• Login
    View Item 
    •   DSpace Home
    • Repositorio UPR
    • Seminario Interuniversitario de Investigación en Ciencias Matemáticas (SIDIM)
    • View Item
    •   DSpace Home
    • Repositorio UPR
    • Seminario Interuniversitario de Investigación en Ciencias Matemáticas (SIDIM)
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    On Parallel Methods for Classifying Time Series Data

    Thumbnail
    View/Open
    On Parallel.pdf (899.8Kb)
    Date
    2013-03-01
    Author
    Rivera Hazim, Edwardo S.
    Metadata
    Show full item record
    Abstract
    Data mining algorithms are crucial in the analysis of many real data-intensive problems. The Symbolic Aggregate Approximation (SAX) algorithm is being used widely by researchers to analyze time series and streaming data. Previous work done by P. Ordóñez et. al. has shown that it is possible to classify a patient's data by using a combination of SAX and the Bag-of-Patterns algorithm (BoP). To our knowledge, parallel implementations for these algorithms have not been proposed yet.
    URI
    http://hdl.handle.net/123456789/2737
    Collections
    • Seminario Interuniversitario de Investigación en Ciencias Matemáticas (SIDIM)

    Contact Us | Send Feedback
     

     

    Browse

    All of DSpaceCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

    My Account

    LoginRegister

    Contact Us | Send Feedback