• DocumentCode
    2733803
  • Title

    Data mining with Clementine

  • Author

    Khabaza, Tom ; Shearer, Colin

  • fYear
    1995
  • fDate
    34732
  • Firstpage
    42370
  • Lastpage
    42374
  • Abstract
    Data mining is the extraction of useful information or knowledge from bodies of data. Data mining is also sometimes referred to as knowledge discovery in databases. Clementine is a comprehensive, integrated toolkit which provides active support for data mining in the form of neural network and rule induction learning techniques, passive support in the form of visualisation, statistical and browsing facilities, and peripheral support for data access and manipulation. Clementine´s visual programming interface provides an environment which is easy to use for technological experts and non-experts alike, and provides a convenient organising framework for any data mining technique. Clementine makes machine learning accessible to non-experts. Clementine also goes beyond simple organisational advantages because it reduces the time taken to perform data mining experiments by one to two orders of magnitude. This means that experiments which would previously have been impractical in any realistic project are made possible by Clementine, effectively opening up new areas of exploration. The first commercial version of Clementine is currently on the market and is attracting a great deal of interest. Future versions will extend the machine learning facilities and provide many other new features. The utility of Clementine will continue to grow, and to provide new possibilities for data mining
  • fLanguage
    English
  • Publisher
    iet
  • Conference_Titel
    Knowledge Discovery in Databases, [IEE Colloquium on]
  • Conference_Location
    London
  • Type

    conf

  • DOI
    10.1049/ic:19950121
  • Filename
    478345