSCO Book Review Digest Plus
  14. EBSCO Computer Science Index
  15. EBSCO Computers & Applied Sciences Complete
  16. EBSCO Discovery Service
  17. EBSCO Engineering Source
  18. EI Compendex
  19. Google Scholar
  20. INSPEC
  21. Japanese Science and Technology Agency (JST)
  22. Journal Citation Reports/Science Edition
  23. Mathematical Reviews
  24. Naver
  25. OCLC WorldCat Discovery Service
  26. Portico
  27. ProQuest Advanced Technologies & Aerospace Database
  28. ProQuest-ExLibris Primo
  29. ProQuest-ExLibris Summon
  30. SCImago
  31. SCOPUS
  32. Science Citation Index
  33. Science Citation Index Expanded (SCIE)
  34. TD Net Discovery Service
  35. UGC-CARE List (India)
  36. WTI AG
  37. Wanfang
  38. zbMATH
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