Decision and Inhibitory Trees and Rules for Decision Tables with Many-valued Decisions
The results presented here (including the assessment of a new tool – inhibitory trees) offer valuable tools for researchers in the areas of data mining, knowledge discovery, and machine learning, especially those whose work involves decision tables with m
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Fawaz Alsolami Mohammad Azad Igor Chikalov Mikhail Moshkov
Decision and Inhibitory Trees and Rules for Decision Tables with Many-valued Decisions
Intelligent Systems Reference Library Volume 156
Series Editors Janusz Kacprzyk, Polish Academy of Sciences, Warsaw, Poland Lakhmi C. Jain, Faculty of Engineering and Information Technology, Centre for Artificial Intelligence, University of Technology, Sydney, NSW, Australia; Faculty of Science, Technology and Mathematics, University of Canberra, Canberra, ACT, Australia; KES International, Shoreham-by-Sea, UK; Liverpool Hope University, Liverpool, UK
The aim of this series is to publish a Reference Library, including novel advances and developments in all aspects of Intelligent Systems in an easily accessible and well structured form. The series includes reference works, handbooks, compendia, textbooks, well-structured monographs, dictionaries, and encyclopedias. It contains well integrated knowledge and current information in the field of Intelligent Systems. The series covers the theory, applications, and design methods of Intelligent Systems. Virtually all disciplines such as engineering, computer science, avionics, business, e-commerce, environment, healthcare, physics and life science are included. The list of topics spans all the areas of modern intelligent systems such as: Ambient intelligence, Computational intelligence, Social intelligence, Computational neuroscience, Artificial life, Virtual society, Cognitive systems, DNA and immunity-based systems, e-Learning and teaching, Human-centred computing and Machine ethics, Intelligent control, Intelligent data analysis, Knowledge-based paradigms, Knowledge management, Intelligent agents, Intelligent decision making, Intelligent network security, Interactive entertainment, Learning paradigms, Recommender systems, Robotics and Mechatronics including human-machine teaming, Self-organizing and adaptive systems, Soft computing including Neural systems, Fuzzy systems, Evolutionary computing and the Fusion of these paradigms, Perception and Vision, Web intelligence and Multimedia. ** Indexing: The books of this series are submitted to ISI Web of Science, SCOPUS, DBLP and Springerlink.
More information about this series at http://www.springer.com/series/8578
Fawaz Alsolami Mohammad Azad Igor Chikalov Mikhail Moshkov •
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Decision and Inhibitory Trees and Rules for Decision Tables with Many-valued Decisions
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Fawaz Alsolami Computer, Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal, Saudi Arabia
Mohammad Azad Computer, Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal, Saudi Arabia
Igor Chikalov Computer, Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal, Saudi Arabia
Mikhail Moshkov Computer, Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Techno
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