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 journals provide forum and motivates scientists, researchers, academics, engineers, and practitioners in all aspects to share their professional and academic knowledge in the fields computing, engineering, humanities, economics, social sciences, management, medical science, and related disciplines. Online Journals also aims to reach a large number of readers worldwide with original and current research work completed on the vital issues of the above important disciplines. The journals permit all readers to read, view, download and print the full-text of all published articles without any subscription or restrictions.
Last date updated on January, 2021