Generating Explanations from Support Vector Machines for Psychological Classifications

An explanation capability is crucial in security-sensitive domains, such as medical applications. Although support vector machines (SVMs) have shown superior performance in a range of classification and regression tasks, SVMs, like artificial neural netwo

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Margaret Lech Insu Song Peter Yellowlees Joachim Diederich (Eds.)

Mental Health Informatics

13

491

Studies in Computational Intelligence Volume 491

Series Editor Janusz Kacprzyk, Polish Academy of Sciences, Warsaw, Poland e-mail: [email protected]

For further volumes: http://www.springer.com/series/7092

About this Series The series ‘‘Studies in Computational Intelligence’’ (SCI) publishes new developments and advances in the various areas of computational intelligence—quickly and with a high quality. The intent is to cover the theory, applications, and design methods of computational intelligence, as embedded in the fields of engineering, computer science, physics and life sciences, as well as the methodologies behind them. The series contains monographs, lecture notes and edited volumes in computational intelligence spanning the areas of neural networks, connectionist systems, genetic algorithms, evolutionary computation, artificial intelligence, cellular automata, self-organizing systems, soft computing, fuzzy systems, and hybrid intelligent systems. Of particular value to both the contributors and the readership are the short publication timeframe and the world-wide distribution, which enable both wide and rapid dissemination of research output.

Margaret Lech Insu Song Peter Yellowlees Joachim Diederich •



Editors

Mental Health Informatics

123

Editors Margaret Lech School of Electrical and Computer Engineering RMIT University Melbourne Australia

Peter Yellowlees Department of Psychiatry and Behavioral Sciences University of California, Davis Sacramento USA

Insu Song School of Business and IT James Cook University Australia Singapore

Joachim Diederich Psychology Network Pty Ltd Brisbane Australia

ISSN 1860-949X ISBN 978-3-642-38549-0 DOI 10.1007/978-3-642-38550-6

ISSN 1860-9503 (electronic) ISBN 978-3-642-38550-6 (eBook)

Springer Heidelberg New York Dordrecht London Library of Congress Control Number: 2013951505  Springer-Verlag Berlin Heidelberg 2014 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. Exempted from this legal reservation are brief excerpts in connection with reviews or scholarly analysis or material supplied specifically for the purpose of being entered and executed on a computer system, for exclusive use by the purchaser of the work. Duplication of this publication or parts thereof is permitted only under the provisions of the Copyright Law of the Publisher’s location, in its current version, and permission for use must always be obtained from Springer. Permissions for use may be obtained through RightsLink at the Copyright Clearance Center. Violations are liabl