• DocumentCode
    3263659
  • Title

    Deciding the Convex Separability of Pattern Sets

  • Author

    Takács, Gábor ; Pataki, Béla

  • Author_Institution
    Budapest Univ. of Technol. & Econ., Budapest
  • fYear
    2007
  • fDate
    6-8 Sept. 2007
  • Firstpage
    278
  • Lastpage
    280
  • Abstract
    Deciding the convex separability of the classes is an interesting question in the data exploration phase of building classification systems. In this paper we propose an efficient algorithm for deciding the convex separability of two point sets in Rd. We compare our algorithm with conventional methods on 6 benchmark problems, and demonstrate that our algorithm is significantly faster.
  • Keywords
    convex programming; pattern classification; set theory; classification systems; point set convex separability; Conferences; Data acquisition; Economic forecasting; Information systems; Intelligent structures; Intelligent systems; Machine learning; Machine learning algorithms; Pattern recognition; Polynomials; Convex Hull; Data Exploration; Linear Classifiers; Pattern Recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications, 2007. IDAACS 2007. 4th IEEE Workshop on
  • Conference_Location
    Dortmund
  • Print_ISBN
    978-1-4244-1347-8
  • Electronic_ISBN
    978-1-4244-1348-5
  • Type

    conf

  • DOI
    10.1109/IDAACS.2007.4488421
  • Filename
    4488421
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3263659