A cluster based prototype reduction for online classification

Kemilly Dearo Garcia, André C.P.L.F. de Carvalho, Joao Mendes-Moreira

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

    3 Citations (Scopus)

    Abstract

    Data stream is a challenging research topic in which data can continuously arrive with a probability distribution that may change over time. Depending on the changes in the data distribution, different phenomena can occur, for example, a concept drift. A concept drift occurs when the concepts associated with a dataset change when new data arrive. This paper proposes a new method based on k-Nearest Neighbors that implements a sliding window requiring less instances stored for training than existing methods. For such, a clustering approach is used to summarize data by placing labeled instances considered similar in the same cluster. Besides, instances close to the uncertainty border of existing classes are also stored, in a sliding window, to adapt the model to concept drift. The proposed method is experimentally compared with state-of-the-art classifiers from the data stream literature, regarding accuracy and processing time. According to the experimental results, the proposed method has better accuracy and less time consumption when fewer information about the concepts are stored in a single sliding window.
    Original languageEnglish
    Title of host publicationIntelligent Data Engineering and Automated Learning - IDEAL 2018
    Subtitle of host publication19th International Conference, Madrid, Spain, November 21–23, 2018, Proceedings, Part I
    EditorsHujun Yin, David Camacho, Paulo Novais, Antonio J. Tallón-Ballesteros
    PublisherSpringer
    Pages603-610
    Number of pages8
    ISBN (Electronic)978-3-030-03493-1
    ISBN (Print)978-3-030-03492-4
    DOIs
    Publication statusE-pub ahead of print/First online - 9 Nov 2018
    Event19th International Conference on Intelligent Data Engineering and Automated Learning 2018 - Autonomous University of Madrid, Madrid, Spain
    Duration: 21 Nov 201823 Nov 2018
    Conference number: 19
    https://aida.ii.uam.es/ideal2018/#!/main

    Publication series

    NameLecture Notes in Computer Science
    PublisherSpringer, Cham
    Volume11314
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349

    Conference

    Conference19th International Conference on Intelligent Data Engineering and Automated Learning 2018
    Abbreviated titleIDEAL 2018
    CountrySpain
    CityMadrid
    Period21/11/1823/11/18
    Internet address

    Fingerprint Dive into the research topics of 'A cluster based prototype reduction for online classification'. Together they form a unique fingerprint.

    Cite this