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  • 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. ...
  • Shang, Changjing; Barnes, Dave (2013-03)
    This paper presents a novel application of advanced machine learning techniques for Mars terrain image classification. Fuzzy-rough feature selection (FRFS) is adapted and then employed in conjunction with Support Vector ...
  • 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 ...
  • Shen, Qiang; Mac Parthaláin, Neil; Jensen, Richard (2008-09-29)
    The accuracy of methods for the detection of mammographic abnormaility is heavily related to breast tissue characteristics. A breast with high tissue density will have reduced sensitivity in terms of detection. Also, breast ...
  • 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 ...
  • 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 ...
  • 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 ...
  • Lee, David; Lupotto, Elisabetta; Powell, Wayne (2009-05-02)
    The mutations that convey the white pericarp phenotype to rice (Oryza sativa subsp. japonica) are in a regulatory gene, Rc. We have identified a genetic difference between the cultivar ‘Perla’ and its natural red rice ...
  • Williams, Howard (2005-09-01)
  • Alison (Peter Lang, 2002)
    Should The Merchant of Venice be staged post-Holocaust? How was Antigone (an icon of noble suffering in the Western liberal humanist tradition) received in Apartheid-riven South Africa? These are some of the questions ...
  • Gadarn 
    Prosiect AHRC ar Welsh Genealogies P.C. Bartrum; AHRC Project on P.C. Bartrum’s Welsh Genealogies (Adran y Gymraeg, Prifysgol Aberystwyth/Welsh Department, Aberystwyth University, 2010)
  • Wilkins, Pete W.; Lovatt, J. Alan (2011-06-01)
    In Western Europe and elsewhere there has been considerable effort during the last 100 years devoted to improving perennial ryegrass (Lolium perenne L.) for agriculture. The first persistent cultivars to be widely used ...
  • Harris, Meinir Elin (Aberystwyth University, 2003)
    Un ystyr galanas oedd 'lladdedigaeth'. Ar ol Haddedigaeth bodolai cyflwr o elyniaeth, sef galanas, rhwng cenhedloedd y Iladdwr a'r Iladdedig. I ddod A'r elyniaeth i ben roedd yn rhaid dial neu dalu iawndal. Cyfatebai'r ...
  • David Andrew (Walter de Gruyter, 2013-10-01)
  • Gamage 01 
    Prosiect AHRC ar Welsh Genealogies P.C. Bartrum; AHRC Project on P.C. Bartrum’s Welsh Genealogies (Adran y Gymraeg, Prifysgol Aberystwyth/Welsh Department, Aberystwyth University, 2010)