SafetyLit Journal Details

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Machine learning

Abbreviation: Mach. Learn.

Published by: Holtzbrinck Springer Nature Publishing Group

Publisher Location: Boston, MA, USA

Journal Website:
https://link.springer.com/journal/10994/volumes-and-issues

Range of citations in the SafetyLit database: 2023; 112(10) -- 2023; 112(10)

Publication Date Range: 1986 --

Number of articles from this journal included in the SafetyLit database: 1
(Download all articles from this journal in CSV format.)

pISSN = 0885-6125 | eISSN = 1573-0565
LCCN = 86655869 | USNLM = 9881780 | CODEN = MALEEZ | OCLC = 12681958 | CONSER = sn 85009087

Find a library that holds this journal: http://worldcat.org/issn/08856125

Journal Language(s): English

Aims and Scope (from publisher): 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.

Articles in database by volume, issue.