Machine Learning

ISSN: 0885-6125

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Machine Learning Q1 Unclaimed

Springer Netherlands Netherlands
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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. It has an SJR impact factor of 1,72.

Type: Journal

Type of Copyright:

Languages: English

Open Access Policy: Open Choice

Type of publications:

Publication frecuency: -

Price

2290 €

Inmediate OA

NPD

Embargoed OA

0 €

Non OA

Metrics

Machine Learning

1,72

SJR Impact factor

169

H Index

219

Total Docs (Last Year)

368

Total Docs (3 years)

11327

Total Refs

2427

Total Cites (3 years)

356

Citable Docs (3 years)

5.09

Cites/Doc (2 years)

51.72

Ref/Doc

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