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    Classification, Novelty Detection and Clustering for Point Pattern Data

    Tran Q 2017.pdf (12.56Mb)
    Access Status
    Open access
    Authors
    Tran, Quang Nhat
    Date
    2017
    Supervisor
    Prof. Ba-Ngu Vo
    Type
    Thesis
    Award
    PhD
    
    Metadata
    Show full item record
    Faculty
    Science and Engineering
    School
    Department of Electrical and Computer Engineering
    URI
    http://hdl.handle.net/20.500.11937/59025
    Collection
    • Curtin Theses
    Abstract

    Point pattern data, also known as multiple instance data or bags, are abundant in nature and applications. However, machine learning problems for point patterns have not received much attention. In this work, we solve three fundamental machine learning problems, namely classification, novelty detection, and clustering, for point pattern data using two approaches: one with knowledge of the underlying data model (model-based approach), and one without (distance-based approach).

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