BIROn - Birkbeck Institutional Research Online

    Estimating the uncertainty of average F1 scores

    Zhang, Dell and Wang, J. and Zhao, X. (2015) Estimating the uncertainty of average F1 scores. In: UNSPECIFIED (ed.) ICTIR '15: Proceedings of the 2015 International Conference on The Theory of Information Retrieval. New York, U.S.: ACM, pp. 317-320. ISBN 9781450338332.

    [img]
    Preview
    Text
    ictir063-zhangA.pdf - Published Version of Record

    Download (277kB) | Preview
    Official URL: http://ictir2015.org/

    Abstract

    In multi-class text classification, the performance (effectiveness) of a classifier is usually measured by micro-averaged and macro-averaged F1 scores. However, the scores themselves do not tell us how reliable they are in terms of forecasting the classifier's future performance on unseen data. In this paper, we propose a novel approach to explicitly modelling the uncertainty of average F1 scores through Bayesian reasoning.

    Metadata

    Item Type: Book Section
    Keyword(s) / Subject(s): Text Classification, Performance Evaluation, Bayesian Inference
    School: Birkbeck Schools and Departments > School of Business, Economics & Informatics > Computer Science and Information Systems
    Research Centre: Birkbeck Knowledge Lab
    Depositing User: Dr Dell Zhang
    Date Deposited: 11 Dec 2015 15:10
    Last Modified: 28 Jul 2019 08:14
    URI: http://eprints.bbk.ac.uk/id/eprint/13586

    Statistics

    Downloads
    Activity Overview
    362Downloads
    191Hits

    Additional statistics are available via IRStats2.

    Archive Staff Only (login required)

    Edit/View Item Edit/View Item