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Introducing the International Journal of Machine Learning and Applications
Henry O. Nyongesa1
1Department of Computer Science, University of the Western Cape, South Africa
Henry Nyongesa
hnyongesa@uwc.ac.za
Private Bag X17, Belville
7535, South Africa111http://dx.doi.org/10.4102/ijmla.v1i1.1
Nyongesa HO. Introducing the International Journal of Machine Learning and Applications. Int J Machine Learn Appl. 2012;1(1), Art. #1, 1 page. http://dx.doi.org/10.4102/ijmla.v1i1.1
© 2012. The Authors.
Licensee: AOSIS OpenJournals. This work
is licensed under the
Creative Commons
Attribution License.
Machine learning is currently one of the most active and exciting areas of research in computational and engineering sciences. Varied paradigms of machine learning are being applied to solve complex real-world problems in diverse fields of application from biology and medicine to chemistry and the environment, economics and finance, material sciences and natural language processing. Machine learning comprises different human- and nature-inspired algorithms, such as case-based and deductive reasoning, expert and logic systems, evolutionary and other biomimetic schemes. It could be said to comprise all current forms of computational artificial intelligence.
What machine learning is or is not could be a topic of discourse. What is not in contestation, however, is that machine learning involves computers being applied to perform useful tasks. Mitchell’s definition of machine learning is therefore a relevant cornerstone. The International Journal of Machine Learning and Applications (IJMLA) aims to be a confluence of scholarly discourse in the application of computational techniques to solve real-world problems. Our goal is to publish peer-reviewed original research, surveys, reviews and applications of machine learning. IJMLA will be published online as an open access journal, enabling immediate, worldwide, open access to the full text of research articles in the best interests of the scientific community. Published articles will also be accessible through popular scientific citation engines.
The scope of the journal covers applications that combine systems theory with computational techniques. These include, but are not limited to:
modelling and simulation
decision-support systems
operations research
computer vision, signal and image processing
data- and text-mining techniques
natural language processing.
On the theoretical side, we invite articles on various areas of artificial and computational intelligence, including neurocomputing, fuzzy systems, evolutionary learning, swarm intelligence and other nature-inspired algorithms.
Our Editorial Board comprises leading scholars in their respective disciplines from across the globe. We also invite leading academics, researchers and industrialists to be part of the journal as members of the board, editors and peer reviewers.
Editorial Board
H.O. Nyongesa, University of the Western Cape, South Africa (Editor-in-Chief)
B. Manderick, Vrije Unviversity Brussel, Brussels
G. Magoulas, University of London, UK
M. Mahfouf, University of Sheffield, UK
D. Walton, University of Manitoba, UK
G. Venayagamoorthy, University of Missouri Science &Technology, USA
M. Rodrigues, Sheffield Hallam University, UK
D. Wunsch, University of Missouri S&T, UK
J-R. Tapamo, University of KwaZulu-Natal, South Africa
P. Rosin, University of Cardiff, UK
B. Manderick, Vrije Unviversity Brussel, Belgium
G. Magoulas, University of London, UK
M. Mahfouf, University of Sheffield, UK
D. Walton, University of Manitoba, UK
G. Venayagamoorthy, University of Missouri Science &Technology, USAM. Rodrigues, Sheffield Hallam University, UK
D. Wunsch, University of Missouri Science &Technology, USA
J-R. Tapamo, University of KwaZulu-Natal, SA
P. Rosin, University of Cardiff, UK
I hope that you will support this journal as either a contributing author or reader.
Editor in chief
Henry O. Nyongesa
International Journal of Machine Learning and Applications