Article Information

Author:
Henry O. Nyongesa1

Affiliation:
1Department of Computer Science, University of the Western Cape, South Africa

Correspondence to:
Henry Nyongesa

Postal address:
Private Bag X17, Belville 7535, South Africa

How to cite this article:
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

Copyright Notice:
© 2012. The Authors. Licensee: AOSIS OpenJournals.

This is an Open Access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Introducing the International Journal of Machine Learning and Applications

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, 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, USA
M. 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


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