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Machine Learning Journal - Springer Nature | 2020 Impact Factor:2.940|Cite Score:6.1|Q1


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 2020:  2.940

Subject Area and Category:   Computer Science Artificial Intelligence Software

Publication Frequency:  

H Index:  152

Best Quartile:

Q1:  Software




Cite Score:  6.1

SNIP:  2.031

Journal Rank(SJR):  0.667

Publisher:  Springer Netherlands

Country:  Netherlands