Machine Learning
Impact Factor Trend (2018–2026)
Clarivate IF trend for Machine Learning
SCImago Journal Rank citation prestige weighting
183 papers with at least that number of citations each
Aims & Scope
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; Scientific discovery; Information retrieval; 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, inductive logic programming, case-based methods, ensemble methods, clustering, etc.); Reinforcement learning; Evolution-based methods; Explanation-based learning; Analogical learning methods; Automated knowledge acquisition; Learning from instruction; Visualization of patterns in data; Learning in integrated architectures; Multistrategy learning; Multi-agent learning.
Special Issues
Calls for PapersNo active Calls for Papers found for this journal.
WoS Categories & Quartiles
Detailed JCR / JCI category rankings and quartile breakdown from Clarivate
COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Annual Historical Statistics & Publications
Track annual publication volume, total citations, and Impact Factor evolution
SCImago & Scopus Journal Intelligence
Global SCImago ranking, SJR prestige index, Scopus coverage, and societal policy impact
Weighted prestige citation metric per document indexed in the Scopus database.
Average citations received per document published in the 2-year window.
Estimated Article Processing Charge for Open Access publication.
Scopus 3-Year Publication & Citation Window
Aggregated from Scopus database across the 3-year SJR evaluation window.
Societal Impact & Inclusivity (SCImago)
Citations in government and international policy documents
Percentage of female authors published in the journal
Real-world societal policy reach and author gender diversity tracked by SCImago.
Scopus Subject Categories
Journal Metrics & Citation Visualizations
Total Cites vs Self-Cites
Evaluation of scholarly independence and citation reach
Citations per Document
Citation metric windows across 2, 3, and 4 years
Chinese Academy of Sciences (CAS) Classification
Major / minor zone classification and CAS Early Warning List history
Academic Intelligence Overview & Context
ImpaQ AnalysisMachine Learning (acronym: mach, abbr: MACH LEARN, ISSN: 0885-6125) is a peer-reviewed international scholarly journal in the field of Engineering & Technology, published by Springer US in United States since 1986. The periodical holds a Journal Impact Factor (JIF) of 4.90, ranking in quartile Q2 of Web of Science (SCIE), a Scopus SJR indicator of 1.027 (Q1), an H-index of 183.
The journal enforces rigorous peer evaluation with a publication frequency of Monthly, an annual output of approximately 159 scientific articles. In terms of accessibility and author fees, it operates under the Hybrid model with an estimated APC of $3,562 USD. It serves as a benchmark publication platform for academics, researchers, and doctoral candidates seeking global research visibility.
Publishing & Editorial Information
Detailed publisher, peer-review turnaround, and publication cycle specifications
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