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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
  • Hendrik Blockeel
Impact factor
7.5 (2022)
5 year impact factor
6.3 (2022)
Submission to first decision (median)
28 days
Downloads
1,349,126 (2023)

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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. Current Contents/Engineering, Computing and Technology
  9. DBLP
  10. Dimensions
  11. EBSCO
  12. EI Compendex
  13. Google Scholar
  14. INSPEC
  15. Japanese Science and Technology Agency (JST)
  16. Mathematical Reviews
  17. Naver
  18. OCLC WorldCat Discovery Service
  19. Portico
  20. ProQuest
  21. SCImago
  22. SCOPUS
  23. Science Citation Index Expanded (SCIE)
  24. TD Net Discovery Service
  25. UGC-CARE List (India)
  26. Wanfang
  27. zbMATH
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