rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Supervised and Unsupervised Ensemble Methods and their Applications
  name:
    name part: Okun, Oleg.
    role:
      role term: editor.
  name:
    name part: Valentini, Giorgio.
    role:
      role term: editor.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: gw
    date issued: 2008
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XIV, 182 p. online resource.
  abstract: This book was inspired by the last argument and resulted from the workshop on Supervised and Unsupervised Ensemble Methods and their Applications (briefly, SUEMA) organized on June 4, 2007 in Girona, Spain. This workshop was held in conjunction with the 3rd Iberian Conference on Pattern Recognition and Image Analysis and was intended to encompass the progress in the ensemble applications made by the Iberian and international scholars. Despite its small format, SUEMA attracted researchers from Spain, Portugal, France, USA, Italy, and Finland, who presented interesting ideas about using the ensembles in various practical cases. Encouraged by this enthusiastic reply, we decided to publish workshop papers in an edited book, since CD proceedings were the only media distributed among the workshop participants at that time. The book includes nine chapters divided into two parts, assembling contributions to the applications of supervised and unsupervised ensembles. The book is intended to be primarily a reference work. It could be a good complement to two excellent books on ensemble methodology – “Combining pattern classifiers: methods and algorithms” by Ludmila Kuncheva (John Wiley & Sons, 2004) and “Decomposition methodology for knowledge discovery and data mining: theory and applications” by Oded Maimon and Lior Rokach (World Scientific, 2005).
  table of contents: Ensembles of Clustering Methods and Their Applications -- Cluster Ensemble Methods: from Single Clusterings to Combined Solutions -- Random Subspace Ensembles for Clustering Categorical Data -- Ensemble Clustering with a Fuzzy Approach -- Collaborative Multi-Strategical Clustering for Object-Oriented Image Analysis -- Ensembles of Classification Methods and Their Applications -- Intrusion Detection in Computer Systems Using Multiple Classifier Systems -- Ensembles of Nearest Neighbors for Gene Expression Based Cancer Classification -- Multivariate Time Series Classification via Stacking of Univariate Classifiers -- Gradient Boosting GARCH and Neural Networks for Time Series Prediction -- Cascading with VDM and Binary Decision Trees for Nominal Data -- Erratum.
  note: edited by Oleg Okun, Giorgio Valentini.
  subject:
    topic: Computer science
  subject:
    topic: Artificial intelligence
  subject:
    topic: Applied mathematics
  subject:
    topic: Engineering mathematics
  subject:
    topic: Computer Science
  subject:
    topic: Artificial Intelligence (incl. Robotics)
  subject:
    topic: Appl.Mathematics/Computational Methods of Engineering
  classification: Q334-342
  classification: TJ210.2-211.495
  classification: 006.3
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Studies in Computational Intelligence, 126
  identifier: 9783540789819
  identifier: http://dx.doi.org/10.1007/978-3-540-78981-9
  record info:
    record creation date: 100301
    record change date: 20151204154301.0
    record identifier: 978-3-540-78981-9