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Machine Learning Journal - Springer Nature | 2021 Impact Factor:5.414|Cite Score:7.2|Q1

Machine Learning Journal

Impact Factor and Journal Rank of Machine Learning Journal


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, including but not limited to: Learning Problems: Classification, regression, recognition, and prediction; Problem solving and planning; Reasoning and inference; Data mining; Web mining.

Journal Home:  Journal Homepage

Editor-in-Chief:  Hendrik Blockeel

scope: Natural language processing; Design and diagnosis; Vision and speech perception; Robotics and control; Combinatorial optimization; Game playing; Industrial, financial, and scientific applications of all kinds. Learning Methods: Supervised and unsupervised learning methods (including learning decision and regression trees, rules, connectionist networks, probabilistic networks and other statistical models.

Print ISSN:  08856125,

Electronic ISSN:  15730565

Abstracting and Indexing:  Scopus SCience Citation Index Expanded

Imapct Factor 2021:  5.414

Subject Area and Category:   Computer Science Artificial Intelligence Software

Publication Frequency:  

H Index:  153

Best Quartile:

Q1:  Software




Cite Score:  7.2

SNIP:  2.348

Journal Rank(SJR):  1.64

Guidelines for Authors: Machine Learning Author Guidelines

Publisher:  Springer Netherlands

Country:  Netherlands