• Login
    View Item 
    •   T-Stór
    • Other
    • Teagasc funded research
    • View Item
    •   T-Stór
    • Other
    • Teagasc funded research
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Browse

    All of T-StórCommunitiesPublication DateAuthorsTitlesSubjectsFunderThis CollectionPublication DateAuthorsTitlesSubjectsFunderProfilesView

    My Account

    LoginRegister

    Information

    Deposit AgreementLicense

    Statistics

    Most Popular ItemsStatistics by CountryMost Popular Authors

    Semi-supervised linear discriminant analysis

    • CSV
    • RefMan
    • EndNote
    • BibTex
    • RefWorks
    Author
    Toher, Deirdre
    Downey, Gerard
    Murphy, Thomas Brendan
    Keyword
    Classification
    Discriminant analysis
    Food authenticity
    Chemometrics--Classification
    Food--Analysis
    Date
    02/07/2012
    
    Metadata
    Show full item record
    Statistics
    Display Item Statistics
    URI
    http://hdl.handle.net/10197/3455
    Citation
    Toher, Deirdre, Downey, Gerard, Murphy, Thomas Brendan : Semi-supervised linear discriminant analysis. Journal of Chemometrics, 25 (12) 2011-12, pp.624-630
    Abstract
    Fisher's linear discriminant analysis is one of the most commonly used and studied classification methods in chemometrics. The method finds a projection of multivariate data into a lower dimensional space so that the groups in the data are well separated. The resulting projected values are subsequently used to classify unlabeled observations into the groups. A semi-supervised version of Fisher's linear discriminant analysis is developed, so that the unlabeled observations are also used in the model fitting procedure. This approach is advantageous when few labeled and many unlabeled observations are available. The semi-supervised linear discriminant analysis method is demonstrated on a number of data sets where it is shown to yield better separation of the groups and improved classification over Fisher's linear discriminant analysis.
    Funder
    Science Foundation Ireland; Teagasc
    ae974a485f413a2113503eed53cd6c53
    http://dx.doi.org/10.1002/cem.1408
    Scopus Count
    Collections
    Food Chemistry & Technology
    Food Quality & Sensory Science
    Teagasc funded research
    Teagasc funded research

    entitlement

     
    DSpace software copyright © 2002-2017  DuraSpace
    Quick Guide | Contact Us | Send Feedback
    Open Repository is a service operated by 
    Atmire NV
     

    Export search results

    The export option will allow you to export the current search results of the entered query to a file. Different formats are available for download. To export the items, click on the button corresponding with the preferred download format.

    By default, clicking on the export buttons will result in a download of the allowed maximum amount of items.

    To select a subset of the search results, click "Selective Export" button and make a selection of the items you want to export. The amount of items that can be exported at once is similarly restricted as the full export.

    After making a selection, click one of the export format buttons. The amount of items that will be exported is indicated in the bubble next to export format.