Browsing Cyfrifiadureg / Computer Science by Title

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Browsing Cyfrifiadureg / Computer Science by Title

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  • Jensen, Richard (2011-12-31)
  • Jensen, Richard; Shen, Qiang (2005-01-01)
    Feature selection refers to the problem of selecting those input features that are most predictive of a given outcome; a problem encountered in many areas such as machine learning, pattern recognition and signal processing. ...
  • Jensen, Richard; Shen, Qiang (2005)
    Crisp decision trees are one of the most popular classification algorithms in current use within data mining and machine learning. However, although they possess many desirable features, they lack the ability to model ...
  • Jensen, Richard; Cornelis, Chris (2010)
    Rough set theory provides a useful mathematical foundation for developing automated computational systems that can help understand and make use of imperfect knowledge. Since its introduction, this theory has been successfully ...
  • Jensen, Richard; Cornelis, Chris (2011-12-31)
  • Cornelis, Chris; Jensen, Richard (2011-09-07)
    Nearest neighbour (NN) approaches are inspired by the way humans make decisions, comparing a test object to previously encountered samples. In this paper, we propose an NN algorithm that uses the lower and upper approximations ...
  • Verbiest, Nele; Cornelis, Chris; Jensen, Richard (IEEE, 2012)
    This paper proposes a classifier that uses fuzzy rough set theory to improve the Fuzzy Nearest Neighbour (FNN) classifier. We show that previous attempts to use fuzzy rough set theory to improve the FNN algorithm have some ...
  • Vander Heyden, Yvan; Dejaegher, Bieke; Jensen, Richard; Funar-Timofei, Simona; Goodarzi, Mohammad (2011-07-13)
    In cancer chemotherapy, multidrug resistance (MDR) is a major clinical problem which occurs by an influential mechanism and which leads to the failure of cancer chemotherapy and/or a relapse of the cancer. In this study, ...
  • MacParthalain, Neil; Jensen, Richard (2011-07-06)
    Much work has been carried out in the area of fuzzy-rough sets for supervised learning. However, very little has been accomplished for the unsupervised or semi-supervised tasks. For many real-word applications, it is often ...
  • Shen, Qiang; Jensen, Richard (2007)
    Attribute selection (AS) refers to the problem of selecting those input attributes or features that are most predictive of a given outcome; a problem encountered in many areas such as machine learning, pattern recognition ...
  • Shen, Qiang; Galea, Michelle (2004)
    A new approach to fuzzy rule induction from historical data is presented. The implemented system - FRANTIC - is a tested on a simple classification problem against a fuzzy tree induction algorithm, a genetic algorithm, and ...
  • Shen, Qiang (Springer Berlin Heidelberg, 2009)
    Both fuzzy set theory and rough set theory play an important role in data-driven, systems modelling and analysis. They have been successfully applied to building various intelligent decision support systems (amongst many ...
  • Marin-Blázquez, Javier; Shen, Qiang (2008)
    Many real-world problems require the development and application of algorithms that automatically generate human interpretable knowledge from historical data. Most existing algorithms for rule induction from imprecise data ...
  • Hülse, Martin; McBride, Sebastian; Lee, Mark (2010-11)
    Substantial evidence supports the role of lateral intraparietal region (LIP) of the brain as the central processing point where bottom-up visual information is modulated by top-down task information from higher cortical ...
  • Jenkins, Helen Ann; Beckmann, Manfred; Draper, John; Hardy, Nigel William (Springer, 2007)
  • Rowland, Jeremy John (2003)
    EC-based supervised learning has been demonstrated to be an effective approach to forming predictive models in genomics, spectral interpretation, and other problems in modern biology. Longer-established methods such as PLS ...
  • Shen, Qiang; Longzhi, Yang (2011)
    Fuzzy interpolative reasoning has been extensively studied due to its ability to enhance the robustness of fuzzy systems and reduce system complexity. In particular, the scale and move transformation-based approach is able ...
  • Pritchard, Leighton; Corne, D.; Kell, Douglas B.; Winson, Mike K.; Rowland, Jeremy John (2005-06-21)
    In this paper, we generalise a previously-described model of the error-prone polymerase chain reaction (PCR) reaction to conditions of arbitrarily variable amplification efficiency and initial population size. Generalisation ...
  • Snooke, Neal; Shipman, Richard (Springer, 2001-12-11)
    Model based reasoning applied to electrical systems has matured over recent years resulting in deployment of commercial design analysis tools in the automotive industry [1, 41. These tools work at the component level on ...
  • Hülse, Martin (2008-09)
    Biological neural systems and the majority of other real-world networks have topologies significant different from fully or randomly connected structures, which are frequently applied for the definition of artificial neural ...

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